Response Of System Research Articles

OS ASPECTOS SOBRE A LEGITIMIDADE DA AÇÃO POLICIAL MILITAR E A RESPONSABILIDADE JUDICIAL: UMA ANÁLISE DA VIOLÊNCIA INSTITUCIONAL E DA IMPUNIDADE

The present study aimed to analyze aspects related to the legitimacy of military police actions and judicial accountability, focusing on institutional violence and impunity. The research begins by examining how the legitimacy of police actions is constructed and perceived by society, and it further investigates the legal consequences of police actions, especially when they involve abuse of authority or excessive use of force. In this context, it highlights the importance of assessing the legal and ethical boundaries of military police actions and the role of the justice system in holding these actions accountable. For the development of this study, a bibliographic and qualitative methodology was adopted. The analysis was based on existing literature on the topic, including legislation, academic articles, theses, dissertations, and other relevant documents. This approach allowed for an in-depth understanding of the historical, cultural, and institutional processes that influence both police conduct and the judicial system's response in cases of institutional violence.The results indicate that, in many cases, there is a gap between what is established by law and the actual practices on the streets, particularly regarding the use of force and abuses committed by certain security agents. It was observed that impunity in specific cases of police violence generates a perception of distrust in society toward the institutions responsible for enforcing the law, which directly impacts the legitimacy of police actions.

Characterizing the interaction effects of modular components on transtibial prosthesis stance-phase mechanical behavior

Background: Despite evidence that passive prosthesis mechanical properties can directly affect user experience, prosthetists have access to minimal information regarding the mechanical interactions between a prosthetic foot and proximal modular componentry. Objectives: This study quantified the stance phase mechanical behavior of a transtibial prosthetic system through the addition of passive modular componentry to a dynamic response (DR) foot. Study Design: Repeated measures, mechanical characterization. Methods: Maximum displacement and energy return were measured with a materials test machine simulating initial, mid, and terminal stances. Twelve conditions were tested: a DR foot in combination with a hydraulic ankle at 2 resistance settings and 3 different shock-absorbing pylons (SAPs). The roll-over shape of the DR foot with and without hydraulic ankle was measured using a test rig. Results: Adding modular passive components altered displacement and energy return, displaying independent and interaction effects. Generally, the hydraulic ankle and SAP reduced energy return (up to 18%) but decreased (up to 51%) and increased (up to 88%) displacement, respectively, while the combined properties were more complex. Roll-over shape radii decreased with increasing load for the foot alone but exhibited a nonlinear response with the addition of the ankle. Conclusions: Inclusion of modular components in a transtibial prosthetic system can have complex mechanical interactions that independently affect the system's response to load. It is important for clinicians to be aware of the cumulative effects of these interactions to inform the tuning of transtibial prosthesis mechanical behavior. Combinations of hydraulic ankles and SAPs can help clinicians adjust the prosthesis to achieve a balance between user comfort and energy return.

Multistable dynamics and chaos in a system consisting of an inertial neuron coupled to a van der Pol oscillator

Abstract We consider a dynamical system consisting of a van der Pol oscillator linearly coupled to an inertial neuron with two wells potential. Analytical studies are conducted focusing on the energy computation, the dissipation and symmetry, as well as the determination and characterization of the equilibrium points. We define the parameter ranges related to different types of oscillations in the coupled system in order to have an overall idea of the nature of the attractors (hidden or self-excited) that may exist. We apply numerical analysis techniques (2-parameter diagrams, bifurcation analysis, phase portraits, basins of attractions, etc) in accordance with the previous operating range in order to shed light on the plethora of competing dynamics of the model and possible forms of strange attractors as well. Another salient point of this work is the coexistence between five self-excited attractors (limit cycle and chaos) with a hidden attractor (limit cycle). We also examine the impact of symmetry breaking on the system response. An appropriate analog simulator of the coupled system is designed and simulated in PSpice in order to check the results reported during the theoretical analyses. We believe that the results of the present work complement and enrich previously published ones concerning the dynamics of a system composed of a van der pol oscillator coupled to a (non-oscillating) double-well oscillator.

Reduction of Vision-Based Models for Fall Detection

Due to the limitations that falls have on humans, early detection of these becomes essential to avoid further damage. In many applications, various technologies are used to acquire accurate information from individuals such as wearable sensors, environmental sensors or cameras, but all of these require high computational resources in many cases, delaying the response of the entire system. The complexity of the models used to process the input data and detect these activities makes them almost impossible to complete on devices with limited resources, which are the ones that could offer an immediate response avoiding unnecessary communications between sensors and centralized computing centers. In this work, we chose to reduce the models to detect falls using images as input data. We proceeded to use image sequences as video frames, using data from two open source datasets, and we applied the Sparse Low Rank Method to reduce certain layers of the Convolutional Neural Networks that were the backbone of the models. Additionally, we chose to replace a convolutional block with Long Short Term Memory to consider the latest updates of these data sequences. The results showed that performance was maintained decently while significantly reducing the parameter size of the resulting models.

Explainable Machine Learning Models for Real-Time Threat Detection in Cybersecurity

In the rapidly evolving landscape of cybersecurity, traditional machine learning models often operate as "black boxes," providing high accuracy but lacking transparency in decision-making. This lack of explainability poses challenges for trust and accountability, especially in critical areas like threat detection and incident response. Explainable machine learning models aim to address this by making the model's predictions more understandable and interpretable to users. This research integrates explainable machine learning models for real-time threat detection in cybersecurity. Data from multiple sources, including network traffic, system logs, and user behavior, undergo preprocessing such as cleaning, feature extraction, and normalization. The processed data is passed through various machine learning models, including traditional approaches like SVM and decision trees, as well as deep learning models like CNN and RNN. Explainability techniques such as LIME, SHAP, and attention mechanisms provide transparency, ensuring interpretable predictions. The explanations are delivered through a user interface that generates alerts, visualizations, and reports, facilitating effective threat assessment and incident response in decision support systems. This framework enhances model performance, trust, and reliability in complex cybersecurity scenarios.

Implications of glioblastoma-derived exosomes in modifying the immune system: state-of-the-art and challenges.

Glioblastoma is a brain cancer with a poor prognosis. Failure of classical chemotherapy and surgical treatments indicates that new therapeutic approaches are needed. Among cell-free options, exosomes are versatile extracellular vesicles (EVs) that carry important cargo across barriers suchas the blood-brain barrier (BBB) to their target cells. Thismakes exosomes an interesting option for the treatment ofglioblastoma. Moreover, exosomes can comprise many therapeutic cargos, including lipids, proteins, and nucleic acids,sampled from special intercellular compartments of their origin cell. Cells exposed to various immunomodulatory stimulican generate exosomes enriched in specific therapeutic molecules. Notably, the secretion of exosomes could modify theimmune response in innate and adaptive immune systems. For instance, glioblastoma-associated exosomes (GBex) uptake bymacrophages could influence macrophage dynamics (e.g., shifting CD markers expression). Expression of critical immunoregulatory proteins such as cytotoxic T-lymphocyte antigen-1 (CTLA1) and programmed death-1 (PD-1) on GBex indicates the direct crosstalk of these nano-size vesicles with the immune system. The present study reviews the role of exosomes in immune system cells, including Bcells, Tcells, natural killer (NK) cells, and dendritic cells (DCs), as well as novel technologies in the field.

Dynamic plastic damage analysis of bending-torsion coupling in cross stiffener systems under mass impact

ABSTRACT This study proposes a simpler theoretical model to predict the bending-torsion coupling dynamic plastic response of cross stiffener systems under mass impact. Traditional methods often rely on torque balance and momentum conservation equations, which involve complex and difficult calculations. To simplify this process, the study uses the law of energy conservation and applies the variational method to solve the dynamic plastic damage of the cross stiffener system. The plastic response of a single stiffener is first analyzed and compared with existing theories, showing consistent results for maximum displacement. The study then extends the model to more complex conditions, performing comparative analyses on stiffeners of different sizes through numerical simulation. The findings show that the maximum displacement at the load and node remains within a reasonable range, with a displacement difference of only 0.9 mm and an error margin of 4.79% in one of the test conditions.

Host Innate and Adaptive Immunity Against African Swine Fever Virus Infection

Africa swine fever virus (ASFV) is the causative agent of African swine fever (ASF), a highly contagious hemorrhagic disease that can result in up to 100% lethality in both wild and domestic swine, regardless of breed or age. The ongoing ASF pandemic poses significant threats to the pork industry and food security, with serious implications for the sanitary and socioeconomic system. Due to the limited understanding of ASFV pathogenesis and immune protection mechanisms, there are currently no safe and effective vaccines or specific treatments available, complicating efforts for prevention and control. This review summarizes the current understanding of the intricate interplay between ASFV and the host immune system, encompassing both innate and adaptive immune responses to ASFV infection, as well as insights into ASFV pathogenesis and immunosuppression. We aim to provide comprehensive information to support fundamental research on ASFV, highlighting existing gaps and suggesting future research directions. This work may serve as a theoretical foundation for the rational design of protective vaccines against this devastating viral disease.

Association of Stress Defense System With Fine Particulate Matter Exposure: Mechanism Analysis and Application Prospects.

The association between the stress defense system and exposure to fine particulate matter (PM2.5) is a hot topic in the field of environmental health. PM2.5 pollution is an increasingly serious issue, and its impact on health cannot be ignored. The stress defense system is an important biological mechanism for maintaining cell and internal environment homeostasis, playing a crucial role in PM2.5-induced damage and diseases. The association between PM2.5 exposure and activation of the stress defense system has been reported. Moderate PM2.5 exposure rapidly mobilizes the stress defense system, while excessive PM2.5 exposure may exceed its compensatory and coping abilities, resulting in system imbalance and dysfunction that triggers pathological changes in cells and tissues, thereby increasing the risk of chronic diseases, such as respiratory diseases, cardiovascular diseases, and cancer. This detailed review focuses on the composition, function, and regulatory mechanisms of the antioxidant defense system, autophagy system, ubiquitin-proteasome system, and inflammatory response system, which are all components of the stress defiance system. In particular, the influence of PM2.5 exposure on each of these defense systems and their roles in responding to PM2.5-induced damage was investigated to provide an in-depth understanding of the pathogenesis of PM2.5 exposure, accurately assess potential hazards, and formulate prevention and intervention strategies for health damage caused by PM2.5 exposure.

Hydrogen peroxide mediates melatonin-induced chilling tolerance in cucumber seedlings.

MT mitigates chilling damage by enhancing antioxidant system and photosystem activities, and cold-responsive genes expression in cucumbers. H2O2 may act as a downstream signaling molecule in the MT-induced chilling tolerance. Melatonin (MT) and hydrogen peroxide (H2O2) are important endogenous signaling molecules that play multifaceted roles in plant responses to abiotic stress. However, the interactive mechanism by which MT and H2O2 regulate chilling tolerance remains unclear. Here we found that MT exhibited a positive regulatory effect on the chilling tolerance of cucumbers, with an optimum concentration of 100µM. MT markedly enhanced RBOH1 mRNA expression, activity and endogenous H2O2 accumulation in cucumber seedlings. However, 1.0mM H2O2 had no significant effect on mRNA levels of TDC and ASMT, the key genes for MT synthesis, and endogenous MT content. Both MT and H2O2 significantly decreased malondialdehyde (MDA), electrolyte leakage (EL) and chilling injury index (CI) by activating the antioxidant system, thereby alleviating chilling damage in cucumber seedlings. MT and H2O2 improved photosynthetic carbon assimilation, which was primarily attributed to an increase in activity, mRNA expression, and protein levels of RuBPCase and RCA. Meanwhile, MT and H2O2 induced the photoprotection for both PSII and PSI by enhancing the QA's electron transport capacity and elevating protein levels of the photosystems. Moreover, MT and H2O2 significantly upregulated the expression of cold response genes. MT-induced chilling tolerance was attenuated by N', N'-dimethylthiourea (DMTU), a H2O2 specific scavenger. Whereas, the MT synthesis inhibitor (p-chlorophenylalanine, p-CPA) did not influence H2O2-induced chilling tolerance. The positive regulation of MT on the antioxidant system, photosynthesis and cold response gene levels were significantly attenuated in RBOH1-RNAi plants compared with WT plants. These findings suggest that H2O2 may functions as a downstream signaling molecule in MT-induced chilling tolerance in cucumber plants.

MIS Solutions During Natural Disaster Management: A Review On Responsiveness, Coordination, And Resource Allocation

This systematic review explores the impact of Management Information Systems (MIS) on enhancing disaster management by optimizing decision-making, resource allocation, and inter-agency communication. As the frequency and severity of natural disasters increase globally, there is a pressing need for more efficient disaster response mechanisms. This study systematically reviewed a total of 160 peer-reviewed articles published between 2010 and 2024, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to ensure a comprehensive and transparent review process. The findings reveal that MIS technologies, such as decision support systems (DSS), geographic information systems (GIS), and predictive analytics, play a crucial role in improving the speed and accuracy of emergency responses. Specifically, DSS and predictive models were found to enhance situational awareness and optimize resource deployment, reducing response times by up to 30%. Additionally, GIS tools significantly improved spatial data analysis, enabling better-targeted relief efforts. However, challenges related to data interoperability, cybersecurity, and the integration of advanced technologies remain significant barriers to fully leveraging MIS in disaster management. Addressing these challenges through investments in infrastructure, standardized protocols, and specialized training will be essential for maximizing the potential of MIS in future disaster response efforts. The review concludes that the strategic use of MIS is vital for building more resilient and responsive disaster management systems, ultimately reducing the socio-economic impacts of emergencies.

Incentive Determination for Demand Response Considering Internal Rate of Return

The rapid expansion of renewable energy sources has led to increased instability in the power grid of Jeju Island, leading to the implementation of the plus demand response (DR) system, which aims to boost electricity consumption during curtailment periods. However, the frequency of curtailment owing to the increased utilization of renewable energy is outpacing the implementation of plus DR, highlighting the need for additional resources, such as energy storage systems (ESS). High initial investment costs have been the primary hindrance to the adoption of ESS by DR-participating companies but have not been fully considered in earlier studies on DR incentive determination. Therefore, this study proposes an algorithm for calculating appropriate incentives for plus DR participation considering the investment costs required for ESS. Based on actual load data, incentives are determined using an iterative mixed-integer programming (MIP) optimization method that progressively adjusts the incentive level to address the overall nonlinearity arising from both the multiplication of variables and the nonlinear characteristics of the internal rate of return (IRR), ensuring that the target IRR is achieved. A case study on the impact of factors such as IRR, ESS costs, and fluctuations in electricity rates on incentive calculations demonstrated that plus DR incentives required to achieve IRR targets of 5%, 10%, and 15% have increased linearly from 142.2 KRW/kWh to 363.0 KRW/kWh, confirming that the appropriate incentive level can be effectively determined based on ESS investment costs and target IRR. This result could help promote ESS adoption among DR companies and plus DR participation, thereby enhancing power grid stability.

Normalized acceleration based online tuning of variable-order fractional derivatives: a case study on quadcopter position control

In recent years, the use of Variable-Order (VO) fractional operators in control system design has been gaining popularity due to their adaptive nature, enabled by their dynamically adjustable fractional derivative and integral orders. This paper presents an online tuning method for adjusting the VO fractional derivatives in fractional controllers. The method is formulated to strategically accelerate or decelerate the system response's rate of change to enhance reference tracking and disturbance rejection performance while preserving closed-loop stability. It uses the normalised acceleration of the system response, a metric that provides insights into the ‘fastness’ or ‘slowness’ of the system response. The effectiveness of the proposed online tuning method is validated through a case study on quadcopter position control. Our research includes both simulation and real-time testing of Variable-Order Fractional PD (VOFPD) controllers, which utilise our online tuning method to adjust their fractional derivatives in real-time. Stability analysis via the D-decomposition method confirms that the quadcopter's closed-loop stability is preserved. Comparative results show significant improvements in reference tracking and disturbance rejection in terms of time-domain criteria.

Industrial Organizations Adapting to the Novel EU Taxonomy While Developing Socio-Technical Systems: A Literature Review

The EU taxonomy defines criteria for economic activities committed to a net zero emission by 2050, and other environmental goals. Its overall goal is to direct investments to economic activities aligned with the European Green Deal and, thereby, classified as sustainable. For industrial organizations, there is an urgent need to develop adaptive capabilities to meet the requirements set by the new taxonomy. The present scoping review contributes by analyzing academic publications on this topic through the lens of a complex science and systems approach. It analyzes academic publications on the EU taxonomy, related to industrial organizations and their development of socio-technical systems. At the initial stage, 526 scientific publications were retrieved from three web repositories (Scopus, World of Science, and Scholar). Only eight publications matched the selection criteria and constitute the data of this study. Results indicate that there is a lack of holistic perspectives and an unbalanced system response to the EU taxonomy. Adopting a systems approach can help industrial organizations navigate the intricate dynamics of a sustainable transition, striking a balance between adhering to the EU taxonomy and maintaining market competitiveness. The findings emphasize the importance of trans-disciplinary approaches and the need for agile and adaptive ways of learning inside industrial organizations.

Knowledge, Attitude, and Practice of the Lebanese University Medical Students and Junior Doctors on Basic Life Support Practices

Background: Basic life support (BLS) is the recognition of sudden cardiac arrest and activation of emergency response system, followed by cardiopulmonary resuscitation (CPR), and rapid defibrillation. Aim: Our study aimed to determine the level of awareness of the Lebanese University medical students and trainees on BLS, by assessing the association between knowledge, attitude, and practice on BLS, and between the demographic variables and KAP scores. Methods: This was a cross-sectional study including 330 medical students enrolled at Lebanese University, from year four of general medicine till year five of residency. An online survey was used to collect data about demographic characteristics, knowledge (K), attitudes (A), and practice (P) about BLS. Data was analyzed using SPSS version 25. Results: Participants were 52.7% females, 47.3% males, and their mean age was 24 ± 2 years. Of the 330 participants, 38.8% received formal training regarding BLS. Medical students had low knowledge (90%), moderate to good attitudes (71.5%), and low practice (93%) regarding BLS. Multiple linear regression showed that knowledge was positively associated with age (p = 0.001), knowledge and information regarding BLS (p = 0.016), and any formal training/workshop regarding BLS (p = 0.021). Attitude was positively associated with academic year (p = 0.002) and knowledge (p = 0.003). Practice was positively associated with age (p < 0.001) and knowledge (p < 0.001). Conclusion: Most Lebanese University medical students showed low knowledge, moderate to good attitudes, and low practice regarding BLS. We recommend that CPR/BLS should be a core competency across all health care professional programs.

Fourier-optics imaging analysis with ABCD matrices: tutorial

The use of ABCD (ray-transfer) matrices to analyze wave propagation through paraxial optical systems, with emphasis on imaging systems, is described. It is shown how to find the image, Fourier transform, and exit pupil planes. Different forms of the propagation integrals are given. The propagation integral for an imaging system, which includes an aperture stop, is derived. The relationships between the aperture stop and the exit pupil and the impulse response of a paraxial imaging system are derived.

Skin Sensitization Potential of Sensitizers in the Presence of Metal Oxide Nanoparticles In Vitro

Silica (SiO2), titanium dioxide (TiO2), and zinc oxide (ZnO) nanoparticles (NPs) are widely used in dermal products. Their skin sensitization potential, especially their effects in combination with known sensitizers, is poorly studied in vitro and their sensitization inconsistently reported in animal studies. In this study, cellular assays were used to identify different steps of sensitization, the activation of keratinocytes and dendritic cells, when cells were exposed to these NPs in the absence and presence of sensitizers. Cellular systems included HaCaT keratinocytes and U937 (U-SENS™) alone, as well as different co-culture systems of THP-1 cells with HaCaT cells (COCAT) and with primary keratinocytes. The effect of NPs differed between co-cultures and U-SENS™, whereas co-cultures with either primary keratinocytes or HaCaT cells responded similarly. Pre-exposure to ZnO NPs increased the U-SENS™ assay response to 2,4-dinitrochlorobenzene six-fold. The COCAT increase was maximally four-fold for the combination of SiO2 and trans cinnamaldehyde. When the THP-1 cells were separated from the keratinocytes by a membrane, the response of the co-culture system was more similar to U-SENS™. The direct contact with keratinocytes decreased the modulating effect of TiO2 and ZnO NPs but suggested an increase in response to sensitizers following dermal contact with SiO2 NPs.

The Therapeutic Potential of Agarwood as an Antimicrobial and Anti-Inflammatory Agent: A Scoping Review

Background/Objectives: Microorganisms such as bacteria, viruses, and fungi are frequently the cause of infections. Antimicrobial agents, such as antibiotics, antivirals, and antifungals, are used to target and eliminate these infectious agents. On the other hand, inflammation is a natural response of the immune system to injury, infection, or irritation. Although herbal remedies have been used to treat these conditions for centuries and can be effective in certain situations, it is crucial to use them with caution. Not all herbal remedies are supported by scientific evidence, and their safety and efficacy can vary. Thus, we conducted this review to determine the potential health benefits of agarwood as an antimicrobial and anti-inflammatory agent. Methods: Three databases (PubMed, Scopus, and Google Scholar) were used to search for original papers submitted between 2013 and 2023, using the Medical Subject Heading (MeSH) terms “agar-wood” crossed with the terms “antimicrobial” and/or “anti-inflammatory”. Synonyms and relevant search terms were also searched. Results: The most-studied agarwood for antimicrobial and anti-inflammatory agents is Aquilaria sinensis. Some studies have shown its potential application as a potent inhibitor of fungi, including Lasiodiplodia theobromae, Fusarium oxysporum, and Candida albicans. Moreover, it is capable of inhibiting Bacillus subtilis and Staphylococcus aureus activities. Several chromones detected in agarwood have been shown to inhibit NF-κB activation, LPS-induced NO production, and superoxide anion generation. In conclusion, more research is needed, particularly regarding future intervention studies, to enhance our knowledge and understanding of agarwood and its isolates. Conclusions: This review reveals that despite the absence of clinical trials, agarwood exhibits antimicrobial and anti-inflammatory properties.

Dual-Redox Responsive Interfaces Based on Donor-Acceptor Interactions.

Nanoparticle surfactant (NPS) is a highly competitive means for stabilizing liquid-liquid interfaces, endowing interfacial assemblies with functionalities, and enabling the construction of all-liquid devices. Integrating different types of supramolecular interactions into NPSs would open possibilities to generate interfaces that are responsive to multiple stimuli. Here, by using donor-acceptor interactions between polydopamine nanoparticles (PDA NPs) and methyl viologen (MV2+) terminated polystyrene, the formation, assembly, and jamming of a supramolecular NPS at the water-toluene interface is demonstrated. Harnessing the redox properties of both catechol and MV2+, the dual-redox responsiveness can be achieved, allowing the reconfiguration of NPS-based structured liquids. Using NPS as an emulsifier, oil-in-water (O/W), water-in-oil (W/O), and oil-in-water-in-oil (O/W/O) Pickering emulsions can be obtained in one step, which exhibit smart responsiveness to redox reagents. Taking advantage of the adsorption capacity of PDA NPs, the purification of dye-polluted water can be achieved through O/W Pickering emulsions. We envision that this unique dual-redox responsive biphasic system would hold great potential for developing sophisticated controlled-release systems as well as other intelligent, functional materials.

Comprehensive Analysis of Cloud Computing Performance Factors: Investigating the Impact of Response Time, Load Balancing and Service Broker Policies on Cloud Service Efficiency Using CloudSim Simulation

Cloud performance refers to the efficiency and effectiveness with which a cloud system operates delivering hosted services over the internet. As cloud computing continues to offer flexibility, scalability and computational power monitoring and improving cloud performance is essential. Performance optimization is influenced by factors such as load balancing and service broker policies which impact system response times and overall user experience. This paper provides an in-depth review of key publications and real-time cloud performance tools identifying critical performance factors that affect cloud efficiency. Notably, response time emerged as a fundamental metric for cloud service quality. Using CloudSim simulation we examine cloud performance evaluation criteria and experimentally assess the impact of response time dependencies on broker policies, load balancing techniques and data center distribution. This study offers a framework for understanding cloud performance evaluation and highlights strategies to enhance user experience in diverse cloud environments.