Search Results (269,206)

Background/Objectives: Surgical pneumoperitoneum (PP) significantly impacts volume-controlled ventilation, characterized by reduced respiratory compliance, elevated peak inspiratory pressure, and an accelerated expiratory phase due to an earlier onset of the airway pressure gradient. We hypothesized that this would shorten expiratory time, potentially increasing expiratory flow rate compared to pneumoperitoneum conditions. Calculations were performed to establish correlations between respiratory parameters and the mean increase in expiratory flow rate relative to baseline. Methods: Mechanical ventilation parameters were recorded for 67 patients both pre- and post-PP. Ventilator settings were standardized with a tidal volume of 6 mL/kg, a respiratory rate of 12 breaths per minute, a PEEP of 3 cmH₂O, an inspiratory time of 2 s, and an inspiratory-to-expiratory ratio of 1:1.5 (I:E). Results: The application of PP increased both peak inspiratory pressure and mean expiratory flow rate by 28% compared to baseline levels. The elevated intra-abdominal pressure of 20 cmH₂O resulted in a 34% reduction in dynamic chest compliance, a 50% increase in elastance, and a 20% increase in airway resistance. The mean expiratory flow rate increments relative to baseline showed a significant negative correlation with elastance (p = 0.0119) and a positive correlation with dynamic compliance (p = 0.0028) and resistance (p = 0.0240). Conclusions: A PP of 20 cmH₂O resulted in an increase in the mean expiratory flow rate in the conventional I:E ratio in the volume-ventilated mode. PP reduces lung and chest wall compliance by elevating the diaphragm, compressing the thoracic cavity, and increasing airway pressures. Consequently, the lungs and chest wall stiffen, requiring greater ventilatory effort and accelerating expiratory flow due to increased airway resistance and altered pulmonary mechanics. Prolonging the inspiratory phase through I:E ratio adjustment helps maintain peak inspiratory pressures closer to baseline levels, and this method enhances the safety and efficacy of mechanical ventilation in maintaining optimal respiratory function during laparoscopic surgery. Full article

In today’s global context, challenges persist in preventing agri-food waste due to factors like limited consumer awareness and improper food-handling practices throughout the entire farm-to-fork continuum. Introducing a forward-thinking solution, the upcycling of renewable feedstock materials (i.e., agri-food waste and by-products) into value-added ingredients presents an opportunity for a more sustainable and circular food value chain. While multi-product cascade biorefining schemes show promise due to their greater techno-economic viability, several biotechnological hurdles remain to be overcome at many levels. This mini-review provides a succinct overview of the biotechnological and societal challenges requiring attention while highlighting valuable food-grade compounds derived from biotransformation processes. These bio-based ingredients include organic acids, phenolic compounds, bioactive peptides, and sugars and offer diverse applications as antioxidants, preservatives, flavorings, sweeteners, or prebiotics in foodstuffs and other consumer goods. Therefore, these upcycled products emerge as a sustainable alternative to certain potentially harmful artificial food additives that are still in use or have already been banned from the industry. Full article

In this article, we investigate a couple of nonlinear time-fractional evolution equations, namely the cubic-quintic-septic-nonic equation and the Davey–Stewartson (DS) equation, both of which have significant applications in complex physical phenomena such as fiber optical communication, optical signal processing, and nonlinear optics. Using a powerful technique named the extended generalized Kudryashov approach, we extract different rich structured soliton solutions to these models, including bell-shaped, cuspon, parabolic soliton, singular soliton, and squeezed bell-shaped soliton. We also study the impact of fractional-order derivatives on these solutions, providing new insights into the dynamics of nonlinear models. The results are compared with the existing literature, revealing novel and distinct solutions that offer a deeper understanding of these fractional models. The results show that the implemented approach is useful, reliable, and compatible for examining fractional nonlinear evolution equations in applied science and engineering. Full article

The book Quantum Machine Learning: What Quantum Computing Means to Data Mining, by Peter Wittek, made quantum machine learning popular to a wider audience. The promise of quantum machine learning for big data is that it will lead to new applications due to the exponential speed-up and the possibility of compressed data representation. However, can we really apply quantum machine learning for real-world applications? What are the advantages of quantum machine learning algorithms in addition to some proposed artificial problems? Is the promised exponential or quadratic speed-up realistic, assuming that real quantum computers exist? Quantum machine learning is based on statistical machine learning. We cannot port the classical algorithms directly into quantum algorithms due to quantum physical constraints, like the input–output problem or the normalized representation of vectors. Theoretical speed-ups of quantum machine learning are usually analyzed in the literature by ignoring the input destruction problem, which is the main bottleneck for data encoding. The dilemma results from the following question: should we ignore or marginalize those constraints or not? Full article

This paper introduces a new methodology for a routine metal analysis of plastic waste (PW) and PW blended with petroleum feedstock such as vacuum gas oil and VGO (PW/VGO). For such purposes, recycled polyethylene and polypropylene plastic were selected to mimic the potential feeds to be integrated at the Fluid Catalytic Cracking unit (FCC) to produce valuable products. Elements such as P, Ca, Al, Mg, Na, Zn, B, Fe, Ti, and Si were included in the method development. Different sample preparation methods were evaluated, such as microwave-assisted acid digestion (MWAD) and dry/wet ashing, followed by a fusion of the ash with lithium borate flux. Some PW homogenization pretreatments, such as cryogenic grinding and hot press molding, were also covered. The finding of this work suggests that MWAD with HNO₃ and H₂O₂ is adequate for both types of samples and is the quickest sample preparation; however, the sample needed to be homogenized, and recoveries for Si and Ti may be biased for PW due to the limited solubilities of these elements in the nitric acid media. Carbon removal is required before fusion sample preparation and analysis due to the amount of carbon in PW samples. The sample needed to be homogenized for wet ash fusion but not for the pre-ash (dry) method. A benefit to the damp ash pretreatment is that the ash for the sample was created in the same crucible used for fusion digestion, avoiding material loss during sample management. Fusion from wet ash or carbon removal allowed for better acid solubility for Si and Ti in PW. The results of the PW samples evaluated matched well with those of both sample preparation methodologies. For most elements, precision was <10% regardless of the sample preparation; however, Fe and P had some variation using wet ash fusion, possibly due to contamination in an open digestion system or variation due to being close to the method limit of quantification (LOQ). The methodology reported here is robust enough to be implemented as routine analysis in any laboratory facility. Full article

In the field of rigid parallel manipulators, the Delta parallel robot is one of the most popular choices in the industry due to its ability to adapt to a wide range of applications, particularly pick-and-place tasks. In this paper, the authors present novel designs of Delta-type continuum parallel manipulators with flexible bars, solving both their direct and inverse kinematics, as well as obtaining the associated workspace. The continuum parallel manipulators, unlike conventional robots, incorporate certain flexible elements, such as slender rods that make up the kinematic chains of the Delta manipulators proposed in this work. As a consequence of the flexibility of these rods, a purely translational movement will not be generated, since it is necessary to analyze the zones of the workspace where a parasitic motion related to the inclination of the moving platform compromises the task devised. In addition, an experimental prototype of the Keops-Delta continuum manipulator has been built, and several experimental tests have been carried out to validate the proposed theoretical model. Full article

In response to the escalating threats of cybersecurity attacks and breaches, ensuring the development and deployment of secure IT products has become paramount for organizations in their cybersecurity transformation. This work emphasizes the critical need for a comprehensive and secure IT project management life cycle that safeguards products from their initial development stages through decommissioning. The primary objective is to seamlessly integrate security considerations into every facet of IT project management life cycles. This work embraces a cyber-resilient IT project management framework and advocates the inclusion of cybersecurity measures in IT projects and their strategic, organized, continuous, and systematic integration throughout the entire product life cycle. It introduces a pioneering framework that harmonizes the cybersecurity risk management process with the IT project management life cycle. This framework delineates a methodical sequence of steps, each encompassing a distinct set of activities. The effectiveness and practical applicability of the proposed framework were validated through a comprehensive case study focused on the Personal Health Record (PHR) system. The PHR case study served as a real-world scenario to assess the framework’s ability to address cybersecurity challenges in a specific domain. The results of the experiment demonstrated the framework’s efficacy in enhancing the security posture of IT projects, showcasing its adaptability and scalability across diverse applications. Full article

This study investigates the neurophysiological effects of transcutaneous electroacupuncture stimulation (TEAS) on brain activity, using advanced machine learning techniques. This work analyzed the electroencephalograms (EEG) of 48 study participants, in order to analyze the brain’s response to different TEAS frequencies (2.5, 10, 80, and sham at 160 pulses per second (pps)) across 48 participants through pre-stimulation, during-stimulation, and post-stimulation phases. Our approach introduced several novel aspects. EEGNet, a convolutional neural network specifically designed for EEG signal processing, was utilized in this work, achieving over 95% classification accuracy in detecting brain responses to various TEAS frequencies. Additionally, the classification accuracies across the pre-stimulation, during-stimulation, and post-stimulation phases remained consistently high (above 92%), indicating that EEGNet effectively captured the different time-based brain responses across different stimulation phases. Saliency maps were applied to identify the most critical EEG electrodes, potentially reducing the number needed without sacrificing accuracy. A phase-based analysis was conducted to capture time-based brain responses throughout different stimulation phases. The robustness of EEGNet was assessed across demographic and clinical factors, including sex, age, and psychological states. Additionally, the responsiveness of different EEG frequency bands to TEAS was investigated. The results demonstrated that EEGNet excels in classifying EEG signals with high accuracy, underscoring its effectiveness in reliably classifying EEG responses to TEAS and enhancing its applicability in clinical and therapeutic settings. Notably, gamma band activity showed the highest sensitivity to TEAS, suggesting significant effects on higher cognitive functions. Saliency mapping revealed that a subset of electrodes (Fp1, Fp2, Fz, F7, F8, T3, T4) could achieve accurate classification, indicating potential for more efficient EEG setups. Full article

This article introduces a novel two-step fifth-order Jacobian-free iterative method aimed at efficiently solving systems of nonlinear equations. The method leverages the benefits of Jacobian-free approaches, utilizing divided differences to circumvent the computationally intensive calculation of Jacobian matrices. This adaptation significantly reduces computational overhead and simplifies the implementation process while maintaining high convergence rates. We demonstrate that this method achieves fifth-order convergence under specific parameter settings, with broad applicability across various types of nonlinear systems. The effectiveness of the proposed method is validated through a series of numerical experiments that confirm its superior performance in terms of accuracy and computational efficiency compared to existing methods. Full article

The aim of this paper is to present examples and original solutions related to the application of the digital twin concept in designing safety systems for robotic stations. This paper includes a review of publications on robot safety systems and digital twins. Based on this review, it was concluded that further work in this area is justified. This paper demonstrates the use of a digital model of a robotic casting mold preparation station to design safety components for an industrial cell. A key element of this paper is the presentation of developed algorithms and their applications in building digital twins of existing robotic stations. By characterizing advanced safety systems used in robotic stations, an example of using a digital twin of a robotic station to create safety zones and so-called restricted zones for the robot was developed. As part of the research conducted, a real, comprehensive example of creating safety zones based on the robot’s TCP paths was carried out. Full article

This study evaluates the vertical stress transmission through a sand–tire mixture layer under impact, focusing on this innovative blended material that can impact underground structures such as tunnels or pipelines. By conducting consolidated undrained triaxial tests, the friction angle (φ) of the sand–tire mixture was determined, ranging from 29° for pure tire to 41° for pure sand. The vertical stress factor (α), representing the ratio of response load to applied load, was found to decrease significantly with increased tire content, with a reduction of up to 50% for mixtures containing 20% tire. Additionally, the vertical stress response decreased from 35 kPa for pure sand to as low as 15 kPa for mixtures with a high tire content under a consistent applied load of 65 kPa. This study not only presents a methodological advancement in analyzing sand–tire mixtures under dynamic loads but also suggests a sustainable approach to utilizing waste tire material in civil engineering projects, thereby contributing to environmental conservation and improved material performance in geotechnical applications. Full article

The burning rate of pure deuterium (D-D) fuel in Z-pinch devices with magneto-inertial confinement was studied in this paper. The system of particle and energy balance equations for D-D fuel burning with a mixed D-T-³He fusion cycle (D-D, D-T, and D-³He reactions) was solved numerically, taking into account the densities of all reacted and produced ions (protons, deuterium, tritium, helium-3, and alpha-particles). The obtained results indicate that effective D-D fusion in Z-pinch devices can be successfully achieved under conditions of a hot, dense plasma with an initial temperature of 31 keV or higher. The initial ion density of deuterium and electron density were equal due to quasi-neutrality condition of the plasma, with both reaching m⁻³. Although the obtained results show that the burning rate of D-D fuel is approximately 2.3 times slower and its power density notably lower than that of D-T fuel, pure deuterium plasma can be considered as a promising alternative to well-studied deuterium–tritium plasma, with potential future applications in magneto-inertial fusion (MIF) facilities. Full article

Hyperbolic discounting is a psychological phenomenon in which individuals prioritize smaller immediate rewards over larger future rewards. Time-inconsistent behavior is deemed irrational as it negatively impacts savings and investment, investment in financial knowledge, and long-term financial and personal well-being. This study hypothesizes that improving financial knowledge, promoting positive financial behavior, and fostering a future-oriented financial attitude can mitigate hyperbolic discounting bias and that these three components of financial literacy enable investors to make long-term economic decisions maximizing utility. We analyzed the responses of 114,170 active investors in Japan to examine the interactions between financial knowledge, behavior, and attitude. Our findings reveal a strong negative relationship between these dimensions and hyperbolic discounting, underscoring their crucial role in shaping individuals’ intertemporal preferences. For researchers, our results highlight the need to integrate multidimensional aspects of financial literacy into investigations of intertemporal discounting behaviors. Policymakers should implement holistic financial education programs that improve knowledge, transform behavior, and shape attitudes. Financial institutions and advisors should prioritize programs that mitigate hyperbolic discounting tendencies among clients. This study represents a significant advancement in the research on financial literacy, offering a comprehensive framework for future studies and practical applications aimed at improving financial decision-making outcomes. Full article

A new technology to write and read covert information in authentication labels is described. This technology uses the phenomenon of photo-induced chirality in Ge₂Sb₂Te₅ thin films to encode the left- or right-circular or linear polarization of the laser beam used to write the label. The written polarization can be revealed by a simple reading device, which is demonstrated to provide the same qualitative information as reading based on cyclotron circular dichroism spectroscopy and imaging. The suggested method, while based on existing manufacturing approaches, offers a balance between technological complexity for writing and simplicity for reading, and may be advantageous as a new authentication technology. Full article

The cladding process reduces manufacturing costs by depositing super austenitic stainless steel onto low-carbon steel. Arc welding techniques, especially gas tungsten arc welding (GTAW), are commonly used for this purpose. This study evaluates the influence of heat input on cladding performance. Macroscopic analysis showed good fusion of the weld beads to the base metal with no defects. Higher heat input resulted in a lower dilution rate due to increased reinforcement. A microstructural analysis of the heat-affected zones revealed similar characteristics, with martensite formation attributed to cooling conditions. Increased microhardness was observed at the interface between the cladding and base metal, corroborating the microstructural findings. Additionally, a significant enhancement in corrosion resistance was noted in the deposited layers. This research contributes to optimizing cladding processes, ensuring better material performance in industrial applications. Full article