Changes In State Research Articles

Dynamic stress analysis of rock joints under railway loading

The proper estimation of stresses generated by the passage of a train is fundamentally important to the serviceability and longevity of railways, and yet very limited knowledge is available where the track substructure is built on a jointed rock mass. The present study introduces an analytical solution for estimating the ground stresses arising from moving wheel loads, causing a change in the three-dimensional stress state in the track formation, in relation to the stress variation with depth and along the longitudinal track section – that is, the direction of train passage. Based on 21 case histories, an array of field measurements and numerical simulations covering a wide range of freight tonnage, train speeds and different formation conditions were considered to validate the proposed analytical solution. The proposed methodology (analytical solution) was then applied to a jointed rock subgrade to determine the normal and shear stresses acting along a specific discontinuity plane. The main analytical outcome demonstrates that the orthogonal vertical and shear stresses present different and phase-shifted history plots for homogeneous ground conditions with principal stresses rotation. However, conversely for a jointed subgrade, the normal and shear stresses along the discontinuity have the same history plot pattern and are in phase. As a practical guide, the results from this study would help to define which cyclic loads should be applied in laboratory tests to simulate realistic traffic patterns of trains travelling over a jointed rock subgrade.

Special theme: Sustainable development challenges in the Pacific small Island developing states: The role of regional cooperation: Urbanization, climate change and sustainable development in the Pacific small Island states: The role of regional cooperation and integration

Special theme: Sustainable development challenges in the Pacific small Island developing states: The role of regional cooperation: Urbanization, climate change and sustainable development in the Pacific small Island states: The role of regional cooperation and integration

Effect of nano-carbon black content and dispersibility on the properties of cement paste

In this study, we analyzed the microstructure, pore structure, and changes in electromagnetic parameters of cement paste with nano-carbon black (CB) added. The following conclusions were drawn: The addition of CB significantly influenced the pore structure of the cement paste, increasing the content of pores less than 100 nm and improving the overall pore structure. The use of the dispersant further enhanced the dispersion of CB and increased its filling effect. Additionally, adding CB had a significant impact on the compressive strength of the cement paste; the presence of certain CB aggregates reduced the compressive strength. However, when the CB content was 0.5wt%, the use of the dispersant decreased the size of CB aggregates and effectively increased the compressive strength. SEM images displayed the dispersion state of CB aggregates within the cement paste, demonstrating that the size and quantity of aggregates could be reduced through the use of the dispersant. The change in the CB dispersion state also slightly affected the electromagnetic parameters and wave absorption properties of the cement paste. The research results presented in this paper offer valuable insights for the design and application of CB cement paste.

Prediction of anticancer drug sensitivity using an interpretable model guided by deep learning

BackgroundThe prediction of drug sensitivity plays a crucial role in improving the therapeutic effect of drugs. However, testing the effectiveness of drugs is challenging due to the complex mechanism of drug reactions and the lack of interpretability in most machine learning and deep learning methods. Therefore, it is imperative to establish an interpretable model that receives various cell line and drug feature data to learn drug response mechanisms and achieve stable predictions between available datasets.ResultsThis study proposes a new and interpretable deep learning model, DrugGene, which integrates gene expression, gene mutation, gene copy number variation of cancer cells, and chemical characteristics of anticancer drugs to predict their sensitivity. This model comprises two different branches of neural networks, where the first involves a hierarchical structure of biological subsystems that uses the biological processes of human cells to form a visual neural network (VNN) and an interpretable deep neural network for human cancer cells. DrugGene receives genotype input from the cell line and detects changes in the subsystem states. We also employ a traditional artificial neural network (ANN) to capture the chemical structural features of drugs. DrugGene generates final drug response predictions by combining VNN and ANN and integrating their outputs into a fully connected layer. The experimental results using drug sensitivity data extracted from the Cancer Drug Sensitivity Genome Database and the Cancer Treatment Response Portal v2 reveal that the proposed model is better than existing prediction methods. Therefore, our model achieves higher accuracy, learns the reaction mechanisms between anticancer drugs and cell lines from various features, and interprets the model’s predicted results.ConclusionsOur method utilizes biological pathways to construct neural networks, which can use genotypes to monitor changes in the state of network subsystems, thereby interpreting the prediction results in the model and achieving satisfactory prediction accuracy. This will help explore new directions in cancer treatment. More available code resources can be downloaded for free from GitHub (https://github.com/pangweixiong/DrugGene).

Improvement of plastic deformation property and current carrying capacity of Bi2212 wires through low oxygen partial pressure post-annealing of precursor

The performance of superconducting magnets is greatly dependent on the size and uniformity of the superconducting filaments within the wire. However, in the fabrication of Bi2Sr2CaCu2Ox (Bi2212) wires using ceramic oxide as the superconducting filaments, we face multiple challenges including filament fragility, poor uniformity, and non-smooth Ag/superconductor interfaces. These challenges primarily stem from the significantly lower plastic deformation capability of ceramic oxide powder filaments compared to metal matrices. To address these challenges, this study focuses on the modification of ceramic oxide precursor powders. Through the utilization of low-temperature, low oxygen partial pressure (pO2) heat treatment, we have observed significant changes in the Cu chemical states and lattice parameters within the Bi2212 grains. These alterations have proven to be highly effective in reducing the energy required for grain sliding and, in turn, enhancing the plastic deformation properties of the Bi2212 oxide filament. Furthermore, post-annealing the oxide powder under low pO2 conditions narrows the gap in plastic deformability between the Ag sheath and the oxide filaments, resulting in improved filament uniformity and a smoother Ag/oxide interface in Bi2212 wires. Notably, the Bi2212 grains exhibit an orderly arrangement within the wires. As a result of these improvements, the critical current density (Jc) of the final wires increases by an impressive 70 %. The outcomes of this study are not only crucial for producing Bi2212 magnets with higher magnetic field strength, improved magnetic field uniformity, and enhanced operational stability, but also offer fresh insights and methodologies for advancing the field of superconducting materials.

Comparative analysis of geometric transformation-based sorting systems for fractional vector beams with polarization mutation angle indeterminacy

The Polarization Topological Charge (PTC) is a crucial parameter of a Cylindrical Vector Beam (CVB). Defined as the repetition number of polarization state changes along the azimuth axis, its sign indicates the polarization’s rotation direction. This paper delves into the effects of polarization mutation within Fractional Vector Beams (FVB) with angular uncertainty on PTC sorting systems. We compare three optical geometric coordinate transformation methods: Log-Polar (LP), Beam-Copying (BC), and Spiral Transformation (ST), focusing on their robustness and suitability. Our findings show that the azimuth angle of polarization mutation markedly influences the PTC sorting system’s output, leading to measurable uncertainties. Importantly, these uncertainties are not intrinsic to the FVB, but rather stem from the sorting system itself. Our study concludes that the BC method is optimal for PTC spectra analysis, whereas the ST method with carefully selected parameters is preferable for average PTC analysis.

ACUTE AND LONG-TERM EFFECTS OF APP-DELIVERED HEARTFULNESS MEDITATION ON PSYCHOLOGICAL OUTCOMES AND THE ENDOCANNABINOID SIGNALING SYSTEM IN CYCLIC VOMITING SYNDROME.

Cyclic vomiting syndrome (CVS) is a disorder of gut brain interaction (DGBI) often triggered by stress. Interventions like meditation may improve psychological outcomes and Health-Related Quality of Life (HRQoL), but their efficacy and the underlying mechanism are unknown. We conducted a 6-week single-arm pilot study to assess the effects of Heartfulness meditation (HFM) in CVS using a custom-designed meditation app. Primary outcomes included state and trait anxiety and mood state changes pre- vs. post-meditation, and secondary outcomes were psychological distress, coping, sleep quality and HRQoL at baseline and weeks 3 and 6. Serum concentrations of endocannabinoids N-arachidonylethanolamine (AEA) and 2-arachidonoylglycerol (2-AG) and related lipids were measured pre-and-post HFM at baseline and week 6. In 30 treatment completers, there was a significant improvement in state anxiety (p<0.001), total mood disturbance (p<0.001), and other mood states (all p values <0.05) across the three time points. Trait anxiety was also improved at week 6. There was a significant improvement in psychological distress (global severity index), sleep quality (daytime dysfunction), coping (using religion/spirituality) and HRQoL (mental and physical) across the three time points (all p <0.05). Significant increases in AEA and related lipids N-oleoylethanolamine and palmitoylethanolamide post-vs.-pre HFM were observed at week 6 (p<0.001, 0.002, 0.003, respectively). No adverse effects were noted. App-delivered HFM is feasible, safe and effective and improves psychological outcomes and augments endocannabinoids. This provides insight into the mechanism underlying HFM and has potential for widespread use as a digital therapeutic in CVS and other DGBI.Study Highlights.

Longitudinal molecular profiling elucidates immunometabolism dynamics in breast cancer

Although metabolic reprogramming within tumor cells and tumor microenvironment (TME) is well described in breast cancer, little is known about how the interplay of immune state and cancer metabolism evolves during treatment. Here, we characterize the immunometabolic profiles of tumor tissue samples longitudinally collected from individuals with breast cancer before, during and after neoadjuvant chemotherapy (NAC) using proteomics, genomics and histopathology. We show that the pre-, on-treatment and dynamic changes of the immune state, tumor metabolic proteins and tumor cell gene expression profiling-based metabolic phenotype are associated with treatment response. Single-cell/nucleus RNA sequencing revealed distinct tumor and immune cell states in metabolism between cold and hot tumors. Potential drivers of NAC based on above analyses were validated in vitro. In summary, the study shows that the interaction of tumor-intrinsic metabolic states and TME is associated with treatment outcome, supporting the concept of targeting tumor metabolism for immunoregulation.

Parasitic-Based Model for Characterizing False Turn-On and Switching-Based Voltage Oscillation in Hybrid T-Type Converter

High frequency and high voltage switching converters utilizing wide bandgap semiconductors are gaining popularity thanks to their compactness and improved efficiency. However, the faster switching requirements gives rise to new challenges. A key issue is the increased oscillation of the drain–source voltage caused by the switching action of the complementary switch in the same phase or change of state of the other phase switches. The voltage stress caused by these oscillations can damage the switch. Furthermore, the high dv/dt during turning-on of one switch might result in false turn-on of the complementary switch due to the miller effect. In this paper, these issues are investigated in a T-type converter through analytical and experimental analysis. Based on the proposed analytical approach, simple and cost-wise solutions utilizing an optimum design of gate driver circuits and circuit layout modifications can be developed to cope with the aforementioned issues. A comprehensive analytical model of the converter with consideration of parasitic capacitances and inductances is developed. By performing sensitivity analysis on the model, the effect of the parasitic parameters on the drain–source voltage oscillation and gate–source voltage amplitude in case of false turn-on is studied. The validity of the model is then assessed through numerical simulations and experimental results.

A novel temporal adaptive fuzzy neural network for facial feature based fatigue assessment

When engaging in activities such as using video display terminals, driving, or sports, effective fatigue monitoring is crucial. Nevertheless, obtaining biological information through contact devices may interfere with normal activities. Deterministic expressions in mainstream machine learning have limitations in reflecting the continuous, dynamic, and fuzzy process of fatigue status. Additionally, fatigue is a cumulative process where the previous state impacts the assessment of the current one. To address these needs and challenges, this paper proposes a novel model based on facial videos called the temporal adaptive fuzzy neural network (TAFNN) for fatigue assessment. TAFNN utilizes an adaptive fuzzy neural network as its foundation and employs causal and dilated convolutions for the time information processing method to achieve time series extraction and fatigue assessment. It leverages facial physiological and motion features to minimize interference during assessment. Furthermore, TAFNN introduces a new calculation method for rule antecedents to enhance stability. Experimental results demonstrate that TAFNN effectively captures the cumulation and fuzziness of state changes, outperforming other widely adopted methods in both assessment ability and runtime performance. The improved rule antecedent calculation method successfully mitigates the issue of multiple memberships rapidly approaching zero after combination. Through 1000 repeated experiments, the enhanced method reduces TAFNN’s instability by 81.58%.

Lunar regolith water ice simulation method and characterization

The exploration of lunar water resources has always been a cutting-edge topic in human space exploration. This paper presents a method for gas deposition and ice formation to simulate the mixture of ice and regolith in lunar polar shadowed regions. Following the principles of “physical structure equivalence and environmental parameter approximation,” based on the principle of water molecule deposition and adsorption in a cold trap environment, water ice is converted into water vapor by raising the temperature in a vacuum environment. Then, water molecules deposit and adsorb on the surface of dry, low-temperature mineral particles, forming an ice film under the action of the cold trap capture principle. The morphology and occurrence status of the particle surface ice film has been obtained through microscopic characterization of the samples in a cold environment. Vacuum pressure monitoring equipment is used to verify the pressure changes of water during the sublimation and deposition, and the phase diagram of water is analyzed to understand its state changes within the simulated setup. Samples are retrieved from a high-purity nitrogen glove box, and their water content is verified using thermogravimetric analysis (TGA). The effectiveness of the proposed lunar regolith simulation method is validated through macroscopic and microscopic approaches. This method provides high-fidelity samples for lunar water resource utilization, scientific exploration, and payload development on the Moon.

Numerical ellipsometry: Artificial intelligence for rapid analysis of indium tin oxide films on silicon

Ellipsometry is a well-known material analytical method widely used to measure thickness and optical properties of thin films and surfaces across a wide range of industrial and research applications including critical dimensions in chipmaking. The method employs the fact that light undergoes a change in polarization state upon reflection from or transmission through a material. The desired properties of the surface structure are related to measurements by the electromagnetic models expressed by Maxwell’s equations as well as models of material properties. The work here demonstrates the use of artificial intelligence in the form of a multilayer perceptron artificial neural network to apply the electromagnetic model. The reflecting surface examined here is composed of indium tin oxide (ITO) films approximately 400 nm in thickness deposited on silicon substrates. Solutions are provided by 299 artificial neural networks, one per wavelength from 210 to 1700 nm across which ITO exhibits transparent as well as absorbing characteristics. Thus, it serves as a proxy for a wide range of other materials. To train the network, simulated measurements are computed at two thicknesses which differ randomly by 1–6 nm and at three different incidence angles of 55°, 65°, and 75°. Following training, results are obtained in less than one second on a conventional desktop computer.

MicroRNAs regulate the vicious cycle of vascular calcification-osteoporosis in postmenopausal women.

Menopause is a normal physiological process accompanied by changes in various physiological states. The incidence of vascular calcification (VC) increases each year after menopause and is closely related to osteoporosis (OP). Although many studies have investigated the links between VC and OP, the interaction mechanism of the two under conditions of estrogen loss remains unclear. MicroRNAs (miRNAs), which are involved in epigenetic modification, play a critical role in estrogen-mediated mineralization. In the past several decades, miRNAs have been identified as biomarkers or therapeutic targets in diseases. Thus, we hypothesize that these small molecules can provide new diagnostic and therapeutic approaches. In this review, we summarize the close interactions between VC and OP and the role of miRNAs in their interplay.

Inalienable possession (and lack thereof) in Spanish

Abstract This paper revisits the phenomenon of inalienable possession between a dative argument and a body-part noun in Spanish. Specifically, it looks at contexts where the inalienable possession interpretation is obligatory, as in constructions containing monoeventive verbs of perception, and those where the inalienable reading becomes optional, namely with bi-eventive predicates denoting a change of state. I offer a possessor raising and applicative hybrid analysis, whereby the inalienable possessor originates inside the body-part DP and raises to the specifier of an applicative head to license dative case; the position ApplP occupies in the derivation determines the dative’s interpretation as a mere possessor (low applicative), or as an affected possessor as well (middle applicative). Alternatively, cases where the dative is not understood as the inalienable possessor but simply as affected occur when this argument is an additional one originating in the specifier of the middle applicative head, and the possessor of the body-part noun is encoded internally via a clitic or strong possessive, or by means of a genitive PP inside the DP. Thus, I propose the existence of two types of affected applicative heads: (i) one whose specifier is available for the possessor inside the possessum DP to move into to be case licensed, and (ii) another introducing an additional argument in its specifier. Additionally, this analysis accounts for the complementary distribution between dative possessors and possessive determiners in Spanish.

Cybercrime Intention Recognition: A Systematic Literature Review

Cybercrime Intention Recognition: A Systematic Literature Review

The Influence of the Teacher’s Psycho-Physiological States on the Development of Professional Competencies in the Course of the Military Aggression

The aim of the article is to determine the specifics of the impact of the correctional programme of psycho-physiological conditions on the development of the professional competence of general secondary school teachers. The Diagnostics of Mental States of the National Academy of Sciences and the Impact of Event Scale - Revised (IES-R) were used to obtain reliable data on the psycho-physiological state of the individual. A specialized online test for teachers was used to obtain data on the teachers’ competence aimed at determining informational competence, testing to determine the teacher’s subject methodical competence, observation of communicative competence. A formative experiment was planned and conducted. It was established that average indicators of psycho-physiological state prevail among teachers. The positive impact of the developed corrective programme on the teachers’ activity and mood was proved. It was concluded that the change in the psycho-physiological states of “invasion” and “avoidance” significantly depends on current social conditions, in particular, on the stability of the safety component. It was found that the correctional programme levelled the connections between the teachers’ subject methodical competence and the current psycho-physiological state. It was established that the teachers’ communicative competence continues to correlate after the completion of the programme with psycho-physiological comfort and general emotional background. In general, we can talk about the relative effectiveness of the developed corrective programme. The obtained results can be used to optimize programmes of continuous postgraduate education in the context of the development of resistance to the stresses of wartime. The prospects for further research are expanding the arsenal of methods for studying the teachers’ psycho-physiological state and clarifying gender differences in the teachers’ experience of stress. Received: 2 February 2024 / Accepted: 25 April 2024 / Published: 5 May 2024

Diminished representational momentum for physical states in patients with depressive disorder

The representational momentum for physical state changes refers to the fact that we remember objects as more changed in physical state than they actually were. It has been well documented that depressive disorder is associated with impairment of time perception. Thus, the present work was conducted with the aim to investigate the representational momentum for physical state changes in patients with depressive disorder, firstly. Forty patients with depressive disorder and forty-two healthy controls were administrated with the task of representational momentum for physical state changes and task of time perception. The stimulus comprises 10 videos showing object state changes (e.g., ice melting). During playing, the video would stop and immediately be obscured by mosaics at a specific point. Participants select from three detection images (the exact frame of the video just be masked, the frame after that, and the frame before that) to test representational momentum and estimate the duration of the video in seconds to test time perception. The depressive group showed diminished representational momentum (i.e., lower scores on the task of representational momentum) than normal controls (U = 215.00, Z = −5.83, p < 0.001). In addition, the scores on the task of representational momentum were significantly positively related with the scores on the task of time perception among depressive group (r = 0.446, p = 0.004). The findings indicate that patients with depressive disorder may exhibit diminished representational momentum for physical states, which may be correlated with their impairment of time perception.

In situ exsolved NiFe nanoparticles in Ni-doped Sr0.9Ti0.3Fe0.63Ni0.07O3‑δ anode with a three-dimensionally ordered macroporous structure for solid oxide fuel cells fueled by alkanes

In this work, A-site deficient Ni-doped Sr0.9Ti0.3Fe0.63Ni0.07O3‑δ perovskite anode with ordered macroporous structures (STFN-3DOM) is designed to facilitate in-situ Ni-Fe exsolution for solid oxide fuel cells fueled by alkanes, e.g., methane and propane. The large specific surface area and A-site deficient of STFN-3DOM provide more exsolved Ni-Fe active sites and enhance the reaction kinetics of alkane reforming. Quasi-in-situ XPS is used to reveal the changes in the chemical state of elements during the exsolution and propane reforming process on the STFN-3DOM surface. The synergistic effect of A-site deficient, three-dimensional ordered macroporous structure, and in-situ Ni-Fe exsolution promotes the La0.8Sr0.2Ga0.83Mg0.17O3‑δ (LSGM) electrolyte-supported SOFC single cell to deliver advanced performance with both wet H2 (1.33 W cm−2) and wet C3H8 (0.838 W cm−2) at 850 °C, exhibiting satisfactory long-time stability in CH4 and redox stability. Density functional theory calculation confirms the low activation energy of STFN-3DOM for the rate-limiting step of C3H8* dissociation.

Contact-angle hysteresis on rough surfaces: mechanical energy balance framework

Using as a starting point conservation of momentum, a multiphase mechanical energy balance equation is derived that accounts for multiple material phases and interfaces present within a moving control volume. This balance is applied to a control volume that is anchored to a three-phase contact line as it advances continuously over the surface of a rough and chemically homogeneous and inert solid. Using semi-quantitative models for the material behaviour occurring within the control volume, an order of magnitude analysis is performed to neglect insignificant terms, producing an equation for predicting contact-angle hysteresis from a knowledge of the interface dynamics occurring around the three-phase contact line. It is shown that the viscous energy dissipation that occurs during the ‘stick–slip’ motion of the three-phase contact line, being the cause of contact-angle hysteresis on rough surfaces, can be calculated from changes in intermediate equilibrium interface states. The balance is applied to the Wenzel, Cassie–Baxter and Fakir (super-hydrophobic) wetting states, showing for the Fakir case that significant dissipation occurs during both interface advance and recede, and relating these dissipations to interfacial area changes that occur around the ‘stick–slip’ events.

New architecture based on Metal-Organic Frameworks and spin crossover complexes to detect volatile organic compounds.

We present here the encapsulation of a spin crossover complex C1 [FeII(L)] (L: 4-amino-, 2-(2-pyridinylmethylene)hydrazide) inside MOF-808(Zr), a chemically robust Metal-Organic Framework. The compound C1⊂MOF-808 retains its crystallinity as well as a partial porosity compared to pristine MOF and shows solvatochromism under Volatile Organic compounds (VOCs) sorption associated to a spin state change of the guest complex. More specifically, this compound shows an interesting reversible color change under formaldehyde and formic acid vapor sorption and can therefore be considered as a new kind of optical VOCs chemosensor, opening new doors for developing a broad range of VOCs optical sensors.