Nonmonotonic Manner Research Articles

Curvature-Assisted Vesicle Explosion Under Light-Induced Asymmetric Oxidation.

Exposure of cell membranes to reactive oxygen species can cause oxidation of membrane lipids. Oxidized lipids undergo drastic conformational changes, compromising the mechanical integrity of the membrane and causing cell death. For giant unilamellar vesicles, a classic cell mimetic system, a range of mechanical responses under oxidative assault has been observed including formation of nanopores, transient micron-sized pores, and total sudden catastrophic collapse (i.e., explosion). However, the physical mechanism regarding how lipid oxidation causes vesicles to explode remains elusive. Here, with light-induced asymmetric oxidation experiments, the role of spontaneous curvature on vesicle instability and its link to the conformational changes of oxidized lipid products is systematically investigated. A comprehensive membrane model is proposed for pore-opening dynamics incorporating spontaneous curvature and membrane curling, which captures the experimental observations well. The kinetics of lipid oxidation are further characterized and how light-induced asymmetric oxidation generates spontaneous curvature in a non-monotonic temporal manner is rationalized. Using the framework, a phase diagram with an analytical criterion to predict transient pore formation or catastrophic vesicle collapse is provided. The work can shed light on understanding biomembrane stability under oxidative assault and strategizing release dynamics of vesicle-based drug deliverysystems.

Advanced feedback enhances sensorimotor adaptation

It is widely recognized that sensorimotor adaptation is facilitated when feedback is provided throughout the movement compared with when it is provided at the end of the movement. However, the source of this advantage is unclear: continuous feedback is more ecological, dynamic, and available earlier than endpoint feedback. Here, we assess the relative merits of these factors using a method that allows us to manipulate feedback timing independent of actual hand position. By manipulating the onset time of "endpoint" feedback, we found that adaptation was modulated in a non-monotonic manner, with the peak of the function occurring in advance of the hand reaching the target. Moreover, at this optimal time, learning was of similar magnitude as that observed with continuous feedback. By varying movement duration, we demonstrate that this optimal time occurs at a relatively fixed time after movement onset, an interval we hypothesize corresponds to when the comparison of the sensory prediction and feedback generates the strongest error signal.

Effects of Segment Length and Crosslinking via POSS on the Calorimetric and Dynamic Glass Transition of Polyurethanes with Aliphatic Hard Segments.

The glass transition in polyurethanes is a complicated phenomenon governed by a multitude of factors, including the microphase separation, which in turn depends strongly on the molar mass of the hard and soft segments, as well as the presence of additives. In this work, we study the effects of the segments' length on the microphase separation and consequently on the calorimetric and dynamic glass transition of a polyurethane with aliphatic, "flexible" hard segments. It is found that the dependence of the calorimetric glass transition follows the same principles as those in systems with aromatic hard segments. Strikingly, however, the dynamic glass transition, as studied by dielectric spectroscopy, shows a slowing down of its dynamics despite a decrease in Tg. This discrepancy is discussed in terms of the strong dielectric response of the flexible segments, especially those close to the interface between the hard domains and soft phase, as opposed to a weak thermal one. In addition, polyhedral oligomeric silsesquioxanes (POSS) are introduced in the soft phase of the three matrices as crosslinking centres. This modification has no visible effect on the calorimetric glass transition; nevertheless, it affects the microphase separation and the dielectric response in a non-monotonic manner.

GPx1 promotes hypertrophic differentiation of chondrocytes through modulation of akt signaling in a non-monotonic manner

GPx1 promotes hypertrophic differentiation of chondrocytes through modulation of akt signaling in a non-monotonic manner

Probing the Starobinsky-Bel-Robinson gravity by photon motion around the Kerr-type black hole in non-uniform plasma

This study investigates the optical properties of a rotating black hole in Starobinsky-Bel-Robinson gravity, characterized by the additional parameter β. The black hole is assumed to be surrounded by non-uniform plasma, with the plasma parameter k describing its effect on photon motion. The results reveal that the influence of the β parameter on the photon motion is significant near the black hole and it becomes weak at larger distances from the black hole. The deflection angle of photons for gravitational lensing which depends on the spin of the black hole demonstrates monotonic decrease with increase in the value of the plasma parameter k. The presence of the β parameter leads to a maximum deflection angle near the black hole, which decreases with increasing photon distance from the horizon of the black hole. The photon sphere radius is strongly affected by the β parameter and by the black hole spin, but weakly influenced by the plasma parameter. The shadow cast by the black hole which is altered by the β parameter, deformed on the left-hand side. Increase in the value of the plasma parameter k reduces the shadow size of the black hole. The effect of the spin on the shadow size is observed when β takes comparatively bigger values. The average shadow radius is affected by the spacetime parameters and plasma parameter, exhibiting a non-monotonic behavior with increasing β. The distortion of shadow of the black hole is influenced by the parameter β in a considerable and non-monotonic manner. Observational constraints for Sgr A* show our model aligns within confidence bounds but falls short of upper limits, revealing shadow radius limitations.

Modality-dependent distortion effects of temporal frequency on time perception.

Time perception has been known to depend on the temporal frequency of the stimulus. Previously, the effect of temporal frequency modulation was assumed to be monotonically lengthening or shortening. However, this study shows that temporal frequency affects time perception in a non-monotonic and modality-dependent manner. Four experiments investigated the time distortion effects induced by modulation of temporal frequency across auditory and visual modalities. Critically, the temporal frequency was parametrically manipulated across four levels (steady stimulus, 10-, 20-, and 30/40-Hz intermittent auditory/visual stimulus). Experiment 1, 2, and 3 consistently showed that a 10-Hz auditory stimulus was perceived as shorter than a steady auditory stimulus. Meanwhile, as the temporal frequency increased, the perceived duration of the intermittent auditory stimulus was lengthened. A 40-Hz auditory stimulus was perceived as longer than a 10- Hz auditory stimulus, but did not differ significantly from a steady one. Experiment 4 showed that, for the visual modality, a 10-Hz visual stimulus was perceived as longer than a steady stimulus, and the perceived duration was lengthened as temporal frequency increased. This study demonstrated that within the scope of the temporal frequencies examined in this study, there were differential distortion effects observed across sensory modalities.

Environmental Nickel Exposure and Cardiovascular Disease in a Nationally Representative Sample of U.S. Adults.

Laboratory studies have linked nickel with the pathogenesis of cardiovascular disease (CVD); however, few observational studies in humans have confirmed this association. This study aimed to use urinary nickel concentrations, as a biomarker of environmental nickel exposure, to evaluate the cross-sectional association between nickel exposure and CVD in a nationally representative sample of U.S. adults. Data from a nationally representative sample (n = 2702) in the National Health and Nutrition Examination Survey 2017-20 were used. CVD (n = 326) was defined as self-reported physicians' diagnoses of coronary heart disease, angina, heart attack, or stroke. Urinary nickel concentrations were determined by inductively coupled plasma mass spectrometry. Logistic regression with sample weights was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of CVD. Urinary nickel concentrations were higher in individuals with CVD (weighted median 1.34μg/L) compared to those without CVD (1.08μg/L). After adjustment for demographic, socioeconomic, lifestyle, and other risk factors for CVD, the ORs (95% CIs) for CVD compared with the lowest quartile of urinary nickel were 3.57 (1.73-7.36) for the second quartile, 3.61 (1.83-7.13) for the third quartile, and 2.40 (1.03-5.59) for the fourth quartile. Cubic spline regression revealed a non-monotonic, inverse U-shaped, association between urinary nickel and CVD (Pnonlinearity < 0.001). Nickel exposure is associated with CVD in a non-monotonic manner among U.S. adults independent of well-known CVD risk factors. The online version contains supplementary material available at 10.1007/s12403-023-00579-4.

19.31% binary organic solar cell and low non-radiative recombination enabled by non-monotonic intermediate state transition

Non-fullerene acceptors based organic solar cells represent the frontier of the field, owing to both the materials and morphology manipulation innovations. Non-radiative recombination loss suppression and performance boosting are in the center of organic solar cell research. Here, we developed a non-monotonic intermediate state manipulation strategy for state-of-the-art organic solar cells by employing 1,3,5-trichlorobenzene as crystallization regulator, which optimizes the film crystallization process, regulates the self-organization of bulk-heterojunction in a non-monotonic manner, i.e., first enhancing and then relaxing the molecular aggregation. As a result, the excessive aggregation of non-fullerene acceptors is avoided and we have achieved efficient organic solar cells with reduced non-radiative recombination loss. In PM6:BTP-eC9 organic solar cell, our strategy successfully offers a record binary organic solar cell efficiency of 19.31% (18.93% certified) with very low non-radiative recombination loss of 0.190 eV. And lower non-radiative recombination loss of 0.168 eV is further achieved in PM1:BTP-eC9 organic solar cell (19.10% efficiency), giving great promise to future organic solar cell research.

Size- and position-dependent cytoplasm viscoelasticity through hydrodynamic interactions with the cell surface

Many studies of cytoplasm rheology have focused on small components in the submicrometer scale. However, the cytoplasm also baths large organelles like nuclei, microtubule asters, or spindles that often take significant portions of cells and move across the cytoplasm to regulate cell division or polarization. Here, we translated passive components of sizes ranging from few up to ~50 percents of the cell diameter, through the vast cytoplasm of live sea urchin eggs, with calibrated magnetic forces. Creep and relaxation responses indicate that for objects larger than the micron size, the cytoplasm behaves as a Jeffreys material, viscoelastic at short timescales, and fluidizing at longer times. However, as component size approached that of cells, cytoplasm viscoelastic resistance increased in a nonmonotonic manner. Flow analysis and simulations suggest that this size-dependent viscoelasticity emerges from hydrodynamic interactions between the moving object and the static cell surface. This effect also yields to position-dependent viscoelasticity with objects initially closer to the cell surface being harder to displace. These findings suggest that the cytoplasm hydrodynamically couples large organelles to the cell surface to restrain their motion, with important implications for cell shape sensing and cellular organization.

Laser and pre-chamber ignition, combustion and flame propagation characteristics of CH4/air mixtures in a constant volume combustion chamber

The most important stages determining the qualitative and quantitative characteristics of a combustion process are mixture preparation, ignition, combustion itself and pollutant emissions. Among these, the ignition phenomenon stands out in terms of ensuring a reliable operation under every working condition (which also affects subsequent stages). In this study, the influence of the properties and the type of the ignition source on combustion and flame propagation characteristics of methane/air mixtures were investigated by using a passively Q-switched Nd:YAG crystal laser and a pre-chamber ignitor in a constant volume combustion chamber. The number of consecutive pulses and the air-fuel-equivalence ratio are studied parameters. With the laser ignition system, it was possible to ignite fuel-air mixtures at very lean conditions. However, as flow conditions in the combustion chamber varied due to the protruding part of the pre-chamber ignitor, ignition possibility decreased and combustion metrics worsened. The number of pulses affected combustion parameters such as the ignition delay time, the combustion duration, the rate of pressure rise etc. in a non-monotonic manner. Deteriorations and improvements on such parameters were detected depending on the air–fuel-equivalence ratio λ.

Can pharmaceutical pollution alter the spread of infectious disease? A case study using fluoxetine.

Human activity is changing global environments at an unprecedented rate, imposing new ecological and evolutionary ramifications on wildlife dynamics, including host-parasite interactions. Here we investigate how an emerging concern of modern human activity, pharmaceutical pollution, influences the spread of disease in a population, using the water flea Daphnia magna and the bacterial pathogen Pasteuria ramosa as a model system. We found that exposure to different concentrations of fluoxetine-a widely prescribed psychoactive drug and widespread contaminant of aquatic ecosystems-affected the severity of disease experienced by an individual in a non-monotonic manner. The direction and magnitude of any effect, however, varied with both the infection outcome measured and the genotype of the pathogen. By contrast, the characteristics of unexposed animals, and thus the growth and density of susceptible hosts, were robust to fluoxetine. Using our data to parameterize an epidemiological model, we show that fluoxetine is unlikely to lead to a net increase or decrease in the likelihood of an infectious disease outbreak, as measured by a pathogen's transmission rate or basic reproductive number. Instead, any given pathogen genotype may experience a twofold change in likely fitness, but often in opposing directions. Our study demonstrates that changes in pharmaceutical pollution give rise to complex genotype-by-environment interactions in its influence of disease dynamics, with repercussions on pathogen genetic diversity and evolution. This article is part of the theme issue 'Infectious disease ecology and evolution in a changing world'.

Infectious disease ecology and evolution in a changing world.

Infectious disease ecology and evolution in a changing world.

Contrasting dose response relationships of neuroactive antidepressants on the behavior of C. elegans

Antidepressant prescriptions are on a rise worldwide and this increases the concerns for the impacts of these pharmaceuticals on nontarget organisms. Antidepressants are neuroactive compounds that can affect organism’s behavior. Behavior is a sensitive endpoint that may also propagate effects at a population level. Another interesting aspect of antidepressants is that they have shown to induce non-monotonic dose-response (NMDR) curves. While such NMDR relationships may have clear implications for the environmental risk, the resolution of current studies is often too coarse to be able to detect relevant NMDR. Therefore, the current study was performed into the behavioral effects (activity, feeding and chemotaxis) in Caenorhabditis elegans as the model organism of the selective serotonin reuptake inhibitors fluoxetine and sertraline and the acetylcholinesterase inhibiting pesticide chlorpyrifos, using a wide range of concentrations (ng/l to mg/l). In order to statistically examine the non-monotonicity, nonlinear regression models were applied to the results. The results showed a triphasic dose-response relationship for activity and chemotaxis after exposure to fluoxetine, but not to sertraline or chlorpyrifos. Effects of fluoxetine already occurred at low concentrations in the range of ng/l while sertraline only showed effects at concentrations in the μg/l range, similar to chlorpyrifos. The different responses between fluoxetine and sertraline, both SSRIs, indicate that response patterns may not always be extrapolated from chemicals with the same primary mode of action. The effects of fluoxetine at low concentrations, in a non-monotonic manner, confirm the relevance of examining such responses at low concentrations.

Aqueous solution synthesis and size control of acid-resistant β-Ga2O3 microparticles

Ellipsoid-shape acid-resistant microparticles of β-Ga2O3 are synthesized as a result of chemical reaction of gallium nitrate and ammonia in an aqueous solution with subsequent annealing of received sediment in air. It is shown that particle size depends in non-monotonous manner on the molar ratio of reacting substances. The maximum value of length and diameter (1718 ± 291 nm and 746 ± 198 nm, respectively) is obtained at ammonia to gallium nitrate ratio of 9:1. A decrease in particle size is observed both with reducing and increasing of the ratio. The particles have a layered structure with layer thickness 30 ± 5 nm.

Dilution of a polar magnet: Structure and magnetism of Zn-substituted Co2Mo3O8

We report crystal structure, magnetization, and specific heat measurements on single crystals of the hexagonal polar magnet ${\mathrm{Co}}_{2\text{\ensuremath{-}}x}{\mathrm{Zn}}_{x}{\mathrm{Mo}}_{3}{\mathrm{O}}_{8}$ magnetically diluted by replacing Co by Zn. In contrast to the transformation from the antiferromagnetic to a ferrimagnetic state observed in the isostructural ${\mathrm{Fe}}_{2}{\mathrm{Mo}}_{3}{\mathrm{O}}_{8}$ upon small Zn doping, a robust antiferromagnetic behavior is preserved in Zn-doped ${\mathrm{Co}}_{2}{\mathrm{Mo}}_{3}{\mathrm{O}}_{8}$ up to $x=0.55$. The N\'eel temperature decreases from ${T}_{\mathrm{N}}=40$ K at $x=0$ to 23 K at $x=0.55$, thus extrapolating to $x=1.27$ (36% filling) as the percolation threshold typical for a three-dimensional, highly coordinated network. This indicates strong magnetic couplings beyond the honeycomb planes in ${\mathrm{Co}}_{2}{\mathrm{Mo}}_{3}{\mathrm{O}}_{8}$. A sharp peak in the specific heat and a clear cusp in the susceptibility associated with the onset of magnetic order is observed up to $x=0.55$, whereas at $x=0.66$ these features are broadened due to increased disorder. Interestingly, the in-plane lattice parameter, the Curie-Weiss temperature, and the magnetic entropy vary with $x$ in a concerted but nonmonotonic manner. These observations can be traced back to the observed site-selective Zn substitution. We found that in the low-doping regime ($x&lt;0.2$) ${\mathrm{Zn}}^{2+}$ ions primarily occupy the octahedrally coordinated sites, although they have a clear preference for occupying the tetrahedrally coordinated sites at higher doping levels. Due to the multiple interlayer exchange paths, dependent on the coordination of the ${\mathrm{Co}}^{2+}$ ions, this behavior is reflected in the nonmonotonic variation of the Curie-Weiss temperature and magnetic entropy with substitution.

Time interval uncertainty-aware and text-enhanced based disease prediction

Deep learning methods have achieved success in disease prediction using electronic health records (EHR) data. Most of the existing methods have some limitations. First, most of the methods adopt a homogeneous decay way to deal with the effect of time interval on patient’s previous visits information. However, the effect of the time interval between patient’s visits is not always negative. For example, although the time interval between visits for patients with chronic diseases is relatively long, the importance of the previous visit to the next visit is high, and we may not be able to consider the effect of the time interval as negative at this point. That is, the effect of the time interval on previous visits is exerted in a nonmonotonic manner, and it is either positive, negative, or neutral. In addition, the effect of text information on prediction results is not taken into account in most of methods. The text in EHR contains a description of the patient’s past medical history and current symptoms of the disease, which is important for prediction results. In order to solve these issues, we propose a Time Interval Uncertainty-Aware and Text-Enhanced Based Disease Prediction Model, which utilizes the uncertain effects of time intervals and patient’s text information for disease prediction. Firstly, we apply a cross-attention mechanism to generate a global representation of the patient using the patient’s disease and text information from the EHR. Then, we use the key–query attention mechanism to obtain the two importance weights of the two visit sequences with and without time intervals, respectively. Furthermore, we achieve disease prediction by making slight adjustments to the encode part of the Transformer, a deep learning model based on a self-attention mechanism. We compare with various state-of-the-art models on two publicly available datasets, MIMIC-III and MIMIC-IV, and select the top 10 diseases with the highest frequency in the dataset as the target diseases. On the MIMIC-III dataset, our model is up to three percent higher than the optimal baseline in terms of evaluation metrics.

Effects of ionic strength and particle size on transport of microplastic and humic acid in porous media

As an emerging pollutant, the transport behavior of colloidal microplastic particles (CMPs) in saturated porous media may be affected by the simultaneous presence of other substances in the natural environment. In this study, colloidal polystyrene microplastic particles (PSMPs) were selected as the representative of CMPs to investigate the cotransport behaviors of CMPs in the presence of humic acid (HA) under varied environmental conditions (ionic strength: 1, 100 mM KCl; HA concentration: 0, 5, 10, 20 mg⋅L−1) in porous media. The presence of HA with different concentrations was found to increase the mobility of 1.0-μm and 0.2-μm CMPs in porous media in a non-linear and non-monotonic manner. Furthermore, the HA-facilitated transport of CMPs occurred under both electrostatically unfavorable and favorable attachment conditions (limited to the conditions examined in this study, corresponding to 1 and 100 mM KCl, respectively). The transport behavior of the smaller-sized CMPs (0.2-μm CMPs) was more sensitive to the change of ionic strength and the presence of HA than that of the larger-sized CMPs (1.0-μm CMPs). The cotransport process of CMPs and HA was affected by many factors. Modeling results showed that a small amount of competitive blocking occurred during the cotransport process. Moreover, both the presence of HA and change in ionic strength could affect the surface properties of CMPs. Thus, the cotransport behavior of CMPs with HA was different from the transport of individual CMPs in porous media. Experimental results revealed that HA induced complexity in the transport behavior of CMPs in the aqueous environment. Therefore, undeniably, a lot more systematic explorations are further demanded to better comprehend the CMPs cotransport mechanism in the presence of other substances.

Experimental and population balance model interpretation of foam physics in porous media

Foam has been used as an effective displacing fluid for gas mobility control in enhanced oil recovery (EOR) and subsurface remediation. In this study, a series of core flooding experiments are performed on cores with a wide permeability ranging from 3.3 to 2749 mD to evaluate the impact of foam quality and permeability on foam performance. It is found that the steady-state foam mobility control factor is related to permeability in a non-linear, non-monotonic manner. A full physics, mechanistic foam model is proposed by incorporating a novel flowing foam fraction relation grounded-up from pore-level observations, and a new kinetic expression of foam coalescence rate by oil based on pinch-off foam rupture mechanism into the population-balance framework of Almajid et al. (Advances in Water Resources, 2021, 150: 103877). The proposed model is applied to match foam flow experimental results in the absence and in the presence of oil. Results show that our model captures the high-quality and low-quality foam regimes observed in previous oil-free foam flow experiments. Within the medium permeability range, in the absence of oil, lower gas mobility is observed in the lower permeability core due to faster foam film thinning at higher capillary pressure, while in the presence of residual oil, the difference in foam mobility fades away due to the insignificant impact of capillary pressure on the stability of pseudoemulsion films.

Macroeconomic co-benefits of DRR investment: assessment using the Dynamic Model of Multi-hazard Mitigation CoBenefits (DYNAMMICs) model

PurposeThe authors present a dynamic macroeconomic model for assessment of disaster risk reduction (DRR) policies under multiple hazards. The model can be used to analyze and compare various potential policies in terms of their economic consequences. The decomposition of these effects into multiple benefits helps policy makers and other stakeholders better understand the ex ante and ex-post advantages of DRR investments. The purpose of this paper is to address these issues.Design/methodology/approachA dynamic real business cycle model is at the core of this research. In the model multiple natural hazards modeled stochastically cause shocks to the economy. Economic outcomes, most importantly, output can be assessed before and after disasters and under various DRR policies. The decomposition of benefits aims to quantify the concept of triple dividends.FindingsIn case study applications in Tanzania and Zambia, the authors find that investments into physical infrastructure and risk transfer instruments generate a variety of benefits even in the absence of disaster. A land use restriction with planned relocation for example reduces output in the short run but in the long run increases it. Overall, policy effects of various DRR interventions evolve in a nonmonotonic manner and should be evaluated over a long period of time using dynamic simulation.Originality/valueThe novelty of this study lies in the economic quantification of multiple benefits described in the triple dividends literature. This helps comparing ex ante, ex-post and volatility-related economic effects of multiple disasters and related physical and financial DRR investment options. As observed in the case studies, the model can also identify overlooked temporal heterogeneity of co-benefits of DRR investments.

Racial/ethnic disparities in nationwide PM2.5 exposure: perils of assuming a linear relationship

BACKGROUND AND AIM Studies of racial/ethnic disparities in air pollution exposure assume an equal magnitude of disparity across the demographic distribution, which may under- or over-estimate the true disparity. Further, historic practices such as racist zoning policies could plausibly drive non-linear relationships between racial/ethnic composition and air pollution exposure. We aimed to conduct a nationwide analysis in urban areas allowing for non-linearity in the relationship between racial/ethnic composition and ambient particulate matter less than 2.5 micrometers (PM₂.₅), and test whether racial segregation modified this relationship. METHODS We obtained tract-level demographic information from the 2010 Census and computed the multi-group dissimilarity index, a metropolitan-area level measure of racial segregation. Ambient PM₂.₅ data was obtained from a publicly available source. We evaluated the relationship between percent non-Hispanic Black and percent non-Hispanic White residents and ambient PM₂.₅ using natural splines. RESULTS In 58,029 U.S. urban census tracts in 2010, we observed first a very steep and then a plateauing relationship between percent non-Hispanic Black residents and ambient PM₂.₅ concentration. Moving from the 25th percentile (1%) to the median (5%) of non-Hispanic Black residents was associated with a 0.58 &amp;#x3bc;g/m³ (95% CI: 0.56, 0.60) increase in PM₂.₅, while moving from the median to the 75th percentile (16% non-Hispanic Black) was associated with a 0.005 &amp;#x3bc;g/m³ (95% CI: -0.012, 0.020) increase. Reciprocally, in predominantly White census tracts, increases in the proportion of White residents was associated with a rapid decrease in ambient PM₂.₅. Segregation modified these relationships in a non-monotonic manner. CONCLUSIONS Our results suggest larger than previously reported Black-White disparities in exposure to PM₂.₅, especially in communities with a modest Black population, which make up the majority of urban census tracts in the US. KEYWORDS Racial/ethnic disparities; Air pollution; Particulate Matter; Environmental justice