Digital brains, green gains: Artificial intelligence's path to sustainable transformation.

The environmental impacts of artificial intelligence on a global scale remain underexplored. This study utilizes a balanced panel dataset to examine artificial intelligence's complex role in enhancing global green productivity between 2008 and 2019. The findings indicate that artificial intelligence robustly boosts green productivity, even after correcting for potential endogeneity using the legal system's origin as an instrument. A detailed mediation analysis underscores that artificial intelligence indirectly promotes green productivity by increasing renewable energy use, attracting skilled labor, and dampening stock market performance. Additional analysis confirms that financial development generally amplifies artificial intelligence's favorable effects on green productivity. However, the combined impact of financial institution access and artificial intelligence on green productivity initially appears hostile, an effect that can be reversed when financial access exceeds a certain threshold. These results offer valuable insights into the interconnection between artificial intelligence and the global shift towards greener practices.

Nonlinear relationship between triglyceride-glucose index and the risk of prediabetes and diabetes: a secondary retrospective cohort study.

Background: The triglyceride-glucose (TyG) index, recognized for its cost-efficiency and simplicity, serves as an accessible indicator of insulin resistance. Yet, its correlation with the risk of prediabetes and diabetes (Pre-DM/DM) in the Chinese demographic remains uncertain. Consequently, our study explored the association between the TyG index and the development of Pre-DM/DM within the Chinese population. Methods: The retrospective cohort study was carried out utilizing data from a health screening initiative. The study included 179541 adults over 20 who underwent medical examinations at the Rich Healthcare Group over a period spanning from 2010 to 2016. The correlation between the TyG index and Pre-DM/DM risk was investigated using Cox regression analysis. Furthermore, Cox proportional hazards regression with cubic spline functions and smooth curve fitting was incorporated to explore their non-linear connection. Results: The mean age of study participants was 41.18 ± 12.20 years old, and 95255 (53.05%) were male. During a median follow-up of 3.01 years, 21281 (11.85%) participants were diagnosed with Pre-DM/DM. After adjusting the potential confounding factors, the results showed that the TyG index was positively correlated with incident Pre-DM/DM (HR: 1.67, 95%CI: 1.62-1.71, P< 0.001). Additionally, a non-linear association was observed between the TyG index and the onset of Pre-DM/DM, with an inflection point identified at 8.73. Hazard ratios (HR) to the left and right of this inflection point were 1.95 (95%CI: 1.86-2.04) and 1.34 (95%CI: 1.27-1.42), respectively. Furthermore, sensitivity analyses confirmed the stability of these findings. Conclusion: The TyG index exhibited a non-linear positive relationship with the risk of Pre-DM/DM. These findings imply that maintaining the TyG index at a lower, specified threshold may be beneficial in mitigating the onset of Pre-DM/DM.

Continuously tunable single-photon level nonlinearity with Rydberg state wave-function engineering.

Extending optical nonlinearity into the extremely weak light regime is at the heart of quantum optics, since it enables the efficient generation of photonic entanglement and implementation of photonic quantum logic gate. Here, we demonstrate the capability for continuously tunable single-photon level nonlinearity, enabled by precise control of Rydberg interaction over two orders of magnitude, through the use of microwave-assisted wave-function engineering. To characterize this nonlinearity, light storage and retrieval protocol utilizing Rydberg electromagnetically induced transparency is employed, and the quantum statistics of the retrieved photons are analyzed. As a first application, we demonstrate our protocol can speed up the preparation of single photons in low-lying Rydberg states by a factor of up to ~40. Our work holds the potential to accelerate quantum operations and to improve the circuit depth and connectivity in Rydberg systems, representing a crucial step towards scalable quantum information processing with Rydberg atoms.

The nonlinear connection between relative fat mass and non-alcoholic fatty liver disease in the Japanese population: an analysis based on data from a cross-sectional study.

BACKGROUND: Relative fat mass (RFM) is a newly developed, sex-specific anthropometric formula designed to estimate total body fat percentage. However, research investigating the correlation between RFM and the risk of non-alcoholic fatty liver disease (NAFLD) remains limited. This study evaluates the association between RFM and the risk of NAFLD within the Japanese population. METHODS: This study including 14,250 Japanese adults who underwent physical examinations at Murakami Memorial Hospital between 2004 and 2015. We employed binary logistic regression to elucidate the direct relationship between RFM levels and the incidence of NAFLD. Additionally, a generalized additive model (GAM) coupled with smooth curve fitting techniques was utilized to map the non-linear association. RESULTS: The cohort had an average age of 43.53 ± 8.89 years, with a male majority of 52.00%. NAFLD was identified in 17.59% of the participants. After adjusting for confounding factors, a significant positive correlation between RFM and NAFLD risk was observed (OR: 1.15, 95%CI: 1.10-1.21, P < 0.0001 for females; OR: 1.15, 95%CI: 1.10-1.19, P < 0.0001 for males). Additionally, a non-linear relationship between RFM and the incidence of NAFLD was detected in both genders. The RFM threshold was identified as 34.95 for women and 23.40 for men. RFM was positively associated with the risk of NAFLD when RFM was below the respective threshold (OR: 1.29, 95%CI: 1.19-1.40, P < 0.0001 for females; OR: 1.23, 95%CI: 1.17-1.29, P < 0.0001 for males), whereas no significant association was found when RFM was above the threshold (OR: 1.05, 95%CI: 0.98-1.12, P = 0.1829 for females; OR: 1.01, 95%CI: 0.95-1.08, P = 0.7392 for males). CONCLUSION: Our findings suggest a positive, nonlinear relationship between RFM and the risk of NAFLD, with a saturation effect. These results imply that maintaining RFM at a lower level may be advantageous in mitigating the risk of NAFLD.

Task-guided attention increases non-linearity of steady-state visually evoked potentials.

Attention is a multifaceted cognitive process, with nonlinear dynamics playing a crucial role. In this study, we investigated the involvement of nonlinear processes in top-down visual attention by employing a contrast-modulated sequence of letters and numerals, encircled by a consistently flickering white square on a black background - a setup that generated steady-state visually evoked potentials. Nonlinear processes are recognized for eliciting and modulating the harmonics of constant frequencies. We examined the fundamental and harmonic frequencies of each stimulus to evaluate the underlying nonlinear dynamics during stimulus processing. In line with prior research, our findings indicate that the power spectrum density of EEG responses is influenced by both task presence and stimulus contrast. By utilizing the Rhythmic Entrainment Source Separation (RESS) technique, we discovered that actively searching for a target within a letter stream heightened the amplitude of the fundamental frequency and harmonics related to the background flickering stimulus. While the fundamental frequency amplitude remained unaffected by stimulus contrast, a lower contrast led to an increase in the second harmonic's amplitude. We assessed the relationship between the contrast response function and the nonlinear-based harmonic responses. Our findings contribute to a more nuanced understanding of the nonlinear processes impacting top-down visual attention while also providing insights into optimizing brain-computer interfaces. .

Cubic nonlinearity and surface shock waves in soft tissue-like materials.

The cubic nonlinearity of shear wave propagation plays a significant role in brain injury biomechanics. However, soft materials, like the brain, also support the propagation of surface waves, which produce a combination of longitudinal and transverse deformation. The order of the nonlinearity of surface waves in soft materials is still unknown. Here, we directly observe nonlinear Scholte waves propagating in an interface formed by an incompressible gelatin tissue-mimicking phantom and a water layer using ultrasound imaging operated as fast as 16667 frames per second. A two-dimensional correlation-based tracking algorithm was utilized to extract movies of the movement produced by the surface wave. Our results show that the initially nearly monochromatic wave becomes progressively distorted with the propagation due to nonlinearity. The distortion of the wave and its frequency spectrum indicate a high content of odd harmonics when compared with even harmonics. Additionally, by fitting our experimental data to a minimalist one-dimensional model based on the wave speed variation as a function of the perturbation amplitude, we found a cubic nonlinear parameter 46 times larger than the quadratic nonlinear parameter. Overall, the wave distortion, the harmonic development, and the dependence of the wave speed with the amplitude prove that cubic nonlinearity is essential to modeling nonlinear Scholte wave propagation.

Novel soliton solutions and phase plane analysis in nonlinear Schrödinger equations with logarithmic nonlinearities.

This paper investigates a generalized form of the nonlinear Schrödinger equation characterized by a logarithmic nonlinearity. The nonlinear Schrödinger equation, a fundamental equation in nonlinear wave theory, is applied across various physical systems including nonlinear optics, Bose-Einstein condensates, and fluid dynamics. We specifically explore a logarithmic variant of the nonlinear Schrödinger equation to model complex wave phenomena that conventional polynomial nonlinearities fail to capture. We derive four distinct forms of the nonlinear Schrödinger equation with logarithmic nonlinearity and provide exact solutions for each, encompassing bright, dark, and kink-type solitons, as well as a range of periodic solitary waves. Analytical techniques are employed to construct bounded and unbounded traveling wave solutions, and the dynamics of these solutions are analyzed through phase portraits of the associated dynamical systems. These findings extend the scope of the nonlinear Schrödinger equation to more accurately describe wave behaviors in complex media and open avenues for future research into non-standard nonlinear wave equations.

Numerical Investigation of Fracture Behaviour of Polyurethane Adhesives under the Influence of Moisture.

The mechanical behaviour of polymer adhesives is influenced by the environmental conditions leading to ageing and affecting the integrity of the material. The polymer adhesives have hygroscopic behaviour and tend to absorb moisture from the environment, causing the material to swell without applying external load. The focus of the work is to investigate the viscoelastic material behaviour under ageing conditions. The constitutive equations and the governing equations to numerically investigate the fracture in swollen viscoelastic material are discussed to describe the numerical implementation. Phase-field damage modelling has been used in numerical studies of ductile and brittle materials for a long time. The finite-strain phase-field damage model is used to investigate the fracture behaviour in aged viscoelastic polymer adhesives. The finite-strain viscoelastic model is formulated based on the continuum rheological model by combining spring and Maxwell elements in parallel. Commercially available post-cured crosslinked polyurethane adhesives are used in the current investigation. Post-cured samples of crosslinked polyurethane adhesives are prepared for different humidity conditions under isothermal conditions. These aged samples are used to perform tensile and tear tests and the test data are used to identify the material parameters from the curve fitting process. The experiment and simulation are compared to relate the findings and are the first step forward to improve the method to model crosslinked polymers.

Testing nonlinearity of heavy-tailed time series.

A test statistic for nonlinearity of a given heavy-tailed time series process is constructed, based on the sub-sample stability of Gini-based sample autocorrelations. The finite-sample performance of the proposed test is evaluated in a Monte Carlo study and compared to a similar test based on the sub-sample stability of a heavy-tailed analogue of the conventional sample autocorrelation function. In terms of size and power properties, the quality of our test outperforms a nonlinearity test for heavy-tailed time series processes proposed by [S.I. Resnick and E. Van den Berg, A test for nonlinearity of time series with infinite variance, Extremes 3 (2000), pp. 145-172.]. A nonlinear Pareto-type autoregressive process and a nonlinear Pareto-type moving average process are used as alternative specifications when comparing the power of the proposed test statistic. The efficacy of the test is illustrated via the analysis of a heavy-tailed actuarial data set and two time series of Ethernet traffic.

Receptive-field nonlinearities in primary auditory cortex: a comparative perspective.

Cortical processing of auditory information can be affected by interspecies differences as well as brain states. Here we compare multifeature spectro-temporal receptive fields (STRFs) and associated input/output functions or nonlinearities (NLs) of neurons in primary auditory cortex (AC) of four mammalian species. Single-unit recordings were performed in awake animals (female squirrel monkeys, female, and male mice) and anesthetized animals (female squirrel monkeys, rats, and cats). Neuronal responses were modeled as consisting of two STRFs and their associated NLs. The NLs for the STRF with the highest information content show a broad distribution between linear and quadratic forms. In awake animals, we find a higher percentage of quadratic-like NLs as opposed to more linear NLs in anesthetized animals. Moderate sex differences of the shape of NLs were observed between male and female unanesthetized mice. This indicates that the core AC possesses a rich variety of potential computations, particularly in awake animals, suggesting that multiple computational algorithms are at play to enable the auditory system's robust recognition of auditory events.

Nonlinear Gradient Field Estimation in Diffusion MRI Tensor Simulation.

Gradient nonlinearities not only induce spatial distortion in magnetic resonance imaging (MRI), but also introduce discrepancies between intended and acquired diffusion sensitization in diffusion weighted (DW) MRI. Advances in scanner performance have increased the importance of correcting gradient nonlinearities. The most common approaches for gradient nonlinear field estimations rely on phantom calibration field maps which are not always feasible, especially on retrospective data. Here, we derive a quadratic minimization problem for the complete gradient nonlinear field (L(r)). This approach starts with corrupt diffusion signal and estimates the L(r) in two scenarios: (1) the true diffusion tensor known and (2) the true diffusion tensor unknown (i.e., diffusion tensor is estimated). We show the validity of this mathematical approach, both theoretically and through tensor simulation. The estimated field is assessed through diffusion tensor metrics: mean diffusivity (MD), fractional anisotropy (FA), and principal eigenvector (V1). In simulation with 300 diffusion tensors, the study shows the mathematical model is not ill-posed and remains stable. We find when the true diffusion tensor is known (1) the change in determinant of the estimated L(r) field and the true field is near zero and (2) the median difference in estimated L(r) corrected diffusion metrics to true values is near zero. We find the results of L(r) estimation are dependent on the level of L(r) corruption. This work provides an approach to estimate gradient field without the need for additional calibration scans. To the best of our knowledge, the mathematical derivation presented here is novel.

Cross-correlation and multifractality analysis of the Chinese and American stock markets based on the MF-DCCA model.

Objective: To compare the multifractal features and factors of the Chinese and American stock markets and their correlation, complexity and uncertainty. Methods: The paper analyzes the CSI 300 and S&P 500 indices from March 2018 to March 2023 using the MF-DCCA model and removes the long-term memory and nonlinear effects by random reshuffling and phase processing methods. Results: The paper shows that (1) CSI 300 and S&P 500 have multifractal features, with different long-term memory, complexity and irregularity at different scales; (2) The markets are fractal movements influenced by investors' irrationality and expectations, not efficient markets; (3) Long-term memory and nonlinear effects cause the multifractal features. The paper offers a new perspective and method for the market investors and regulators.

Hybrid Fibers with Subwavelength-Scale Liquid Core for Highly Sensitive Sensing and Enhanced Nonlinearity.

Interest grows in designing silicon-on-insulator slot waveguides to trap optical fields in subwavelength-scale slots and developing their optofluidic devices. However, it is worth noting that the inherent limitations of the waveguide structures may result in high optical losses and short optical paths, which challenge the device's performance in optofluidics. Incorporating the planar silicon-based slot waveguide concept into a silica-based hollow-core fiber can provide a perfect solution to realize an efficient optofluidic waveguide. Here, we propose a subwavelength-scale liquid-core hybrid fiber (LCHF), where the core is filled with carbon disulfide and surrounded by a silicon ring in a silica background. The waveguide properties and the Stimulated Raman Scattering (SRS) effect in the LCHF are investigated. The fraction of power inside the core of 56.3% allows for improved sensitivity in optical sensing, while the modal Raman gain of 23.60 m-1·W-1 is two times larger than that generated around a nanofiber with the interaction between the evanescent optical field and the surrounding Raman media benzene-methanol, which enables a significant low-threshold SRS effect. Moreover, this in-fiber structure features compactness, robustness, flexibility, ease of implementation in both trace sample consumption and reasonable liquid filling duration, as well as compatibility with optical fiber systems. The detailed analyses of the properties and utilizations of the LCHF suggest a promising in-fiber optofluidic platform, which provides a novel insight into optofluidic devices, optical sensing, nonlinear optics, etc.

Association of hemoglobin-to-red cell distribution width ratio with the three-month outcomes in patients with acute ischemic stroke.

Aim: To explore the association of Hemoglobin-to-Red Cell Distribution Width Ratio (HRR) with the risk of three-month unfavorable outcomes in acute ischemic stroke (AIS). Methods: A secondary analysis was conducted based on a prospective cohort study. A total of 1,889 patients with AIS treated in South Korea from January 2010 to December 2016 were enrolled. Multivariable logistic regression was conducted to investigated the independent relationship between HRR and risk of three-month unfavorable outcomes in AIS. Fitted smoothing curves were used to determine non-linear correlations. The recursive method was employed to explore the turning point and build a two-piece linear regression model. In addition, a set of subgroup analyses were carried out to evaluate the relationship between HRR and risk of three-month unfavorable outcomes. Results: Multivariate analysis in which potential confounders were adjusted for indicated that the risk of unfavorable outcomes was reduced by 10% for each unit increased of HRR [OR = 0.90, 95% CI: 0.84-0.96, p = 0.0024]. In addition, a non-linear relationship was observed between HRR and risk of three-month unfavorable outcomes, which had an inflection point of HRR was 10.57. The effect sizes and the confidence intervals on the left side of the inflection point were 0.83 (0.75, 0.91), p = 0.0001. On the right side of the inflection point, no association was found between HRR and the risk of three-month unfavorable outcomes. Conclusion: This study demonstrates a negative association between HRR and risk of three-month unfavorable outcomes. The relationship between HRR and risk of three-month unfavorable outcomes is non-linear. The correlation is negative for HRR values less than 10.57. For, HRR higher than 10.57, HRR is not associated with the risk of three-month unfavorable outcomes.

Newest Methods and Approaches to Enhance the Performance of Optical Frequency-Domain Reflectometers.

In this review, we summarize the latest advances in the design of optical frequency-domain reflectometers (OFDRs), digital signal processing, and sensors based on special optical fibers. We discuss state-of-the-art approaches to improving metrological characteristics, such as spatial resolution, SNR, dynamic range, and the accuracy of determining back reflection coefficients. We also analyze the latest achievements in the OFDR-based sensors: the accuracy of spatial localization of the impact, the error in detecting temperatures, deformation, and other quantities, and the features of separate measurement of various physical quantities. We also pay attention to the trend of mutual integration of frequency-domain optical reflectometry methods with time-domain optical reflectometry, which provides completely new sensing possibilities. We believe that this review may be useful to engineers and scientists focused on developing a lab setup, complete measurement instrument, or sensing system with specific requirements.

Modelling insertion behaviour of PVP (Polyvinylpyrrolidone) and PVA (Polyvinyl Alcohol) microneedles.

A comprehensive investigation into the effects of nonlinear material behaviour of polymeric (MN) and skin on the dynamics of the MN insertion in skin was undertaken in this study using experiments and numerical simulations. The nonlinearity of the material behaviour was incorporated by employing the Ramberg-Osgood and neo-Hookean equations for stress-strain relationships for the MN materials and skin, respectively. For this purpose, a characteristic type of dissolving MN array was selected. This type of MN is made by a combination of poly(vinyl alcohol) and poly(vinyl pyrrolidone). The numerical simulations were validated using experimental investigations where the MNs were fabricated using laser-engineered silicone micromould templates technology. Young's modulus, Poisson's ratio, and compression breaking force for the MN polymers were determined using a texture analyser. The alignment between experimental findings and simulation data underscores the accuracy of the parameters determined through mechanical testing and mathematical calculations for both MN materials (PVP/PVA) and skin behaviour during the MN insertion. This study has demonstrated a strong alignment between the experimental findings and computational simulations, confirming the accuracy of the established parameters for MNs and skin interactions for modelling MN insertion behaviour in skin, providing a solid foundation for future research in this area.

Generation of Soliton Frequency Combs in NEMS.

In this study, we present an innovative approach leveraging combination internal resonances within a NEMS platform to generate mechanical soliton frequency combs (FCs) spanning a broad spectrum. In the time domain, the FCs take the form of a periodic train of narrow pulses, a highly coveted phenomenon within the realm of nonlinear wave-matter interactions. Our method relies on an intricate interaction among multiple vibration modes of a bracket-nanocantilever enabled by the strong nonlinearity of the electrostatic field. Through numerical simulation and experimental validation, we demonstrate that by amplifying the motions of the NEMS with the external electrostatic forcing tuned to excite the superharmonic resonance of order-n of the fundamental mode and exploiting combination internal resonances, we can generate multiple stable localized mechanical wave packets with different lobe sizes embodying soliton states I and II. This represents a significant breakthrough with profound implications for quantum computing and metrology.

Do bitcoin electricity consumption and carbon footprint exhibit random walk and bubbles? Analysis with policy implications.

One of the main current focuses of global economies and decision-makers is the efficiency of energy utilization in cryptocurrency mining and trading, along with the reduction of associated carbon emissions. Understanding the pattern of Bitcoin's energy consumption and its bubble frequency can greatly enhance policy analysis and decision-making for energy efficiency and carbon emission reduction. This research aims to assess the validity of the random walk hypothesis for Bitcoin's electricity consumption and carbon footprint. We employed both traditional methods (ADF and KPSS) and recently proposed unit root techniques that account for structural breaks and non-linearity in the data series. Our analysis covers daily data from July 2010 to December 2021. The empirical results revealed that traditional unit root techniques did not confirm the stationarity of both bitcoin's electricity consumption and carbon footprint. However, novel structural break (SB) and linearity tests conducted enabled us to discover five SB episodes between 2012 and 2020 and non-linearity of the variables, which informed our application of the newly developed non-linear unit root tests with structural breaks. With the new methods, the results indicated stationarity after accommodating the SB and non-linearity. Furthermore, based on Phillips and Shi (2019)'s test, we identified certain bubble episodes in the bitcoin energy and carbon variables between 2013 and 2021. The major drivers of the bubbles in bitcoin energy consumption and carbon footprint are variables relating to the bitcoin and financial markets activities and risks, including the global economic and political risks. The study's conclusion based on the above findings informs several policy implications drawn for energy and environmental management including the encouragement of green investments in cryptocurrency mining and trading.

Examination of nonlinear associations between pulse pressure index and incident prediabetes susceptibility: a 5-year retrospective cohort investigation.

Prediabetes and related complications constitute significant public health burdens globally. As an indicator closely associated with abnormal glucose metabolism and atherosclerosis, the utility of Pulse Pressure Index (PPI) as a prediabetes risk marker has not been explored. We performed a retrospective cohort analysis to investigate this putative association between PPI and prediabetes hazard. Our analysis encompassed 183,517 Chinese adults ≥ 20 years registered within the Rich Healthcare Group 2010-2016. PPI was defined as (systolic blood pressure - diastolic blood pressure)/systolic blood pressure. The relationship between PPI and prediabetes risk was assessed via Cox proportional hazards regression modeling. Non-linearity evaluations applied cubic spline fitting approaches alongside smooth curve analysis. Inflection points of PPI concerning prediabetes hazard were determined using two-piecewise Cox models. During a median follow-up of 3 years (2.17-3.96 years), new-onset prediabetes was documented in 20,607 patients (11.23%). Multivariate regression analysis showed that PPI was an independent risk factor for prediabetes, and the risk of prediabetes increased by 0.6% for every 1% increase in PPI (Hazard Ratio [HR]: 1.006, 95% Confidence Interval [CI] 1.004-1.008, P < 0.001). This association was non-significant for PPI ≤ 37.41% yet exhibited a sharp upsurge when PPI surpassed 37.41% (HR: 1.013, 95% CI 1.005-1.021, P = 0.0029). Our analysis unveils a positive, non-linear association between PPI and future prediabetes risk. Within defined PPI ranges, this relationship is negligible but dramatically elevates beyond identified thresholds.

A decade of thermostatted kinetic theory models for complex active matter living systems.

In the last decade, the thermostatted kinetic theory has been proposed as a general paradigm for the modeling of complex systems of the active matter and, in particular, in biology. Homogeneous and inhomogeneous frameworks of the thermostatted kinetic theory have been employed for modeling phenomena that are the result of interactions among the elements, called active particles, composing the system. Functional subsystems contain heterogeneous active particles that are able to perform the same task, called activity. Active matter living systems usually operate out-of-equilibrium; accordingly, a mathematical thermostat is introduced in order to regulate the fluctuations of the activity of particles. The time evolution of the functional subsystems is obtained by introducing the conservative and the nonconservative interactions which represent activity-transition, natural birth/death, induced proliferation/destruction, and mutation of the active particles. This review paper is divided in two parts: In the first part the review deals with the mathematical frameworks of the thermostatted kinetic theory that can be found in the literature of the last decade and a unified approach is proposed; the second part of the review is devoted to the specific mathematical models derived within the thermostatted kinetic theory presented in the last decade for complex biological systems, such as wound healing diseases, the recognition process and the learning dynamics of the human immune system, the hiding-learning dynamics and the immunoediting process occurring during the cancer-immune system competition. Future research perspectives are discussed from the theoretical and application viewpoints, which suggest the important interplay among the different scholars of the applied sciences and the desire of a multidisciplinary approach or rather a theory for the modeling of every active matter system.