Scale Factor Research Articles

Influences of Outdoor Experiences During Childhood on Time Spent in Nature as an Adult

IntroductionTime spent in nature provides myriad physical and mental health benefits for both adults and children. Despite these benefits, most people spend too little time in nature to realize the maximal effect. Different types of childhood experiences may have differential influence on adult time in nature. This study assessed the influences of different kinds of childhood outdoor experiences on time spent in nature as an adult. The first aim was to utilize 20 childhood nature experience items to construct summative scales. The second aim was to examine the influence of each scale and other factors on adult time in nature. MethodsA 2-factor scale measuring “wild” and “domesticated” childhood nature experiences was developed using principal and confirmatory factor analyses. An on-line study of 2,109 American adults was conducted. Multiple linear regression examined the influences of the two childhood nature experiences scales, attitude and self-efficacy scales, and sex and age covariates, on adult time spent in nature. ResultsSignificant predictors of adult time in nature were wild childhood nature experiences (β = 0.279, < 0.001), positive attitudes about nature (β = 0.12, p < 0.05), negative attitudes about nature (β = -0.23, p < 0.001) and self-efficacy (β = 0.71, p < 0.001). ConclusionsWild childhood nature experiences (e.g., camping, hiking, and fishing) that include skill-building, that are immersive and engaging, and that involve opportunity for social interaction may translate better into adult nature activities. Programs that introduce and support wild experiences may increase lifelong time spent in nature.

Dynamical dark energy from spacetime-symmetry breaking — Late-time behaviour and phantom crossing

We investigate the late-time cosmological dynamics in a simple case of explicit spacetime-symmetry breaking. By expanding in a small symmetry-breaking coefficient we are able to write the Friedmann equations as ΛCDM + dynamical dark energy, which we show contains logarithmic dependence of the scale factor. We find that the dark energy equation of state displays divergencies and phantom behaviour for certain values of the symmetry-breaking coefficient, where the NEC is also broken. We discuss the adiabatic sound speed of dark energy and compare the model to current constraints using the Chevallier–Polarski–Linder parametrisation. Remarkably, although the constraints on the same symmetry-breaking coefficient from e.g. gravitational-wave propagation are orders of magnitude stronger than what we obtain in this paper, we are able to cut those constraints, which are more or less symmetric around zero, in half by showing that same coefficient must be negative (or zero) if one wishes to keep the NEC intact.

Fisheries Impact Pathway: Making Global and Regionalised Impacts on Marine Ecosystem Quality Accessible in Life Cycle Impact Assessment

Fisheries Impact Pathway: Making Global and Regionalised Impacts on Marine Ecosystem Quality Accessible in Life Cycle Impact Assessment

Assessing paddy methane emissions through the identification of rice and winter crop areas using Sentinel-2 imagery in Korea

AbstractThe global efforts on reducing methane (CH4) emissions was emphasized in COP 28 and the potential for improved estimation became feasible through bottom-up data acquisition with advanced remote sensing technology. The objectives of this study were to extract summer rice and winter crop cultivation areas based on satellite images and to incorporate into estimating CH4 emissions in South Korea for the year 2020. Satellite images of Sentinel-1 and Sentinel-2 were acquired from European Space Agency. Rice paddy was classified with backscattering coefficient from Sentinel-1 images, while the normalized difference vegetation index from Sentinel-2 images was used to identify winter cropping field. The equation of IPCC guidelines was used to estimate CH4 emissions by incorporating the areas of rice paddy and winter crop extracted with the respective satellite image. National farming statistics were used to determine the scaling factors for paddy organic matter and water management practices. The estimated areas for rice paddy and winter crop cultivation were 712,237 ha and 117,840 ha, respectively. The rice paddy areas were primarily concentrated in the western regions of the Korean peninsula, whereas winter crop cultivation was predominantly found in southern part of the country. The total amount of CH4 emissions was 6272 Gg CO2 eq./yr when considering rice straw and winter cropping practices into estimation (modified Tier 2 method). This represents a 7% increase compared to the method that considered solely the rice straw incorporation (current Tier 2 method). The CH4 emissions per unit area were also 8.82 tons CO2 eq./ha/yr with the modified Tier 2 method, indicating a 10% greater compared to the current Tier 2 method. Substantial CH4 emissions were primarily concentrated in western regions where extensive rice paddy cultivation occurs, while greater CH4 emissions per unit area were predominantly found in southern regions with substantial winter crop cultivation. The study findings hold importance for improving the accuracy of CH4 emissions estimation by employing bottom-up approach that utilizes satellite imagery to assess rice paddy and winter cropping areas. Further study would be needed to incorporate field-based data on rice crop management practices, such as rice straw and water management, to further refine CH4 emission estimation method.

ASKING IF VACUUM ENERGY allows COMPUTATIONAL “BITS” PRESENT AT START OF COSMOLOGICAL EVOLUTION, and its possible ties into torsion physics

Based on Torsion as given by de Sabbata and Sirvaram, Erice 1990 . The 1990 article claims that Torsion cancels Cosmological vacuum energy. We consider if relic black holes at the start of inflation may allow for the observed cosmological constant. Using the 1990 text if thermal energy is used at start of inflation creates conceptual issues, whereas an energy term based on Corda’s treatment of black holes may provide a solution. i.e. a left over cosmological constant 10^-121 times vacuum energy . Considerations as to how black hole physics may contribute to torsion and the cosmological constant are considered in several numerical cases Also we present entanglement entropy in the early universe with a shrinking scale factor, due to Muller and Lousto , and show that there are consequences due to initial entanged for a time dependent horizon radius in cosmology, with (flat space conditions) for conformal time . This construction preserves a minimum non zero vacuum energy, and in doing so keep the bits, for computational bits cosmological evolution. The bits are ascribed to initial torsion for reasons which we elaborate on in this manuscript

Dynamics of bridges during proof load tests and determination of mass-normalized mode shapes from OMA

Modal shapes derived from Operational Modal Analysis (OMA) lack normalization with respect to masses, hindering direct estimation of effective mass or modal participation factors. The mass-change method is suitable to solve this issue since it proposes an experimental derivation of scaling factors for modes based on OMA results in different load conditions. However, in the case of bridges, the method application is challenging, as significant static masses are required on the deck for OMA in loaded conditions. To address this challenge, trucks can be used as added masses during standard static proof load tests for bridges, making the mass-change method feasible. However, the presence of trucks introduces dynamic coupling effects among bridge and vehicles, potentially complicating the dynamic identification. This paper proposes a methodology to exploit data obtained from OMA on bridges loaded with stationed trucks within the framework of the mass-change method in order to get the modal scaling factors for the mass normalisation of mode shapes and taking into account possible effects of the dynamic coupling between the two systems. To this purpose, the bridge dynamics with added stationed trucks is studied by introducing a finite element model to address the bridge-vehicles dynamic coupling. Then, a simple but effective 2-degree of freedom system is introduced to develop a parametric investigation in a non-dimensional manner in order to provide a practical tool for engineers to account for the bridge-truck dynamic coupling effects. Finally, numerical applications are proposed to derive some conclusions about the effectiveness of the proposed procedure and its suitability in real applications.

Improved multiscale coded dispersion entropy: A novel quadratic-coded health indicator of rolling bearings

Abstract Dispersion entropy (DE) is widely used to quantify the complexity of nonlinear time series. In order to improve the ability to capture fault characteristics, a novel approach called coded dispersion entropy (CDE) has been introduced in recent years. CDE aims to expand the number of possible dispersion patterns and enhance the encoding of similar dispersion patterns. However, the coding method of CDE ignores the amplitude differences between dispersion elements and average elements, resulting in the inaccurate assignment of samples. Additionally, CDE is unable to extract effective information from other time scales. These limitations hinder the ability of CDE to effectively characterize faults. This paper proposes an improved multiscale coded dispersion entropy (IMCDE) to solve these limitations. The method introduces the interval scaling factor "R" and utilizes the sum and difference between the mean element and R as new coding boundaries. This approach addresses the sensitivity issue of the CDE coding mode towards smaller amplitude differences by the reasonable quadratic coding mode. Additionally, a composite coarse-graining process is introduced to rearrange the first coarse-grained point in sequence, resulting in multiple sets of sequences. The average probability of the same dispersion pattern at each scale is calculated to correct the entropy error. The experimental results from two sets of bearing faults demonstrate the effectiveness of this method in extracting critical features associated with faulty bearings. Furthermore, the method showed higher classification accuracy compared to multiscale dispersion entropy (MDE) and multiscale coded dispersion entropy (MCDE). Additionally, it exhibited smaller classification error than MDE and MCDE.

Cosmological Consequence of Varying Speed of Light and Gravitational Constant

&lt;p&gt;The speed of light is taken to be a constant in a vacuum. This forms the basic tool for the principle of General Covariance, which asserts that all laws of Physics should take the same form in all frames of reference. Without putting inflation into consideration, the theory of varying speed of light (VSL) would solve basic problems of cosmology in the early universe. Furthermore, the Gravitational constant G that occurred in the Friedmann Equations may not have been real constants in the early universe but have some variation with the universe scale factor. Cosmological models with varying physical constants have been of interest in recent years with few works in the literature. A cosmological solution obtained by incorporating variable speed of light and gravitational constant gives a cosmic model which is free from the initial Big Bang singularity and horizon problem. It is also observed here that the early universe was dominated by dark matter, however, as the scale factor increases, the dark energy become dominant.&lt;/p&gt;

Conserved spin operator of Dirac’s theory in spatially flat FLRW space-times

New conserved spin and orbital angular momentum operators of Dirac’s theory on spatially flat FLRW space-times are proposed generalizing thus the recent results concerning the role of Pryce’s spin operator in the flat case (Cotăescu in Eur Phys J C, 82, 1073, 2022). These operators split the conserved total angular momentum generating the new spin and orbital symmetries that form the rotations of the isometry groups. The new spin operator is defined and studied in active mode with the help of a suitable spectral representation giving its Fourier transform. Moreover, in the same manner is defined the operator of the fermion polarization. The orbital angular momentum is derived in passive mode using a new method, inspired by Wigner’s theory of induced representations, but working properly only for global rotations. In this approach the quantization is performed finding that the one-particle spin and orbital angular momentum operators have the same form in any FLRW spacetime regardless their concrete geometries given by various scale factors.

Abstract PO4-11-12: Patient Reported Outcomes from a multi-site, prospective Pivotal study evaluating pegulicianine fluorescence guided surgery (pFGS) for breast cancer lumpectomy procedures using the Lumicell Direct Visualization System (DVS)

Abstract Background: In pegulicianine fluorescence guided surgery (pFGS), a standard of care lumpectomy procedure is performed, and additional tissue is taken from cavity walls at sites of high pFGS signal. This approach been shown to reduce 2nd surgeries and remove additional tumor left by standard surgery, but may remove more tissue, potentially worsening cosmetic outcomes. Patient breast satisfaction surveys were used to assess cosmesis after pFGS. Methods: A prospective Pivotal trial of pFGS in women undergoing lumpectomy surgery for stage 0-III breast cancer was conducted at 14 US sites (NCT03686215). We assessed the safety and efficacy of the Lumicell DVS in identifying and removing residual cancer from the lumpectomy cavity in real time. Patient Reported Outcome Measures (PROM) data was collected as an exploratory endpoint. The BREAST-Q, a validated tool that measures patient perspectives after different breast procedures, was used to collect PROM data. An 11-question BREAST-Q survey was used to measure patients’ breast satisfaction at baseline (pre-surgery) and at multiple timepoints through 6-months post lumpectomy. Descriptive statistics of participating patients’ responses were collected and analyzed. Survey results were analyzed by the distribution of patient ratings for each question and the change in the distribution of ratings over time, with comparison of baseline to post-lumpectomy. Comparison of patient satisfaction with or without additional pFGS-directed tissue removal was performed with Item Response Theory assuming all items equally discriminative of responding patients. For each timeframe, responses to BREAST-Q items were used to create a response score for each patient. Scaled factor scores (0-100) were compared between groups with and without additional tissue removed during pFGS. Results: Of the 357 patients evaluated for efficacy in the primary Pivotal study analysis, 255 patients agreed to participate in the PROM surveys (71%). Approximately 60% of the participating respondents completed a pre- and initial post-lumpectomy survey while only 34% of the participating patients completed a pre- and 6-month post-lumpectomy survey. Most patients responded either “Very Satisfied” or “Somewhat Satisfied” across all surveyed timeframes. No significant difference in patient breast satisfaction was found at any time point between the groups with and without additional pFGS-guided shaves removed (p &amp;gt;0.05). There were 4 patients with scores of 3 or higher pre-surgery but 2 or lower post-surgery. Among these, 1 had no pFGS-guided shaves taken. The remaining 3 had had pFGS-guided shaves taken, but 2 required a second lumpectomy surgery and 1 underwent mastectomy, these additional surgeries likely accounting for decreased cosmetic outcomes. Discussion: Patient perspective of breast satisfaction was not decreased by the amount of extra tissue removed by pFGS. These data suggest that pFGS using the Lumicell DVS does not significantly decrease breast cosmesis. Three of 4 patients with decreased satisfaction had 2nd surgeries, confirming the importance of finding approaches to decrease 2nd surgeries. This data was collected during the COVID-19 pandemic, which may have adversely impacted the compliance rate of survey completion. Studies in larger cohorts with longer follow up are required to better assess the relative impact of 2nd surgeries, radiation, and systemic therapy on breast satisfaction PROM scores after lumpectomy. Citation Format: Kelly Hunt, Irene Wapnir, E Shelley Hwang, David Carr, Peter Blumencranz, Kate Smith, Manna Chang, Jorge Ferrer, Barbara Smith. Patient Reported Outcomes from a multi-site, prospective Pivotal study evaluating pegulicianine fluorescence guided surgery (pFGS) for breast cancer lumpectomy procedures using the Lumicell Direct Visualization System (DVS) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-11-12.

Development of a Universal Adaptive Control Algorithm for an Unknown MIMO System Using Recursive Least Squares and Parameter Self-Tuning

Development of a Universal Adaptive Control Algorithm for an Unknown MIMO System Using Recursive Least Squares and Parameter Self-Tuning

Individual Wave Overtopping Volumes On Mound Breakwaters

Mound breakwaters are widely used to protect harbors from wave attack. Wave overtopping is a key parameter on the breakwater design, since it affects the hydraulic stability, the port operativity and also generates risks to the facilities, vehicles and pedestrians. The estimation of the mean wave overtopping rate, q[m3/s/m], has been extensively analyzed in the literature (see EurOtop, 2018 and Van Gent et al., 2007). However, the maximum individual wave overtopping volume, Vmax [m3/m], can be much larger than q[m3/s/m] and it is a better variable to evaluate the direct hazards. The prediction tools of q and Vmax are mainly based on laboratory tests, where q is registered much more easily than individual wave overtopping volumes. However, few of these studies detail the methodology to identify the number of overtopping waves and the associated individual wave overtopping volumes. The estimation of Vmax is usually made in literature (see Molines et al., 2019 and EurOtop, 2018) using a 2-parameter Weibull distribution (shape and scale factor) fitted with utility functions which consider the 10%, 30% or 50% of the highest individual wave overtopping volumes. The shape factor (b) is fitted with the laboratory measurements and the scale factor (A) is obtained by forcing the mean value of the Weibull distribution to be equal to the registered mean individual wave overtopping. In this study, a fully automatic detection methodology of the individual wave overtopping waves and volumes is developed using 2D physical tests. The performance of the 2-parameter Weibull and Exponential distributions to estimate Vmax is analyzed here with four utility functions to weight the data, f(u). The full findings of this study are available in Molines et al. (2019).

Adaptive Sampling Offspring Generation Strategy for Multi-objective Optimization

A covariance adaptive sampling offspring generation strategy (CASS) based on fuzzy clustering is proposed, and a multi-objective distribution estimation algorithm (MEDCA) based on this strategy is introduced. The GK-FCM clustering partitioning strategy is designed to build a Gaussian model for each individual, collectively approximating the manifold of the Pareto solution set and generating offspring through sampling. The introduction of an individual’s survival generation adapts the individual’s preference for exploration and exploitation. This is achieved by incorporating it as a scaling factor of the covariance matrix in the sampling model, in order to satisfy the individual’s preferences for development and exploration in different evolutionary stages. This method significantly improves the performance of MEDCA in solving complex multi-objective optimization problems through covariance matrix adaptation sampling strategy and scaling factor adaptation strategy. The experimental results demonstrate the advantages of MEDCA in the application of offspring generation strategies during model sampling.

A caregivers' perspective on social reintegration and stigma of childhood cancer survivors in Kenya.

Childhood cancer survivors' social reintegration may be hampered in low and middle-income countries. The nature and extent of social challenges and prejudices that survivors encounter in such settings are largely unknown. This study explores caregivers' perspectives on social reintegration and stigmatization of Kenyan childhood cancer survivors. Caretakers of childhood cancer survivors (<18years) were interviewed using mixed-methods questionnaires during home or clinic visits between 2021 and 2022. Stigma was assessed with an adjusted Social Impact Scale and risk factors were investigated. Caretakers of 54 survivors (median age 11years) were interviewed. Families' income (93%) decreased since start of treatment. Caretakers (44%) often lost their jobs. Financial struggles (88%) were a burden that provoked conflicts within communities (31%). School fees for siblings became unaffordable (52%). Families received negative responses (26%) and were left or avoided (13%) by community members after cancer disclosure. Survivors and families were discriminated against because the child was perceived fragile, and cancer was considered fatal, contagious, or witchcraft. Survivors repeated school levels (58%) and were excluded from school activities (19%) or bullied (13%). Performance limitations of daily activities (p=0.019), male sex (p=0.032), solid tumors (p=0.056) and a short time since treatment completion (p=0.047) were associated with increased stigma. Caretakers recommended educational programs in schools and communities to raise awareness about cancer treatment and curability. Childhood cancer survivors and their families experienced difficulties with re-entry and stigmatization in society. Increasing cancer and survivorship awareness in schools and communities should facilitate social reintegration and prevent stigmatization.

Quantification of large-spatial scale and in-stream factors affecting the structure of benthic macroinvertebrate communities in mountain streams

Habitat diversity plays a crucial role in shaping the structure and distribution of benthic macroinvertebrate communities. However, few studies have investigated the concurrent effects of such drivers operating at different spatial scales in mountain streams. Here, we assessed which environmental factors at different spatial scales, related to stream/river type and substrate, influence the diversity of benthic macroinvertebrate assemblages in mountain streams and rivers. Within the framework of the aquatic investigations of the Biodiversity Monitoring South Tyrol (BMS) – a newly-established, regional-based, long-term biodiversity monitoring program – benthic macroinvertebrates and a set of environmental factors describing water quality, stream/river hydromorphology and in-stream habitat characteristics were collected and analysed. The variation in total density, taxonomic richness, Shannon evenness and % Ephemeroptera–Plecoptera–Trichoptera taxa of stream benthic macroinvertebrates was assessed at multi-scale habitat levels, in 48 sampling sites across the mountainous region of the Autonomous Province of Bolzano/Bozen (Italy). The effects of stream/river type, substrates and different environmental factors on community composition of benthic macroinvertebrates were quantified, using a stepfoward Redundancy Analysis (RDA) and generalized additive models (GAMs). In addition, we performed an Indicator Value analysis to detect taxa that were significantly associated with a specific substrate and/or stream/river type. Overall, we observed significant differences in benthic biological metrics among both stream/river and substrate types. We also found at least one indicator taxa for each stream/river type, with environmental factors acting at reach and large-spatial scale – temperature, stream channel stability, elevation – being the key drivers in shaping macroinvertebrate distribution patterns in the analysed mountain rivers. While significant differences in macroinvertebrate community structures were found among substrates, the influence of stream/river type conditions was particularly evident. Apart from ranking environmental variables worth including in a long-term aquatic biodiversity monitoring program in mountain areas, our study provides a baseline for practical applications. For instance, depending on the desired outcome of habitat heterogeneity restoration, it can suggest the optimal scale (landscape vs. reach vs. patch) for prioritizing in-field interventions.

The Temperature of the Deep Ocean Is a Robust Proxy for Global Mean Surface Temperature During the Cenozoic

AbstractReconstructing global mean surface temperature (GMST) is one of the key contributions that paleoclimate science can make in addressing societally relevant questions and is required to determine equilibrium climate sensitivity (ECS). GMST has been derived from the temperature of the deep ocean (Td), with previous work suggesting a simple Td‐GMST scaling factor of 1 prior to the Pliocene. However, this factor lacks a robust mechanistic basis, and indeed, is intuitively difficult to envisage given that polar amplification is a ubiquitous feature of past warm climate states and deep water overwhelmingly forms at high latitudes. Here, we interrogate whether and crucially, why, this relationship exists using a suite of curated data compilations and two sets of paleoclimate model simulations. We show that models and data are in full agreement that a 1:1 relationship is a good approximation. Taken together, the two sets of climate models suggest that (a) a lower sensitivity of SST in the season of deep water formation than high latitude mean annual SST in response to climate forcing, and moreover (b) a greater degree of land versus ocean surface warming are the two processes that act to counterbalance a possible polar amplification‐derived bias on Td‐derived GMST. Using this knowledge, we provide a new Cenozoic record of GMST. Our estimates are substantially warmer than similar previous efforts for much of the Paleogene and are thus consistent with a substantially higher‐than‐modern ECS during deep‐time high CO2 climate states.

Microseismic Observation Enabled by High-Sensitivity Micromechanical Interferometers

High-sensitivity accelerometry has historically been employed to explore Earth sciences and advance resource-related industries, such as petroleum exploitation. The devices capable of such measurements, however, traditionally involve precise mechanical structures and consequent large dimensions. In this work, combined by micromechanical systems and grating-assisted interferometry, a closed-loop optical accelerometer with nano-g (ng) sensitivity is developed for microseismic observations. In order to lower the intrinsic thermal noise, a modified 8.84 Hz micromechanical spring-mass oscillator is designed and fabricated. Additionally, an active control system is equipped to stabilize the device temperature and thus enhance the low-frequency stability. Field tests demonstrate that the prototype has achieved a scale factor of 1195 V/g, along with a dynamic range of 1.12 mg and a bandwidth of about 7 Hz. Further, under the controlled 45 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 0.01 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> C temperature condition, complete terrestrial microsesimic peaks from 0.1 Hz to 3 Hz are tracked. After calibration by a reference seismometer, the device self-noise is determined as 2 ng/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sqrt{Hz}$</tex-math></inline-formula> from 0.2 Hz to 4 Hz with a bias stability of 7.9 ng. The transducer and control circuits are both packaged within a 13.6 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\times 13.6\times$</tex-math></inline-formula> 12.8 cm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{3}$</tex-math></inline-formula> insulated enclosure, making it advantageous for outdoor observations.

Spectral neural approximations for models of transcriptional dynamics

The advent of high-throughput transcriptomics provides an opportunity to advance mechanistic understanding of transcriptional processes and their connections to cellular function at an unprecedented, genome-wide scale. These transcriptional systems, which involve discrete stochastic events, are naturally modeled using chemical master equations (CMEs), which can be solved for probability distributions to fit biophysical rates that govern system dynamics. While CME models have been used as standards in fluorescence transcriptomics for decades to analyze single-species RNA distributions, there are often no closed-form solutions to CMEs that model multiple species, such as nascent and mature RNA transcript counts. This has prevented the application of standard likelihood-based statistical methods for analyzing high-throughput, multi-species transcriptomic datasets using biophysical models. Inspired by recent work in machine learning to learn solutions to complex dynamical systems, we leverage neural networks and statistical understanding of system distributions to produce accurate approximations to a steady-state bivariate distribution for a model of the RNA life cycle that includes nascent and mature molecules. The steady-state distribution to this simple model has no closed-form solution and requires intensive numerical solving techniques: our approach reduces likelihood evaluation time by several orders of magnitude. We demonstrate two approaches, whereby solutions are approximated by 1) learning the weights of kernel distributions with constrained parameters or 2) learning both weights and scaling factors for parameters of kernel distributions. We show that our strategies, denoted by kernel weight regression and parameter-scaled kernel weight regression, respectively, enable broad exploration of parameter space and can be used in existing likelihood frameworks to infer transcriptional burst sizes, RNA splicing rates, and mRNA degradation rates from experimental transcriptomic data.

Predict the prevalence and incidence of Parkinson's disease using fractal interpolation-LSTM model.

The investigation of the prediction of disease population is a noticeable exploration topic in the field of sciences. As a type of neurological disease, the incidence and prevalence of Parkinson's disease are still difficult to accurately study. In this paper, a method is proposed to forecast the number of incident cases (NumIn), incidence rate (InRa), the number of prevalent cases (NumPr), and prevalence rate (PrRa) of Parkinson's disease in ten countries selected. Using past data on the incidence rate, the number of prevalent cases, and the prevalence rate from 1990 to 2019, three types of fractal interpolations with different fractal dimensions are constructed for reconstructing the past data, where the vertical scaling factors are determined by the method proposed in this article. Then, the Long Short-Term Memory (LSTM) model is employed to forecast the values of NumIn, InRa, NumPr, and PrRa with Parkinson's disease in 2020. Meanwhile, the autoregressive integrated moving average model is used to predict the values compared with the LSTM model. The evaluation metrics employed for error calculation include the root mean square error and the coefficient of determination (R2). According to the proposed optimal criteria, the best predicted results are the average of three types of prediction values based on the LSTM model by analyzing and comparing eight predicted results.

Self-calibrated atom-interferometer gyroscope by modulating atomic velocities.

Atom-interferometer gyroscopes have attracted much attention for their long-term stability and extremely low drift. For such high-precision instruments, self-calibration to achieve an absolute rotation measurement is critical. In this work, we propose and demonstrate the self-calibration of an atom-interferometer gyroscope. This calibration is realized by using the detuning of the laser frequency to control the atomic velocity, thus modulating the scale factor of the gyroscope. The modulation determines the order and the initial phase of the interference stripe, thus eliminating the ambiguity caused by the periodicity of the interferometric signal. This self-calibration method is validated through a measurement of the Earth's rotation rate, and a relative uncertainty of 162 ppm is achieved. Long-term stable and self-calibrated atom-interferometer gyroscopes have important applications in the fields of fundamental physics, geophysics, and long-time navigation.