Global Spectrum Research Articles

Population-based prevalence and mutational landscape of von Willebrand disease using large-scale genetic databases

Von Willebrand disease (VWD) is a common bleeding disorder caused by mutations in the von Willebrand factor gene (VWF). The true global prevalence of VWD has not been accurately established. We estimated the worldwide and within-population prevalence of inherited VWD by analyzing exome and genome data of 141,456 individuals gathered by the genome Aggregation Database (gnomAD). We also extended our data deepening by mining the main databases containing VWF variants i.e., the Leiden Open Variation Database (LOVD) and the Human Gene Mutation Database (HGMD) with the goal to explore the global mutational spectrum of VWD. A total of 4,313 VWF variants were identified in the gnomAD population, of which 505 were predicted to be pathogenic or already reported to be associated with VWD. Among the 282,912 alleles analyzed, 31,785 were affected by the aforementioned variants. The global prevalence of dominant VWD in 1000 individuals was established to be 74 for type 1, 3 for 2A, 3 for 2B and 6 for 2M. The global prevalences for recessive VWD forms (type 2N and type 3) were 0.31 and 0.7 in 1000 individuals, respectively. This comprehensive analysis provided a global mutational landscape of VWF by means of 927 already reported variants in the HGMD and LOVD datasets and 287 novel pathogenic variants identified in the gnomAD. Our results reveal that there is a considerably higher than expected prevalence of putative disease alleles and variants associated with VWD and suggest that a large number of VWD patients are undiagnosed.

Wavelet analysis of combustion characteristics and numerical validation of CI engine with novel water emulsified fuels

This study examined the dependability of running a diesel engine on a novel water-emulsified diesel fuel with prolonged phase stability investigation. In order to develop a stable water emulsified fuel, experiments were conducted to standardize the composition ratios. The water-in-diesel emulsions were prepared using the surfactant named “Propylene Glycol Monostearate” along with Tween80 and Octanol was also chosen as co-emulsifier in order to enhance the phase stability. Using water-emulsified diesel fuel with the designations E0, E10, E20, E30, E40, and E50, the combustion stability using statistical and wavelet method were assessed on a 1-cylinder, 4-stroke CI engine. Even after being prepared for 100 days at room temperature, all water-in-diesel emulsions were discovered to be stable and homogenous. Moreover, to validate the combustion metrices such as in-cylinder pressure and HRR, a MATLAB-based single-zone thermodynamic model was developed. The combustion stability analyses using statistical method showed that the COV was found below 5 % at all loading conditions except E0 emulsion fuel whereas, the wavelet approach revealed that the E0 emulsion fuel's wavelet power spectrum (WPS) result showed a major intensity variance at high frequencies and lower frequencies for other emulsions and diesel 25 and 50 % loading condition. The analysis of the Global Wavelet Spectrum (GWS) results revealed that E0 exhibited higher peak power compared to diesel and other test fuels at 25 % and 50 % load conditions. The WPS and GWS results for E30 and E50 emulsion showed a similar trend as diesel fuel at all tested loading conditions implying a stable combustion with water-emulsified diesel. On the other hand, the prediction model anticipated the numerical values and was computed to be in strong conformity with the outcomes of the experiment. All numerical values lay within 95 % of the prediction band in regression analysis with an R2 value of 99.8 % and standard error (S = 0622) suggesting strong significant data and a better thermodynamic simulation model. In conclusion, PGM + Tween 80 could be used as a potential emulsifier to prepare stable water-in-diesel emulsion and Wavelet analysis proves to be a valuable tool for evaluating the cyclic variation observed in engine combustion. Additionally, the thermodynamic model is capable of providing accurate predictions of the engine combustion parameters.

Divergent Geochemical Pathways of Carbonate Aquifer Evolution in a Classic Karst Terrain: (1) Polygenetic Cave Development Identified Using Longitudinal Groundwater Geochemistry

Carbonic acid and sulfuric acid speleogenesis describe a dichotomy between epigenetic and hypogenetic caves and carbon and sulfur cycling in karst, but do not acknowledge the global spectrum of cave formation. This paper, part one of a two-part investigation, tests and revises speleogenetic models from a classic karst landscape using dissolved ion concentrations δ13CDIC, and δ34S in water samples collected at four sites across the Bluespring and Lost River karst basins in the Mitchell Plateau, Indiana, USA. Analyses revealed elevated sulfur in both karst basins but differently sourced; H2S (δ34S = −14.2‰) evolved from petroleum seeps in Bluespring Caverns accounted for up to 61% of sulfur in the cave stream, while evaporite beds (δ34S = [+14.50‰, +17.91‰]) of the St. Louis Limestone contributed up to 100% of sulfur at Orangeville Rise, a terminal spring of the Lost River karst basin. These results have implications for carbon–sulfur cycle linkages, particularly the potential acceleration of carbon flux from sulfuric acid dissolution in otherwise epigenetic settings. We suggest a new paradigm for speleogenesis in the North American midcontinent—speleogenesis in the Mitchell Plateau and similar settings is not epigenetic or hypogenetic, but instead polygenetic with competing chemical processes varying across space and time.

Assessment of the global applicability of three leading indices that characterize the spectral distribution of solar irradiance impacting various photovoltaic technologies

At each instant, the actual solar irradiance has a specific spectral distribution that most generally differs substantially from the standardized reference conditions under which photovoltaic (PV) cells are rated. To help reduce the dimensionality of the calculations needed to quantify the spectral effects on PV cells, various spectral indices have been introduced in the literature to simply characterize the incident spectral distribution with a single number. In previous studies, diverging conclusions have been reached about whether or not a single number can effectively represent a specific spectral distribution. This disagreement needs to be resolved before the usage of spectral indices can be considered best practice. To that effect, this study proposes a novel modeling approach. Here, three spectral indices (Average Photon Energy, APE; Blue Fraction, BF; and Useful Fraction, UF) are critically evaluated and compared using the SMARTS radiative transfer model and a large database of atmospheric inputs that are representative of the vast diversity of possible conditions worldwide, thus avoiding the rarity and limitations of costly experimental measurements. A total of 28,260 pairs of direct normal and global horizontal spectra are obtained, from which the three indices are calculated over six different wavebands that characterize different PV technologies. The key variables that have a significant impact on the indices are found to be: air mass, aerosol optical depth, Ångström exponent, and precipitable water. Using a variety of tests to evaluate the behavior of the three indices relatively to the reference direct and global spectra, results show that UF is prone to anomalous variations under a variety of circumstances. APE and BF behave similarly and reliably, but APE is found more responsive to even small changes in atmospheric conditions, and is thus preferable. A critical finding is that none of the indices can be considered bijective because compensations between red-shifting and blue-shifting atmospheric processes often result in different spectral distributions having the same index value.

Estimating Ejecta Mass Ratios in Kepler’s Supernova Remnant: Global X-Ray Spectral Analysis Including Suzaku Systematics and Emitting Volume Uncertainties

The exact origins of many Type Ia supernovae—progenitor scenarios and explosive mechanisms—remain uncertain. In this work, we analyze the global Suzaku X-ray spectrum of Kepler’s supernova remnant (SNR) in order to constrain the mass ratios of various ejecta species synthesized during explosion. Critically, we account for the Suzaku telescope effective-area calibration uncertainties of 5%–20% by generating 100 mock effective-area curves and using Markov Chain Monte Carlo–based spectral fitting to produce 100 sets of best-fit parameter values. Additionally, we characterize the uncertainties from assumptions made about the emitting volumes of each model plasma component and find that these uncertainties can be the dominant source of error. We then compare our calculated mass ratios to previous observational studies of Kepler’s SNR and to the predictions of Type Ia simulations. Our mass ratio estimates require a 90% attenuated 12C+16O reaction rate and are potentially consistent with both near- and sub-M Ch progenitors, but are inconsistent with the dynamically stable double-detonation origin scenario and only marginally consistent with the dynamically unstable dynamically driven double-degenerate double-detonation (D6) scenario.

Climate Change and Human Security in Zimbabwe

Across the global spectrum, climate change has proven to be problematic with no definitive way of solving it. At the same time, its effects on humanity have been catastrophic and detrimental, undermining all facets of human security such as food security, personal security, health security, environmental security, economic security, political security and community security. Zimbabwe has not been spared, as the scale and magnitude of climate change have proven to be more vicious and malignant owing it to a myriad of quagmires which among others include but are not limited to weak preparedness and emergence management systems, insufficient budget, lack of political will and poor community education campaigns. Using mixed method, the research examines the effects of climate change and human security in Zimbabwe with the primary purpose of coming up with organic and actionable policy alternatives that can be used to enhance human security. The paper concludes that, climate change undermines human security and there is need for urgent intervention from the government to invest in climate adaptation and mitigatory measures.

Responses of Total Electron Content to Solar Flares over Low and Mid-Latitude Regions during Sun Halo Day

The responses of total electron content (TEC) to solar flares over low- and mid-latitude regions during the sun halo days were investigated. The research is based on GPS data obtained from Bangalore (13.02117°N, 77.57038°E) on May 24, 2021; Cape Town (-33.918861°N, 18.423300°E) on October 26, 2020; and North Dakota (46.55756°N, -96.472300°E) on December 27, 2021, during the solar halo days. The results of this study demonstrate that the values of TEC increased at Bangalore and Cape Town stations during solar halo days as compared to other days. However, over the North Dakota station, TEC during the sun halo day was greater than that on the days before and after the halo day from around 19:00 UT to 23:59 UT hours. During the sun halo over Bangalore and Cape Town stations, positive relative changes in TEC prevail, suggesting that the action of the interplanetary electric field, the prompt penetration electric field, and the disturbance dynamo electric field lead to higher TEC values. However, during the sun halo over North Dakota station, negative relative changes in TEC prevail, which might be related to the consequence that low solar activity with no earth’s field disturbances (a positive Dst) leads to lower ionospheric TEC values. Stations that have greater relative changes in TEC have shown greater power spectrum and global wave spectrum energy. Cape Town has a greater relative change in TEC, a greater power spectrum, and a larger global wave spectrum than Bangalore and North Dakota stations. The values of TEC over three stations are different due to the latitudinal and longitudinal differences in addition to the universal time effects. Finally, solar flares have a major influence on ionosphere electrodynamics, and the upward drift velocity of ionospheres at the low latitude station is more strongly influenced by solar flares due to the effects of the ExB drifts, which induce TEC disturbances during the halo days over the suggested stations.

NuSTAR Observations of Abell 665 and 2146: Constraints on Nonthermal Emission

Observations from past missions such as RXTE and Beppo-SAX suggested the presence of inverse Compton (IC) scattering at hard X-ray energies within the intracluster medium of some massive galaxy clusters. In subsequent years, observations by, e.g., Suzaku, and now NuSTAR, have not been able to confirm these detections. We report on NuSTAR hard X-ray searches for IC emission in two massive galaxy clusters, A665 and A2146. To constrain the global IC flux in these two clusters, we fit global NuSTAR spectra with three models: single (1T) and two-temperature (2T) models, and a 1T plus power-law component (T+IC). The temperature components are meant to characterize the thermal ICM emission, while the power law represents the IC emission. We find that the 3–30 keV A665 and 3–20 keV A2146 spectra are best described by thermal emission alone, with average global temperatures of kT = (9.15 ± 0.1) keV for A665 and kT = (8.29 ± 0.1) keV for A 2146. We constrain the IC flux to F NT <0.60 × 10−12 erg s−1 cm−2 and F NT < 0.85 × 10−12 erg s−1 cm−2 (20–80 keV) for A665 and A2146, respectively both at the 90% confidence level. When we couple the IC flux limits with 1.4 GHz diffuse radio data from the VLA, we set lower limits on the average magnetic field strengths of >0.14 μG and >0.011 μG for A665 and A2146, respectively.

Perrotta Hypersexuality Questionnaire (PeHy-Q): Development, regulation and validation of a new psychometric instrument for the diagnosis of hypersexuality

Introduction: The clinically relevant condition of hypersexuality is to date nebulous in its definition, and although it is understood as a psychological and behavioural alteration as a result of which sexually motivated stimuli are inappropriately sought and often experienced in a way that is not entirely satisfactory, it is unclear whether it is an obsessive disorder or is a trait of a more complex personality disorder or a consequence arising from a medical condition, whether primary or secondary. Methods: Using the Perrotta Hypersexuality Global Spectrum of Gradation (PH-GSS) as a model, the clinical and control population was selected to validate a new psychometric test, then compared with the Sexual Addiction Screening Test (SAST-R, v. 2.0). Results: Statistical analysis showed that the new psychometric test has a well-defined and stable construct (R = 0.975; p = 0.000), the variables are well represented (R = 0.999; p = 0.000) and it is positively correlated with the other constructs already validated (R = 0.951; p = 0.000). Conclusions: Perrotta Hypersexuality Questionnaire (PeHy-Q) is a valid, efficient, and effective psychometric tool to diagnose the clinically relevant condition of hypersexuality to improve the structural and functional framing of the patient and the appropriate therapy to pursue.

Resting-state networks representation of the global phenomena.

Resting-state functional magnetic resonance imaging (rsfMRI) has been widely applied to investigate spontaneous neural activity, often based on its macroscopic organization that is termed resting-state networks (RSNs). Although the neurophysiological mechanisms underlying the RSN organization remain largely unknown, accumulating evidence points to a substantial contribution from the global signals to their structured synchronization. This study further explored the phenomenon by taking advantage of the inter- and intra-subject variations of the time delay and correlation coefficient of the signal timeseries in each region using the global mean signal as the reference signal. Consistent with the hypothesis based on the empirical and theoretical findings, the time lag and correlation, which have consistently been proven to represent local hemodynamic status, were shown to organize networks equivalent to RSNs. The results not only provide further evidence that the local hemodynamic status could be the direct source of the RSNs' spatial patterns but also explain how the regional variations in the hemodynamics, combined with the changes in the global events' power spectrum, lead to the observations. While the findings pose challenges to interpretations of rsfMRI studies, they further support the view that rsfMRI can offer detailed information related to global neurophysiological phenomena as well as local hemodynamics that would have great potential as biomarkers.

Spectral–Temporal Transformer for Hyperspectral Image Change Detection

Deep-Learning-based (DL-based) approaches have achieved remarkable performance in hyperspectral image (HSI) change detection (CD). Convolutional Neural Networks (CNNs) are often employed to capture fine spatial features, but they do not effectively exploit the spectral sequence information. Furthermore, existing Siamese-based networks ignore the interaction of change information during feature extraction. To address this issue, we propose a novel architecture, the Spectral–Temporal Transformer (STT), which processes the HSI CD task from a completely sequential perspective. The STT concatenates feature embeddings in spectral order, establishing a global spectrum–time-receptive field that can learn different representative features between two bands regardless of spectral or temporal distance, thereby strengthening the learning of temporal change information. Via the multi-head self-attention mechanism, the STT is capable of capturing spectral–temporal features that are weighted and enriched with discriminative sequence information, such as inter-spectral correlations, variations, and time dependency. We conducted experiments on three HSI datasets, demonstrating the competitive performance of our proposed method. Specifically, the overall accuracy of the STT outperforms the second-best method by 0.08%, 0.68%, and 0.99% on the Farmland, Hermiston, and River datasets, respectively.

Mutational Spectrum and Genotype-phenotype Correlations in Neurofibromatosis Type 1 Patients from North Macedonia: Identification of Ten Novel NF1 Pathogenic Variants.

Neurofibromatosis type 1 (NF1) is an autosomal dominant neurocutaneous disorder, characterized by multiple café-au-lait macules, axillary and inguinal freckling, tumors of the nervous system, and iris hamartomas. More than 3,100 different pathogenic variants have been reported in the NF1 gene, including missense, nonsense, frameshift, in-frame, splicing, and large deletions. To determine the NF1 mutational spectrum in patients with NF1 from the Republic of North Macedonia. A cohort study. Molecular analyses included reverse transcription and cDNA sequencing of the NF1 gene and next-generation sequencing using the TruSight Cancer panel, along with the multiple ligation probe amplification method to detect single nucleotide variants and copy number variations. Direct DNA sequencing was also used for the family member analysis. Our 9-year study of patients suspected of having NF1 in the Republic of North Macedonia encompassed molecular characterization of 30 cases of the disease. We identified 28 unique pathogenic NF1 variants (NM_001042492.3), of which ten were novel: c.208delA; c.341_364del; c.1480_1481delTT; c.2325+1G>C; c.2495_2496dupAC; c.2533_2541del; c.4517delC; c.5844C>G; c.6971delA; c.7605_7606delGAinsAT. In addition to the variant spectrum analysis, our research revealed two positive genotype-phenotype correlations. One between the clinical manifestation of cognitive impairment and gross deletions in the NF1 gene, and the other between cognitive impairment and truncating variants located in the RAS-GAP functional domain. This is the first study of NF1 patients in the Republic of North Macedonia, and it contributes ten novel variants to the global spectrum of pathogenic NF1 variants. It also corroborates the crucial importance of NF1 genetic testing for a prompt and precise diagnosis, particularly in younger patients.

Leaf-level coordination principles propagate to the ecosystem scale

Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories – the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis – are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

Performance investigation of piezoelectric-mechanical electromagnetic compound vibration energy harvester for electric tractor

The electric tractor belongs to off-road vehicle and often travels on the rugged ground generally featured as the Class-D Road which leads to large vibration. Currently, this kind of vibration energy has not been effectively recovered and utilized which results in energy waste. To address this problem, a novel piezoelectric-mechanical electromagnetic compound vibration energy harvester (P-MECVEH) was proposed. Then, the 10 DOF nonlinear dynamic model of the P-MECVEH was established, and its energy nonlinear dynamic characteristics were revealed numerically through the global bifurcation, phase orbit, Poincaré map and FFT spectrum. The results showed that the energy output response of the P-MECVEH presented a high-energy period-2 state within the ranges of the excitation frequency f∈ [2.475, 2.850 Hz] and amplitude Am∈ [0.00644, 0.01000 m]. Finally, the reliability of the established dynamic model was verified through comparative analysis between the prototype experimental and theoretical results, and it was shown that the prototype generated a maximum output voltage of 38 V and a peak power of 14.44 W at a load resistance of 100 Ω under the excitation frequency of 2.42 Hz and amplitude of 0.002 m, which indicates that the P-MECVEH has the potential in vibration energy recovery and utilization for electric tractors.

Surface Properties of Global Land Surface Microwave Emissivity Derived from FY-3D/MWRI Measurements

Land surface microwave emissivity is crucial to the accurate retrieval of surface and atmospheric parameters and the assimilation of microwave data into numerical models over land. The microwave radiation imager (MWRI) sensors aboard on Chinese FengYun-3 (FY-3) series satellites provide valuable measurements for the derivation of global microwave physical parameters. In this study, an approximated microwave radiation transfer equation was used to estimate land surface emissivity from MWRI by using brightness temperature observations along with corresponding land and atmospheric properties obtained from ERA-Interim reanalysis data. Surface microwave emissivity at the 10.65, 18.7, 23.8, 36.5, and 89 GHz vertical and horizontal polarizations was derived. Then, the global spatial distribution and spectrum characteristics of emissivity over different land cover types were investigated. The seasonal variations of emissivity for different surface properties were presented. Furthermore, the error source was also discussed in our emissivity derivation. The results showed that the estimated emissivity was able to capture the major large-scale features and contains a wealth of information regarding soil moisture and vegetation density. The emissivity increased with the increase in frequency. The smaller surface roughness and increased scattering effect may result in low emissivity. Desert regions showed high emissivity microwave polarization difference index (MPDI) values, which suggested the high contrast between vertical and horizontal microwave signals in this region. The emissivity of the deciduous needleleaf forest in summer was almost the greatest among different land cover types. There was a sharp decrease in the emissivity at 89 GHz in the winter, possibly due to the influence of deciduous leaves and snowfall. The land surface temperature, the radio-frequency interference, and the high-frequency channel under cloudy conditions may be the main error sources in this retrieval. This work showed the potential capabilities of providing continuous and comprehensive global surface microwave emissivity from FY-3 series satellites for a better understanding of its spatiotemporal variability and underlying processes.

Emission spectra of fullerenes: Computational evidence for blackbody-like radiation due to structural diversity and electronic similarity

The spectral emission of hot ${\mathrm{C}}_{60}$ has been experimentally shown to be broad and continuous, in apparent contradiction with the discrete and narrow absorption spectrum associated with the high symmetry of buckminsterfullerene. In the present work we computationally model the emission spectrum of isolated carbon clusters, assuming a broad distribution of isomers that are likely populated under the experimental conditions. The contributions of individual structures to the global spectrum correspond to the relaxation via recurrent fluorescence and vibrational emission, electronic and vibrational structures being described by a simple but efficient density-functional-based tight-binding scheme. The model predicts a blackbody-like emission spectrum that is naturally broad and correctly accounts for the experimental measurements, except for a maximum that is quantitatively shifted with respect to Wien's displacement law. To quantify such differences, we introduce an emissivity parameter $\ensuremath{\varepsilon}$ as the ratio between the spectral emittance and the corresponding exact blackbody spectrum; $\ensuremath{\varepsilon}$ is numerically found to scale as ${(\ensuremath{\lambda}T)}^{\ensuremath{-}2}$ at leading order with increasing temperature $T$ and for wavelengths $\ensuremath{\lambda}&gt;350$ nm, and we provide a theoretical justification for this behavior. Our results are discussed in the light of the astrophysical detection of interstellar fullerenes, as well as in combustion environments where carbon clusters are relevant in the context of nascent soot particle formation.

Spatio‐Temporal Coarse‐Graining Decomposition of the Global Ocean Geostrophic Kinetic Energy

AbstractWe expand on a recent determination of the first global energy spectrum of the ocean's surface geostrophic circulation (Storer et al., 2022, https://doi.org/10.1038/s41467-022-33031-3) using a coarse‐graining (CG) method. We compare spectra from CG to those from spherical harmonics by treating land in a manner consistent with the boundary conditions. While the two methods yield qualitatively consistent domain‐averaged results, spherical harmonics spectra are too noisy at gyre‐scales (&gt;1,000 km). More importantly, spherical harmonics are inherently global and cannot provide local information connecting scales with currents geographically. CG shows that the extra‐tropics mesoscales (100–500 km) have a root‐mean‐square (rms) velocity of ∼15 cm/s, which increases to ∼30–40 cm/s locally in the Gulf Stream and Kuroshio and to ∼16–28 cm/s in the ACC. There is notable hemispheric asymmetry in mesoscale energy‐per‐area, which is higher in the north due to continental boundaries. We estimate that ≈25%–50% of total geostrophic energy is at scales smaller than 100 km, and is un(der)‐resolved by pre‐SWOT satellite products. Spectra of the time‐mean circulation show that most of its energy (up to 70%) resides in stationary eddies with characteristic scales smaller than (&lt;500 km). This highlights the preponderance of “standing” small‐scale structures in the global ocean due to the temporally coherent forcing by boundaries. By coarse‐graining in space and time, we compute the first spatio‐temporal global spectrum of geostrophic circulation from AVISO and NEMO. These spectra show that every length‐scale evolves over a wide range of time‐scales with a consistent peak at ≈200 km and ≈2–3 weeks.

Five-minute oscillations of photospheric and chromospheric swirls

Context. Swirls are ubiquitous in the solar atmosphere. They are thought to be related to the excitation of different modes of magnetohydrodynamic waves and pulses, as well as spicules. However, statistical studies of their collective behaviour are rare. Aims. We aim to study the collective as well as the individual behaviour of photospheric and chromospheric swirls detected by the automated swirl detection algorithm (ASDA) from observations obtained by the Swedish 1-m Solar Telescope and the Hinode satellite. Methods. We performed a detailed analysis of six different parameters of photospheric and chromospheric swirls with the wavelet analysis. Two clusters with periods with significant wavelet power, one from 3 − 8 min and the other from 10 − 14 min, were found. The former coincides with the dominant period of the global p-mode spectrum. The wavelet and fast Fourier transform analysis of example swirls also revealed similar periods. Results. These results suggest that global p-modes might be important in triggering photospheric and thus chromospheric swirls. A novel scenario of global p-modes providing energy and mass fluxes to the upper solar atmosphere via generating swirls, Alfvén pulses, and spicules is then proposed.

On singular values of large dimensional lag-[formula omitted] sample auto-correlation matrices

We study the limiting behavior of singular values of a lag-τ sample auto-correlation matrix Rτϵ of large dimensional vector white noise process, the error term ϵ in the high-dimensional factor model. We establish the limiting spectral distribution (LSD) that characterizes the global spectrum of Rτϵ, and derive the limit of its largest singular value. All the asymptotic results are derived under the high-dimensional asymptotic regime where the data dimension and sample size go to infinity proportionally. Under mild assumptions, we show that the LSD of Rτϵ is the same as that of the lag-τ sample auto-covariance matrix. Based on this asymptotic equivalence, we additionally show that the largest singular value of Rτϵ converges almost surely to the right end point of the support of its LSD. Based on these results, we further propose two estimators of total number of factors with lag-τ sample auto-correlation matrices in a factor model. Our theoretical results are fully supported by numerical experiments as well.

An effective model for the cosmic-dawn 21-cm signal

ABSTRACT The 21-cm signal holds the key to understanding the first structure formation during cosmic dawn. Theoretical progress over the last decade has focused on simulations of this signal, given the non-linear and non-local relation between initial conditions and observables (21 cm or reionization maps). Here, instead, we propose an effective and fully analytical model for the 21-cm signal during cosmic dawn. We take advantage of the exponential-like behaviour of the local star-formation rate density (SFRD) against densities at early times to analytically find its correlation functions including non-linearities. The SFRD acts as the building block to obtain the statistics of radiative fields (X-ray and Lyman α fluxes), and therefore the 21-cm signal. We implement this model as the public python package Zeus21. This code can fully predict the 21-cm global signal and power spectrum in ∼1 s, with negligible memory requirements. When comparing against state-of-the-art semi-numerical simulations from 21CMFAST we find agreement to $\sim 10~{{\ \rm per\ cent}}$ precision in both the 21-cm global signal and power spectra, after accounting for a (previously missed) underestimation of adiabatic fluctuations in 21CMFAST. Zeus21 is modular, allowing the user to vary the astrophysical model for the first galaxies, and interfaces with the cosmological code CLASS, which enables searches for beyond standard-model cosmology in 21-cm data. This represents a step towards bringing 21-cm to the era of precision cosmology.