Effective Degrees Of Freedom Research Articles

Exploration of diverse solutions for the calibration of imperfect climate models

Abstract. The calibration of Earth system model parameters is subject to data, time, and computational constraints. The high dimensionality of this calibration problem, combined with errors arising from model structural assumptions, makes it impossible to find model versions fully consistent with historical observations. Therefore, the potential for multiple plausible configurations presenting different trade-offs between skills in various variables and spatial regions remains usually untested. In this study, we lay out a formalism for making different assumptions about how ensemble variability in a perturbed physics ensemble relates to model error, proposing an empirical but practical solution for finding diverse near-optimal solutions. A meta-model is used to predict the outputs of a climate model reduced through principal component analysis. Then, a subset of input parameter values yielding results similar to a reference simulation is identified. We argue that the effective degrees of freedom in the model performance response to parameter input (the “parametric component”) are, in fact, relatively small, illustrating why manual calibration is often able to find near-optimal solutions. The results explore the potential for comparably performing parameter configurations that have different trade-offs in model errors. These model candidates can inform model development and could potentially lead to significantly different future climate evolution.

Association between metabolic score of visceral fat and carotid atherosclerosis in Chinese health screening population: a cross-sectional study

BackgroundThe metabolic score for visceral fat (METS-VF) quantifies the cumulative burden of visceral and intra-abdominal adipose tissues. However, the relationship between the METS-VF and carotid atherosclerosis (CAS) has not been extensively explored. Therefore, this study aimed to investigate the association between the METS-VF and CAS.MethodsThis cross-sectional study enrolled 7089 Chinese adults who underwent physical examinations at the Zhenhai Lianhua Hospital, Zhejiang, China, in 2020. Multivariable logistic regression analysis was used to explore the linear relationship between METS-VF and CAS. Generalised additive models (GAM) were employed to evaluate potential nonlinear associations. The inflection points of METS-VF were determined using segmented logistic regression analysis optimised for maximum likelihood ratios and recursive algorithms.ResultsMultivariable logistic regression analysis revealed a positive correlation between METS-VF and CAS (odds ratio [OR]: 1.824, 95% confidence interval [CI]: 1.753–1.899; P < 0.001). The GAM analysis confirmed a nonlinear association between them [effective degrees of freedom: 4.803, χ2: 876.7, P < 0.001], with an inflection point at a METS-VF of 8.09 (P < 0.001 for log-likelihood ratio test). Below this inflection point, METS-VF exhibited a significant positive association with CAS risk (OR: 1.874, 95% CI: 1.796–1.954; P < 0.001). Conversely, no significant association was observed when METS-VF ≥ 8.09 (OR: 0.998, 95% CI: 0.786–1.268; P = 0.989).ConclusionsMETS-VF and CAS demonstrated a positive non-linear correlation, with the curve indicating a saturation effect at METS-VF = 8.09.

Two Effective Degrees of Freedom Can Represent the Dominant Features of Global Rayleigh Wave Dispersion Maps

AbstractObjectively exploring global variations in crust and upper mantle structure helps constrain fundamental aspects of Earth's plate tectonic and convective processes. Here we adopted a Variational Auto‐Encoder to explore the degrees of freedom of global Rayleigh wave dispersion maps at 4–40 mHz. We found that two latent variables sufficiently represent the global variations, suggesting inherent coupling between crustal and mantle seismic properties. We propose that the two extracted latent variables mostly correspond with crustal thickness and upper mantle thermal structure. The first variable shows low values for continental mountain belts and ocean spreading ridges, contrasted by high values for abyssal plains. The second variable shows low values for most oceanic lithosphere and Phanerozoic continental areas, contrasted by high values for Archean cratons. Latent space correlations indicate that continental lithosphere has more strongly coupled depth features than beneath the oceans, which might be a consequence of its longevity.

Measuring complexity for hierarchical models using effective degrees of freedom

AbstractHierarchical models can express ecological dynamics using a combination of fixed and random effects, and measurement of their complexity (effective degrees of freedom, EDF) requires estimating how much random effects are shrunk toward a shared mean. Estimating EDF is helpful to (1) penalize complexity during model selection and (2) to improve understanding of model behavior. I applied the conditional Akaike Information Criterion (cAIC) to estimate EDF from the finite‐difference approximation to the gradient of model predictions with respect to each datum. I confirmed that this has similar behavior to widely used Bayesian criteria, and I illustrated ecological applications using three case studies. The first compared model parsimony with or without time‐varying parameters when predicting density‐dependent survival, where cAIC favors time‐varying demographic parameters more than conventional Akaike Information Criterion. The second estimates EDF in a phylogenetic structural equation model, and identifies a larger EDF when predicting longevity than mortality rates in fishes. The third compares EDF for a species distribution model fitted for 20 bird species and identifies those species requiring more model complexity. These highlight the ecological and statistical insight from comparing EDF among experimental units, models, and data partitions, using an approach that can be broadly adopted for nonlinear ecological models.

Extremely Large-Scale MIMO: Fundamentals, Challenges, Solutions, and Future Directions

Extremely large-scale multiple-input-multipleoutput (XL-MIMO) is a promising technology to empower the next-generation communications. However, XL-MIMO, which is still in its early stage of research, has been designed with a variety of hardware and performance analysis schemes. To illustrate the differences and similarities among these schemes, we comprehensively review existing XL-MIMO hardware designs and characteristics in this article. Then, we thoroughly discuss the research status of XL-MIMO from "channel modeling", "performance analysis", and "signal processing". Several existing challenges are introduced and respective solutions are provided. We then propose two case studies for the hybrid propagation channel modeling and the effective degrees of freedom (EDoF) computations for practical scenarios. Using our proposed solutions, we perform numerical results to investigate the EDoF performance for the scenarios with unparallel XL-MIMO surfaces and multiple user equipment, respectively. Finally, we discuss several future research directions.

One size does not fit all: Differential predation on livestock species by leopards (Panthera pardus) in a multiuse landscape in the gangetic plains, India

There are underlying patterns involved in predation, particularly for an adaptable species like leopard. One of them is size of the prey. The selection of a prey by a carnivore is typically determined by the trade-off between energy spent and gained. Here size becomes even more consequential when conflict is involved, but most studies typically map all species as a single entity at a single spatial scale. This study aimed at understanding the multiscale nature of the conflict based on the size livestock attacked by leopards (large stock − cattle and small stock − goat and sheep). The methodology encompassed targeted sampling which included the collection of the GPS locations of the attack sites. Spatial layers of 14 environmental variables that represented three spatial scales i.e. proximate (cache-distance), local (daily-movement), and landscape (home-range) scale were then created through remotely sensed data. After that Generalized additive models were utilized for analysis, with ΔAIC used for model selection and evaluation was performed via AUC and TSS statistic. Our results indicate a spatial distinction in predation strategies. In the final model the statistically significant variables for large stock included a higher proportion of cover, and a lower proportion of settlements at the home-range scale, very low human population density at daily-movement scale, and NDVI representing moderately dense vegetation and terrain ruggedness index representing flat terrain at cache-distance scale. Similarly, for small stock the variables included a higher proportion of agricultural land and NDVI values representing open terrain. The effective degrees of freedom was higher than 2 for most of the variables, indicating non-linear relationships. We inferred that the leopards’ targeted large stock in more secluded dry deciduous forests farther from human settlements, where they may be found grazing alone. In contrast, smaller stock, being easier to catch, are killed more frequently in rugged terrain across a wider scrub landscape with scantier cover. Consequently, this selective selection based on size might have its basis in the perceived risk of being chased off by people and the reward in terms of the size of the acquired meal.

Unimodality of Parametric Linear Programming Solutions and Efficient Quantile Estimation

For linear optimization problems with a parametric objective, so-called parametric linear programs (PLP), we show that the optimal decision values are, under few technical restrictions, unimodal functions of the parameter, at least in the two-degrees-of-freedom case. Assuming that the parameter is random and follows a known probability distribution, this allows for an efficient algorithm to determe the quantiles of linear combinations of the optimal decisions. The novel results are demonstrated with probabilistic economic dispatch. For an example setup with uncertain fuel costs, quantiles of the resulting inter-regional power flows are computed. The approach is compared against Monte Carlo and piecewise computation techniques, proving significantly reduced computation times for the novel procedure. This holds especially when the feasible set is complex and/or extreme quantiles are desired. This work is limited to problems with two effective degrees of freedom and a one-dimensional uncertainty. Future extensions to higher dimensions could yield a key tool for the analysis of probabilistic PLPs and, specifically, risk management in energy systems.

Multi-year observations of particulate matter and gases over Mumbai: Spatio-temporal variation, oxidation ratios, and secondary aerosols

System of Air quality and weather Forecasting And Research (SAFAR-Mumbai) network hourly observations of air pollutants spanning half a decade are subjected to a Generalized Additive Model (GAM) to investigate the non-linear relationship of PM2.5 to other precursor gases and meteorological parameters. The Effective Degrees of Freedom (EDF), a statistic of GAM quantifying the non-linear relationship, reveals that PM2.5 is highly non-linearly dependent on NH3, SO2, and CO as inferred from the response curves exhibiting at least one inflexion point and threshold responses. PM2.5 is linearly related to NO2 (EDF = 1), while it is non-linearly related to other gases and meteorological parameters (EDF > 2). The frequency distribution of PM2.5 shows a sharp peak at 25 μg m−3 in monsoon and broad peaks in pre-monsoon (peak at 50 μg m−3), post-monsoon (peak at 60 μg m−3) and winter (peak at 100 μg m−3) indicating relatively large variability in winter and post-monsoon. Chemical analysis of PM2.5 shows a high contribution of four major ions in the order of SO42− > Cl− > Na+ > NH4+, mainly associated with anthropogenic and marine sources. The average sulphate oxidation ratio (SOR), nitrogen oxidation ratio (NOR), and neutralization ratio (NR) are up to 0.3, 0.04, and 0.27, respectively, indicating that SO2 is contributing majorly to secondary aerosol production. Monthly concertation of PM2.5, Ozone (O3), CO, NO2, SO2, and NH3 shows U-shaped variability with maximum in winter and minimum in monsoon.

Functional connectivity MRI quality control procedures in CONN.

Quality control (QC) for functional connectivity magnetic resonance imaging (FC-MRI) is critical to ensure the validity of neuroimaging studies. Noise confounds are common in MRI data and, if not accounted for, may introduce biases in functional measures affecting the validity, replicability, and interpretation of FC-MRI study results. Although FC-MRI analysis rests on the assumption of adequate data processing, QC is underutilized and not systematically reported. Here, we describe a quality control pipeline for the visual and automated evaluation of MRI data implemented as part of the CONN toolbox. We analyzed publicly available resting state MRI data (N = 139 from 7 MRI sites) from the FMRI Open QC Project. Preprocessing steps included realignment, unwarp, normalization, segmentation, outlier identification, and smoothing. Data denoising was performed based on the combination of scrubbing, motion regression, and aCompCor - a principal component characterization of noise from minimally eroded masks of white matter and of cerebrospinal fluid tissues. Participant-level QC procedures included visual inspection of raw-level data and of representative images after each preprocessing step for each run, as well as the computation of automated descriptive QC measures such as average framewise displacement, average global signal change, prevalence of outlier scans, MNI to anatomical and functional overlap, anatomical to functional overlap, residual BOLD timeseries variability, effective degrees of freedom, and global correlation strength. Dataset-level QC procedures included the evaluation of inter-subject variability in the distributions of edge connectivity in a 1,000-node graph (FC distribution displays), and the estimation of residual associations across participants between functional connectivity strength and potential noise indicators such as participant's head motion and prevalence of outlier scans (QC-FC analyses). QC procedures are demonstrated on the reference dataset with an emphasis on visualization, and general recommendations for best practices are discussed in the context of functional connectivity and other fMRI analysis. We hope this work contributes toward the dissemination and standardization of QC testing performance reporting among peers and in scientific journals.

Examining non-linearity in the association between age and reported opioid use in different socioeconomic strata: cohort study using Health Survey for England waves from 1997 to 2014

BackgroundAge and socioeconomic status (SES) predict several health-related outcomes, including prescription opioid use. Contrasting findings from previous literature found higher prevalence of opioid use in both people over 65 years...

Electromagnetic Channel Model for Near Field MIMO Systems in the Half Space

In most multiple-input multiple-output (MIMO) communication systems, the amount of information that can be transmitted reliably depends on the effective degrees of freedom (EDoF) of the wireless channel. Conventionally, one can model the channel matrix and study the EDoF, based on an electromagnetic (EM) channel model that is built with the free space Green function. However, the EDoF of free-space channel model may not fit the practical scenario when EM waves only transmit above the ground. In this letter, we analyze the EDoF for both discrete and continuous aperture MIMO systems in the half space. We also propose an approach to quickly calculate the Green function in the half space from the Sommerfeld identity. Simulation results show that the difference between the EDoF in the half space and that in the free space is non-negligible for the near field communications, which indicates that the ground exerts noticeable influence on EDoF. The proposed study establishes a fundamental electromagnetic framework for MIMO wireless communication in the half space.

Evidence for superadiabatic heating and cooling of Alfvénic solar wind

ABSTRACT Alfvénic fluctuations are widespread and crucial in various physical processes of space &amp; astrophysical plasma. However, their role in heating and work done remains unexplored. Here, we have used Wind spacecraft’s data situated at 1 au distance to examine 12 distinct Alfvénic regions using polytropic analysis. The study finds an average polytropic index value α = 2.64, which is consistent with a superadiabatic behaviour for plasma particles with three effective degrees of freedom (f = 3). Moreover, this study examines several scenarios for plasma particles with different degrees of freedom. We noted that the investigated Alfvénic region could be adiabatic only for plasma particles with f = 1.26 degrees of freedom. In addition to this, for α = 2.64, the ratio of work done to the total heat supply within the system is $\frac{\delta w}{\delta q} = -0.68$, indicating that 68 per cent of the total supplied heat is utilized to accomplish work by the system on the surrounding (expansion phenomena), and the remaining is used to increase the internal energy of the system. As a result, we hypothesized that the Alfvénic plasma region is cooling more than the adiabatic expectation, resulting in supercooling phenomena. Thus, we propose that the discovered possible superadiabatic process would be critical in understanding the energy transfer from the Alfvénic zone to the surrounding plasma.

Epigenome-wide DNA methylation in leukocytes and toenail metals: The normative aging study

BackgroundEnvironmental metal exposures have been associated with multiple deleterious health endpoints. DNA methylation (DNAm) may provide insight into the mechanisms underlying these relationships. Toenail metals are non-invasive biomarkers, reflecting a medium-term time exposure window. ObjectivesThis study examined variation in leukocyte DNAm and toenail arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg) among elderly men in the Normative Aging Study, a longitudinal cohort. MethodsWe repeatedly collected samples of blood and toenail clippings. We measured DNAm in leukocytes with the Illumina HumanMethylation450 K BeadChip. We first performed median regression to evaluate the effects of each individual toenail metal on DNAm at three levels: individual cytosine-phosphate-guanine (CpG) sites, regions, and pathways. Then, we applied a Bayesian kernel machine regression (BKMR) to assess the joint and individual effects of metal mixtures on DNAm. Significant CpGs were identified using a multiple testing correction based on the independent degrees of freedom approach for correlated outcomes. The approach considers the effective degrees of freedom in the DNAm data using the principal components that explain >95% variation of the data. ResultsWe included 564 subjects (754 visits) between 1999 and 2013. The numbers of significantly differentially methylated CpG sites, regions, and pathways varied by metals. For example, we found six significant pathways for As, three for Cd, and one for Mn. The As-associated pathways were associated with cancer (e.g., skin cancer) and cardiovascular disease, whereas the Cd-associated pathways were related to lung cancer. Metal mixtures were also associated with 47 significant CpG sites, as well as pathways, mainly related to cancer and cardiovascular disease. ConclusionsThis study provides an approach to understanding the potential epigenetic mechanisms underlying observed relations between toenail metals and adverse health endpoints.

The spectral geometry of de Sitter space in asymptotic safety

Within the functional renormalization group approach to Background Independent quantum gravity, we explore the scale dependent effective geometry of the de Sitter solution dS4. The investigation employs a novel approach whose essential ingredient is a modified spectral flow of the metric dependent d’Alembertian, or of similar hyperbolic kinetic operators. The corresponding one-parameter family of spectra and eigenfunctions encodes information about the nonperturbative backreaction of the dynamically gravitating vacuum fluctuations on the mean field geometry of the quantum spacetime. Used as a diagnostic tool, the power of the spectral flow method resides in its ability to identify the scale dependent subsets of field modes that supply the degrees of freedom which participate in the effective field theory description of the respective scale. A central result is that the ultraviolet of Quantum Einstein Gravity comprises far less effective degrees of freedom than predicted (incorrectly) by background dependent reasoning. The Lorentzian signature of dS4 is taken into account by selecting a class of renormalization group trajectories which are known to apply to both the Euclidean and a Lorentzian version of the approach. Exploring the quantum spacetime’s spatial geometry carried by physical fields, we find that 3-dimensional space disintegrates into a collection of coherent patches which individually can, but in their entirety cannot be described by one of the effective average actions occurring along the renormalization group trajectory. A natural concept of an entropy is introduced in order to quantify this fragmentation effect. Tentatively applied to the real Universe, surprising analogies to properties of the observed cosmic microwave background are uncovered. Furthermore, a set of distinguished field modes is found which, in principle, has the ability to transport information about the asymptotic fixed point regime from the ultraviolet, across almost the entire “scale history”, to cosmological distances in the observed Universe.

In-medium hadronization of heavy quarks and its effect on charmed meson and baryon distributions in heavy-ion collisions

We present a new model for the description of heavy-quark hadronization in relativistic heavy-ion collisions in the presence of a reservoir of lighter thermal particles with which recombination can occur leading to the formation of color-singlet clusters. Color neutralization is assumed to occur locally, within the same fluid cell occupied by the heavy quark and it proceeds via the recombination of the latter with light antiquarks (quarks) or diquarks (anti-diquarks), which are assumed to be present in the medium with thermal abundance as effective degrees of freedom around the QCD crossover temperature T_c. Typically the resulting color-singlet clusters have quite low invariant mass, in most of the cases below 4 GeV, and in this case they are assumed to undergo an isotropic 2-body decay in their local rest-frame. Heavier clusters are instead fragmented as Lund strings. The possibility of recombination with light diquarks enhances the yields of charmed baryons, in qualitative agreement with recent measurements. The assumption of local color neutralization leads to a strong space-momentum correlation, which provides a substantial enhancement of the collective flow of the final-state charmed hadrons, affecting both their momentum and their angular distributions.

Meaningful expression of uncertainty in measurement

The Guide to the expression of uncertainty in measurement (GUM) has been the enduring guide on measurement uncertainty for metrologists since its first publication in 1993. According to the GUM, a measurement should always be accompanied by a reasoned and defensible expression of uncertainty, and the primary such expression is the standard uncertainty. In this article, we distinguish between the use of an expression of uncertainty as information for the recipient of a measurement result and its use when propagating uncertainty about inputs to a measurement model in order to derive the uncertainty in a measurand. We propose a new measure of uncertainty, the characteristic uncertainty, and argue that it is more fit for these purposes than standard uncertainty. For the purpose of reporting a measurement result, we demonstrate that standard uncertainty does not have a meaningful interpretation for the recipient of a measurement result and can be infinite. These deficiencies are resolved by the characteristic uncertainty, which we therefore recommend for use in reporting. For similar reasons, we advocate the use of the median estimate as the measured value. For the purpose of propagating uncertainty in a measurement model, we propose simple propagation of the median and characteristic uncertainty and show through some examples that this characteristic uncertainty framework is simpler and at least as reliable and accurate as the propagation of estimate, standard uncertainty and effective degrees of freedom according to the GUM uncertainty framework.

Selenium-associated differentially expressed microRNAs and their targeted mRNAs across the placental genome in two U.S. birth cohorts

ABSTRACT Selenium is an important micronutrient for foetal development. MicroRNAs play an important role in the function of the placenta, in communication between the placenta and maternal systems, and their expression can be altered through environmental and nutritional cues. To investigate the associations between placental selenium concentration and microRNA expression in the placenta, our observational study included 393 mother-child pairs from the New Hampshire Birth Cohort Study (NHBCS) and the Rhode Island Child Health Study (RICHS). Placental selenium concentrations were quantified using inductively coupled plasma mass spectrometry, and microRNA transcripts were measured using RNA-seq. We fit negative binomial additive models for assessing the association between selenium and microRNAs. We used the microRNA Data Integration Portal (mirDIP) to predict the target mRNAs of the differentially expressed microRNAs and verified the relationships between miRNA and mRNA targets in a subset of samples using existing whole transcriptome data (N = 199). We identified a non-monotonic association between selenium concentration and the expression of miR-216a-5p/miR-217-5p cluster (effective degrees of freedom, EDF = 2.44 and 2.08; FDR = 3.08 × 10−5) in placenta. Thirty putative target mRNAs of miR-216a-5p and/or miR-217-5p were identified computationally and empirically and were enriched in selenium metabolic pathways (driven by selenoprotein coding genes, TXNRD2 and SELENON). Our findings suggest that selenium influences placental microRNA expression. Further, miR-216a-5p and its putative target mRNAs could be the potential mechanistic targets of the health effect of selenium.

Epigenome-wide DNA Methylation in Leukocyte and Toenail Metals: the Normative Aging Study

BACKGROUND AND AIM: Environmental metal exposures have been associated with deleterious health endpoints. DNA methylation (DNAm) may provide insight into mechanisms underlying these associations. We aimed to examine variation in leukocyte DNAm and its relationship to toenail arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg) among elderly men in the Normative Aging Study. METHODS: We repeatedly collected blood samples and toenails clippings and measured DNAm with the Illumina HumanMethylation450K BeadChip. We performed median regression with subject-specific intercepts for each of the five toenail metals and DNAm at individual cytosine-phosphate-guanine (CpG) site adjusting for covariates. We adjusted for multiple comparison using two thresholds: 1) Bonferroni correction based on effective degrees of freedom using the number of principal components explaining 95% variation of the total CpGs (i.e., PC-based); and 2) false discovery rate at the level of 0.05. We further conducted regional analyses using {comb-p} and pathway analyses using {Metacore}. RESULTS:We included 549 men with 758 visits (1999-2013). The numbers of significantly differentially methylated CpGs using PC-based Bonferroni correction or false discovery rate (in parenthesis) were 51 (38) for As, 55 (52) for Mn, 11 (5) for Cd, 1 (0) for Hg, and 2 (0) for Pb, respectively. The annotated genes by As, Mn, and Cd were associated with cardiovascular disease, psychiatric disorders, diabetes and cancer. For example, the identified gene {HDAC4} by As is associated with myocardial infarction. We observed 14 significant regions for As and Mn, 4 for Cd, 2 for Hg, and 0 for Pb. We also found 3 significant pathways, which have been related to Alzheimer's disease (As), heart diseases (Cd), and psychiatric disorders (Cd). CONCLUSIONS:This study provides preliminary data on epigenetic mechanisms that may underlie environmental metals and adverse health endpoints. Further work is needed to assess interactions among metals and among health outcomes associated with exposure. KEYWORDS: Heavy metals, Epigenomics, Male

Additive models with autoregressive symmetric errors based on penalized regression splines

In this paper additive models with p-order autoregressive conditional symmetric errors based on penalized regression splines are proposed for modeling trend and seasonality in time series. The aim with this kind of approach is try to model the autocorrelation and seasonality properly to assess the existence of a significant trend. A backfitting iterative process jointly with a quasi-Newton algorithm are developed for estimating the additive components, the dispersion parameter and the autocorrelation coefficients. The effective degrees of freedom concerning the fitting are derived from an appropriate smoother. Inferential results and selection model procedures are proposed as well as some diagnostic methods, such as residual analysis based on the conditional quantile residual and sensitivity studies based on the local influence approach. Simulations studies are performed to assess the large sample behavior of the maximum penalized likelihood estimators. Finally, the methodology is applied for modeling the daily average temperature of San Francisco city from January 1995 to April 2020.

Large N-ightmare dark matter

A dark QCD sector is a relatively minimal extension of the Standard Model (SM) that admits Dark Matter (DM) candidates, but requires no portal to the visible sector beyond gravitational interactions:a “nightmare scenario” for DM detection.We consider a secluded dark sector containing a single flavor of light, vector-like dark quark gauged under (N).In the large-N limit, this single-flavor theory becomes highly predictive, generating two DM candidates whose masses and dynamics are described by few parameters:a light quark-antiquark bound state, the dark analog of the η' meson, and a heavy bound state of N quarks, the dark analog of the Δ++ baryon.We show that the latter may freeze-in with an abundance independent of the confinement scale,forming DM-like relics for N ≲ 10, while the former may generate DM via cannibalization and freeze-out.We study the interplay of this two-component DM system,and determine the characteristic ranges of the confinement scale,dark-visible sector temperature ratio, and N that admit non-excluded DM,once effects of self-interaction constraints and bounds on effective degrees of freedom at the BBN and CMB epochs are included.