Single Bin Research Articles

Functional Variation in Human CAZyme Genes in Relation to the Efficacy of a Carbohydrate-Restricted Diet in IBS Patients

Limiting the dietary intake of certain carbohydrates has therapeutic effects in some but not all irritable bowel syndrome (IBS) patients. We investigated genetic variation in human Carbohydrate-Active enZYmes (hCAZymes) genes in relation to the response to a FODMAP-lowering diet in the DOMINO study. HCAZy polymorphism was studied in IBS patients from the dietary (FODMAP-lowering; N=196) and medication (otilonium bromide; N=54) arms of the DOMINO trial via targeted sequencing of 6 genes of interest (AMY2B, LCT, MGAM, MGAM2, SI and TREH). hCAZyme defective (hypomorphic) variants were identified via computational annotation using clinical pathogenicity classifiers. Age- and sex-adjusted logistic regression was used to test hCAZyme polymorphisms in cumulative analyses where IBS patients were stratified into carrier and non-carrier groups (collapsing all hCAZyme hypomorphic variants into a single bin). Quantitative analysis of hCAZyme variation was also performed, in which the number of hCAZyme genes affected by a hypomorphic variant was taken into account. In the dietary arm, the number of hypomorphic hCAZyme genes positively correlated with treatment response rate (P=.03, OR=1.51 [CI=0.99-2.32]). In the IBS-D group (N=55), hCAZyme carriers were six times more likely to respond to the diet than non-carriers (P=.002, OR=6.33 [CI=1.83-24.77]). These trends were not observed in the medication arm. HCAZYme genetic variation may be relevant to the efficacy of a carbohydrate-lowering diet. This warrants additional testing and replication of findings, including mechanistic investigations of this phenomenon.

Improved approximation for two-dimensional vector multiple knapsack

We study the uniform 2-dimensional vector multiple knapsack (2VMK) problem, a natural variant of multiple knapsack arising in real-world applications such as virtual machine placement. The input for 2VMK is a set of items, each associated with a 2-dimensional weight vector and a positive profit, along with m 2-dimensional bins of uniform (unit) capacity in each dimension. The goal is to find an assignment of a subset of the items to the bins, such that the total weight of items assigned to a single bin is at most one in each dimension, and the total profit is maximized.Our main result is a (1−ln⁡22−ε)-approximation algorithm for 2VMK, for every fixed ε>0, thus improving the best known ratio of (1−1e−ε) which follows as a special case from a result of Fleischer et al. (2011) [6].Our algorithm relies on an adaptation of the Round&Approx framework of Bansal et al. (2010) [15], originally designed for set covering problems, to maximization problems. The algorithm uses randomized rounding of a configuration-LP solution to assign items to ≈m⋅ln⁡2≈0.693⋅m of the bins, followed by a reduction to the (1-dimensional) Multiple Knapsack problem for assigning items to the remaining bins.

Methodological refinement of the submillimeter galaxy magnification bias

Aims.The main goal of this work is to test the results of a methodological improvement in the measurement of the magnification bias signal on a sample of submillimeter galaxies. In particular, we investigate the constraining power of cosmological parameters within the ΛCDM model. We also discuss important points that can affect the results.Methods.We measured the angular cross-correlation function between a sample of foreground GAMA II galaxies in a single wide spectroscopic redshift bin of 0.2 < z < 0.8 and a sample of background submillimeter galaxies fromHerschel-ATLAS. We focused on the photometric redshift range of 1.2 < z < 4.0, with an improved methodological framework. Interpreting the weak lensing signal within the halo model formalism and performing a Markov chain Monte Carlo (MCMC) algorithm, we obtained the posterior distribution of both the halo occupation distribution and cosmological parameters within a flat ΛCDM model. Our analysis was also performed with additional galaxy clustering information via a foreground angular auto-correlation function.Results.We observed an overall remarkable improvement in terms of uncertainties in both the halo occupation distribution and cosmological parameters with respect to previous results. A priori knowledge aboutβ, the logarithmic slope of the background integral number counts, is found to be paramount to derive constraints onσ8when using the cross-correlation data alone. Assuming a physically motivated prior distribution forβ, we obtain mean values of Ωm = 0.23−0.06+0.03and σ8 = 0.79−0.10+0.10and an unconstrained distribution for the Hubble constant. These results are likely to suffer from sampling variance, since one of the fields, G15, appears to have an anomalous behavior with a systematically higher cross-correlation. We find that removing it from the sample yields mean values of Ωm = 0.27−0.04+0.02andσ8 = 0.72−0.04+0.04and, for the first time, a (loose) restriction of the Hubble constant is obtained via this observable:h = 0.79−0.14+0.13. The addition of the angular auto-correlation of the foreground sample in a joint analysis tightens the constraints, but also reveals a discrepancy between both observables that might be an aggravated consequence of sampling variance or due to the presence of unmodeled aspects on small and intermediate scales.

Covariance matrices for the Lyman-α forest using the lognormal approximation

We investigate the nature of correlations in the small-scale flux statistics of the Lyman-α (Lyα) forest across redshift bins. Understanding and characterising these correlations is important for unbiased cosmological and astrophysical parameter inference using the Lyα forest. We focus on the 1-dimensional flux power spectrum (FPS) and mean flux (F̅) simulated using the semi-numerical lognormal model we developed in earlier work. The lognormal model can capture the effects of long wavelength modes with relative ease as compared to full smoothed particle hydrodynamical (SPH) simulations that are limited by box volume. For a single redshift bin of size Δz ≃ 0.1, we show that the lognormal model predicts positive cross-correlations between k-bins in the FPS, and a negative correlation for F̅ × FPS, in qualitative agreement with SPH simulations and theoretical expectations. For measurements across two neighbouring redshift bins of width Δ z each (using long flux skewers of length 2Δ z that are 'split' in half), the lognormal model predicts an anti-correlation for FPS × FPS and a positive correlation for F̅ × FPS, caused by modes with the longest wavelengths. This is in contrast to SPH simulations which predict a negligible magnitude for cross-redshift correlations derived from such `split' skewers, and we discuss possible reasons for this difference. Finally, we perform a preliminary test of the impact of neglecting long wavelength modes on parameter inference, finding that whereas the correlation structure of neighbouring redshift bins has relatively little impact, the absence of long wavelength modes in the model can lead to ≳ 2 - σ biases in the inference of astrophysical parameters. Our results motivate a more careful treatment of long wavelength modes in analyses that rely on the small-scale Lyα forest for parameter inference.

The InBIO Barcoding Initiative Database: DNA barcodes of Iberian Bees.

Bees are important actors in terrestrial ecosystems and are recognised for their prominent role as pollinators. In the Iberian Peninsula, approximately 1,100 bee species are known, with nearly 100 of these species being endemic to the Peninsula. A reference collection of DNA barcodes, based on morphologically identified bee specimens, representing 514 Iberian species, was constructed. The "InBIO Barcoding Initiative Database: DNA Barcodes of Iberian bees" dataset contains records of 1,059 sequenced specimens. The species of this dataset correspond to about 47% of Iberian bee species diversity and 21% of endemic species diversity. For peninsular Portugal only, the corresponding coverage is 71% and 50%. Specimens were collected between 2014 and 2022 and are deposited in the research collection of Thomas Wood (Naturalis Biodiversity Center, The Netherlands), in the FLOWer Lab collection at the University of Coimbra (Portugal), in the Andreia Penado collection at the Natural History and Science Museum of the University of Porto (MHNC-UP) (Portugal) and in the InBIO Barcoding Initiative (IBI) reference collection (Vairão, Portugal). Of the 514 species sequenced, 75 species from five different families are new additions to the Barcode of Life Data System (BOLD) and 112 new BINs were added. Whilst the majority of species were assigned to a single BIN (94.9%), 27 nominal species were assigned to multiple BINs. Although the placement into multiple BINs may simply reflect genetic diversity and variation, it likely also represents currently unrecognised species-level diversity across diverse taxa, such as Amegillaalbigena Lepeletier, 1841, Andrenarussula Lepeletier, 1841, Lasioglossumleucozonium (Schrank, 1781), Nomadafemoralis Morawitz, 1869 and Sphecodesalternatus Smith, 1853. Further species pairs of Colletes, Hylaeus and Nomada were placed into the same BINs, emphasising the need for integrative taxonomy within Iberia and across the Mediterranean Basin more broadly. These data substantially contribute to our understanding of bee genetic diversity and DNA barcodes in Iberia and provide an important baseline for ongoing taxonomic revisions in the West Palaearctic biogeographical region.

Mid-frequency convergence zone propagation

Convergence zone propagation has a cycle distance of order 50 km with most of the path spent below the thermocline. Calculations using Garrett-Munk statistics and rays computed with a smoothed background sound speed profile over this single cycle predict propagation in the partially saturated regime and an integration time of 500 seconds (time spent in a single output bin of a discrete Fourier transform). Parabolic equation simulations with synthetic fine structure and ocean dynamics validate the ray-based calculations. Data of narrowband transmissions from 1.5 to 7.5 kHz from a shallow towed source (150 m) to a shallow drifting array (150 m) depth at a range of 59 km demonstrate smoothly varying phase in a beam permitting coherent integrations of 3.5 minutes. The shorter integration time in data is consistent with non-uniform motion estimated from GPS.

Spectral information content of Compton scattering events in silicon photon counting detectors.

Silicon (Si) is a possible sensor material for photon counting detectors (PCDs). A major drawback of Si is that roughly two-thirds of x-ray interactions in the diagnostic energy range are Compton scattering. Because Compton scattering is an energy-insensitive process, it is commonly assumed that Compton events retain little spectral information. To quantify how much information can be recovered from Compton scattering events in models of Si PCDs. We built a simplified model of Si interactions including two interaction mechanisms: photoelectric effect and Compton scattering. We considered three different binning options that represent strategies for handling Compton events: in Compton censoring, all events under 38keV (the maximum energy possible from Compton scattering for a 120keV incident photon) were discarded; in Compton counting, all events between 1 and 38keV were placed into a single bin; in Compton binning, all events were placed into energy bins of uniform width. These were compared to the ideal detector, which always recorded the correct energy (i.e., 100% photoelectric effect). Every photon was assumed to interact once and only once with Si, and the energy bin width was 5keV. In the primary analysis, the Si detector was irradiated with a 120kV spectrum filtered by 30cm of water, with 99.5% of the arriving spectrum above 38keV so that there was good separation between photoelectric effect and Compton scattering, and the figures of merit were the Cramér-Rao lower bound (CRLB) of the variance of iodine and water basis material decomposition images, as well as the CRLB of virtual monoenergetic images (i.e., linear combinations of material images) that maximize iodine CNR or water CNR. We also constructed a local linear estimator that attains the CRLB. In secondary analyses, we applied other sources of spectral distortion: (1) a nonzero minimum energy threshold; (2) coarser, 10keV energy bins; and (3) a model of charge sharing. With our chosen spectrum, 67% of the interactions were Compton scattering. Consistent with this, the material decomposition variance for the Compton censoring model, averaged over both basis materials, was 258% greater than the ideal detector. If Compton events carried no spectral information, the Compton counting model would show similar variance. Instead, its basis material variance was 103% greater than the ideal detector, implying that Compton counts indeed carry significant spectral information. The Compton binning model had a basis material variance 60% greater than the ideal detector. The Compton binning model was not affected by a 5keV minimum energy threshold, but the variance increased from 60% to 107% when charge sharing was included and to 78% with coarser energy bins. For optimized CNR images, the average variance was 149%, 12%, and 10% higher than the ideal detector for the Compton censoring, counting, and binning models, reinforcing the hypothesis that Compton counts are useful for detection tasks and that precise energy assignments are not necessary. Substantial spectral information remains after Compton scattering events in silicon PCDs.

Effects of vertical load and inflation pressure on tire-soil interaction on artificial soil

Instrumented single tire soil bin testing was conducted on a rigid surface and artificial soil by vertically loading a radial tire (LT235/75R15) to two tire vertical loads (6 kN and 8 kN) inflated to three levels of tire inflation pressure (179, 241, and 283 kPa). Lowering the tire inflation pressure by 37 % resulted in 26 % (6 kN vertical load) and 39 % (8 kN vertical load) greater contact lengths (P < 0.05). The 2-D contact area on artificial soil (initial bulk density of 1.51 Mg/m3) was significantly affected (P < 0.05) by tire inflation pressure for each load case. Increasing the load significantly affected the tire’s contact length on soil (P = 0.0010); however, tire inflation pressure did not significantly affect the contact length on soil (P = 0.0609). Soil rut depth and tire-soil deformed volume were not significantly affected by vertical load and tire inflation pressure. Measured tire contact area on soil surface was 3.3 times the contact area on the rigid surface, suggesting tire-soil interaction interface properties on deformable soil are better than using the gross flat plate for evaluating low ground pressure tire technology effects on traction and reducing soil compaction.

Per-length biomass estimates of Antarctic krill (Euphausia superba)

Total biomass and areal biomass density are often necessary to establish ecological relationships and enable informed management decisions, in particular setting fisheries catch limits. Further refining these estimates to sub-population biomass based on length informs ecological models of predator-prey dynamics, ecosystem energy transfer and biogeochemical cycles; however, measures of uncertainty in these per-length biomass estimates are needed. We present a statistical method to calculate the per-length biomass of Antarctic krill (Euphausia superba) from conversion factors using acoustic and net sample data. Variability in krill length-frequency, and wetmass introduced by net sampling is also explored through non-parametric bootstrapping. We applied this method on a 1 mm length window to active acoustic and net sample data collected during an Antarctic krill biomass survey in CCAMLR Division 58.4.2 (62 – 67°S; 55 – 80°E, with a survey area of 775,732 km2) performed between February – March 2021. We found that 77% of the total estimated biomass was attributable to krill of length 14 – 49 mm. The largest biomass of krill in a single length bin was estimated as 340,000 t (95% CI: 148,000 - 408,000 t) and was found in the 49 mm length bin (i.e., 48.5 to 49.5 mm). This method will allow future surveys (with sufficient data) to estimate biomass of krill on a per-length basis along with associated uncertainty (confidence intervals) derived from net sampling and so may be used to provision size-based ecosystem models with krill biomass.

Phase-space tomography in magnetically confined plasmas

In this paper, a tomography approach aiming at reconstructing a phase-space structure is proposed. For the phase-space resolved diagnostic system, a signal must be decomposed in real-space, velocity-space, and time; therefore, it is challenging to obtain a sufficiently high signal intensity in a single detector bin. To overcome this difficulty, three different sets of data having different integration directions in real-space, velocity-space, and time are simultaneously used, and a reconstruction of the original structure in the phase-space is attempted by a tomographic manner. The proposed method is demonstrated using a synthetic dataset in the actual diagnostic setup in the Large Helical Device. Time evolution of a phase-space perturbation induced by the Landau damping, which is caused by energetic particle-driven magnetohydrodynamic bursts, is successfully reconstructed by this method. Robustness against realistic diagnostic noise is also presented.

Modeling tire-soil compression resistance on artificial soil using the scaling law of pressure-soil sinkage relationship

Semi-empirical traction models utilize soil parameters estimated from ASABE cone and flat plate soil sinkage data; however, limited studies apply the scaling law of the soil measurement tool to a full-scale tire-to-soil system for various initial soil conditions. This study investigated the effects of three scaled plates (size and shape) and two soil bulk density conditions on pressure-sinkage relationships in artificial soil. Rectangular estimated tire-soil shape and a contact area of 484 cm2 were measured from vertical loading of an LT235/75R15 tire (179 kPa inflation pressure and 8 kN vertical load) in a soil bin test on an artificial soil. Pressure-sinkage data were collected on an artificial soil column at 1.21 Mg/m3 soil bulk density (66% of Proctor density) and 1.41 Mg/m3 soil bulk density (75% of Proctor density) initial conditions using circular, rectangular, and square plates, each at three scaled areas (λ = 0.5, λ = 0.25, and λ = 0.125, where λ = 1 is the tire-soil estimated footprint area from the single tire soil bin test). A scaling law with a strong correlation was established between the geometric scale and the energy expended in compressing the soil. The plate pressure data for λ = 0.125 exhibited a relatively linear increase in pressure as depth increased for loose soil, similar to the soil cone penetrometer data. The pressure-sinkage data for λ = 0.5 exhibited a trend similar to existing models, but coefficients differed for the two initial soil bulk densities. The study demonstrates applying a scaling law to simulate a tire-soil system on soft and dense soils.

A Deep Learning-Based approach to Segregate Solid Waste Generated in Residential Areas

Residential waste is a substantial contributor to solid waste generation, which is approximately around 36.5 million tons annually in India. The waste created in households is not separated at the source. All waste is accumulated in a single waste bin and stashed in a nearby public waste bin, resulting in a massive amount of waste being dumped in landfills and also infused with other types of waste, causing environmental pollution. The core objective of this research is to develop a household waste segregator using the TensorFlow object detection model and Arduino microcontroller. The SSD MobileNet V2 model has been trained with a household dataset consisting of paper, plastic, metal, organic waste, glass, and one more additional empty class to detect whether waste is placed for detection or not. This proposed system can predict the waste class and segregate it into their specific dustbin with mean Average Precision (mAP) and recall of 86.5% and 88.3%, respectively. Waste segregation and recycling can reduce landfills, lower carbon footprints, increase recycling, recover value from garbage, and lower greenhouse gases emitted from waste. Segregation at the source will reduce the cost of the segregation process carried by the municipal solid waste management.

IMD-MTFC: Image-Domain Material Decomposition via Material-Image Tensor Factorization and Clustering for Spectral CT

Spectral computed tomography (CT) provides multispectral X-ray information that can be used for quantitative material-specific imaging compared to the conventional CT. However, the low-count photon rate in a single energy bin may lead to highly noisy measurements with compromised material contrast and accuracy. Moreover, the complicated material decomposition process is an ill-posed inverse problem, which is sensitive to noise. In this work, we develop an image-domain material decomposition method via material-image tensor factorization and clustering (IMD-MTFC) for spectral CT to obtain high-precision material-specific images. Specifically, a set of image patches is extracted from the normalized material-specific image tensors decomposed by the direct inversion (DI). Then, each of them is clustered in a given nonlocal neighboring area to explore the nonlocal self-similarity of material-specific images. Furthermore, the low-rank regularized Kronecker-basis-representation tensor factorization is employed to incorporate the sparsity and redundant correlation across the material-specific images. The split-Bregman is employed to optimize the model by dividing it into several subproblems. The performance of our method is validated with numerically simulated mouse projections, physical phantom, and preclinical experiments. The results confirm that the IMD-MTFC method outperforms other state-of-the-art competing methods.

Unique Assembly Verification in Two-Handed Self-Assembly

One of the most fundamental and well-studied problems in Tile Self-Assembly is the Unique Assembly Verification (UAV) problem. This algorithmic problem asks whether a given tile system uniquely assembles a specific assembly. The complexity of this problem in the 2-Handed Assembly Model (2HAM) at a constant temperature is a long-standing open problem since the model was introduced. Previously, only membership in the class coNP was known and that the problem is in P if the temperature is one (\(\tau =1\)). The problem is known to be hard for many generalizations of the model, such as allowing one step into the third dimension or allowing the temperature of the system to be a variable, but the most fundamental version has remained open. In this paper, we prove the UAV problem in the 2HAM is hard even with a small constant temperature (\(\tau = 2\)), and finally answer the complexity of this problem (open since 2013). Further, this result proves that UAV in the staged self-assembly model is coNP-complete with a single bin and stage (open since 2007), and that UAV in the q-tile model is also coNP-complete (open since 2004). We reduce from Monotone Planar 3-SAT with Neighboring Variable Pairs, a special case of 3SAT recently proven to be NP-hard. We accompany this reduction with a positive result showing that UAV is solvable in polynomial time with the promise that the given target assembly will have a tree-shaped bond graph, i.e., contains no cycles. We provide a \(\mathcal {O}(n^5)\) algorithm for UAV on tree-bonded assemblies when the temperature is fixed to 2, and a \(\mathcal {O}(n^5\log \tau )\) time algorithm when the temperature is part of the input.

A Matheuristic Approach to the Integration of Three-Dimensional Bin Packing Problem and Vehicle Routing Problem with Simultaneous Delivery and Pickup

This work presents a hybrid approach to solve a distribution problem of a Portuguese company in the automotive industry. The objective is to determine the minimum cost for daily distribution operations, such as collecting and delivering goods to multiple suppliers. Additional constraints are explicitly considered, such as time windows and loading constraints due to the limited capacity of the fleet in terms of weight and volume. An exhaustive review of the state of the art was conducted, presenting different typology schemes from the literature for the pickup and delivery problems in the distribution field. Two mathematical models were integrated within a matheuristic approach. One model reflects the combination of the Vehicle Routing Problem with Simultaneous Delivery and Pickup with the Capacitated Vehicle Routing Problem with Time Windows. The second one aims to pack all the items to be delivered onto the pallets, reflecting a three-dimensional single bin size Bin Packing Problem. Both formulations proposed—a commodity-flow model and a formulation of the Three-Dimensional Packing Problem must be solved within the matheuristic. All the approaches were tested using real instances from data provided by the company. Additional computational experiments using benchmark instances were also performed.

Modelling grain-size distributions in C-type shocks using a discrete power-law model

In this paper we discuss the implementation of a discrete, piecewise power-law grain-size distribution method into a numerical multifluid MHD code as described in Sumpter and Van Loo (2020). Such a description allows to capture the full size range of dust grains and their dynamical effects. The only assumptions are that grains within a single discrete bin have the same velocity and charge. We test the implementation by modelling plane-parallel C-type shocks and compare the results with shock models of multispecies grain models. We find that both the discrete and multispecies grain models converge to the same shock profile. However, the convergence for the discrete models is faster than for the multispecies grain models. For the pure advection models a single discrete bin is sufficient, while the multispecies grain models need a minimum of 8 grain species. When including grain sputtering the necessary number of discrete bins increases to 4, as the grain distribution cannot be described by a single power-law as in the advection models. The multispecies grain models still need more grain species to model the distribution, but the number does not increase compared to the pure advection models. Our results show that modelling the grain distribution function using a discrete distribution reduces the computational cost needed to capture the grain physics significantly.

A Numerical Study on Heat and Mass Transfer Coupled with Respiration Reaction within Stacked Spherical Postharvest Produce: Spatial Distribution and Temporal Variation

Reaction rate of respiration in postharvest horticultural produce is dependent on coupling effects of heat and mass transfer. The present work is aimed to develop a numerical model of heat and mass transfer coupled with respiration reaction for forced-air cooling (FAC) and modified atmosphere (MA) storage of postharvest produce. Wind tunnel model with a single bin of stacked spherical produce therein is used as a benchmark case to analyze spatial distribution and temporal variation of heat and mass transfer characteristics. Competitive diffusion of O2 results in the highest O2 partial pressure around 8 kPa between produce surface and core at 10 min during FAC combined with MA. With positions of such peaks moving inward, similar O2 partial pressure around 4 kPa is obtained in the vicinity of produce core at 30 min. This indicates comparative effects of convective removing and reaction consumption of O2. During the same process, under simultaneous effects of low temperature and O2 content, peak values of respiration heat between produce surface and core are generally below 60 W/m3 at 10 min, while two peaks in each produce individual basically merge together with reduced values to around 40 W/m3 at 20 min.

Packing batches of cubes into a single bin

In λ-packing items are grouped in batches. Items arrive one by one (online) and they are stored in a buffer until either the total volume of stored items is greater than or equal to λ or all items have already arrived. Then items from the buffer are packed offline into a unit capacity bin and the buffer is emptied. We show that any sequence of cubes with total volume not greater than 1/4 can be 1/8-packed into a single bin (a unit cube).

Identify Patterns in Online Bin Packing Problem: An Adaptive Pattern-Based Algorithm

Bin packing is a typical optimization problem with many real-world application scenarios. In the online bin packing problem, a sequence of items is revealed one at a time, and each item must be packed into a bin immediately after its arrival. Inspired by duality in optimization, we proposed pattern-based adaptive heuristics for the online bin packing problem. The idea is to predict the distribution of items based on packed items, and to apply this information in packing future arrival items in order to handle uncertainty in online bin packing. A pattern in bin packing is a combination of items that can be packed into a single bin. Patterns selected according to past items are adopted and periodically updated in scheduling future items in the algorithm. Symmetry in patterns and the stability of patterns in the online bin packing problem are discussed. We have implemented the algorithm and compared it with the Best-Fit in a series of experiments with various distribution of items to show its effectiveness.

Pseudorapidity dependence of the p T spectra of charged hadrons in pp collisions at s = 0.9 and 2.36 TeV

Abstract We report the predictions of different Monte Carlo event generators including HIJING, Pythia, and QGSJETII in comparison with the experimental data measured by the CMS Collaboration at CERN in proton–proton (pp) collisions at center-of-mass energy s = 0.9 and 2.36 TeV. The CMS experimental transverse momentum (p T or p ⊥) spectra of charged hadrons were measured for pseudorapidity range 0 ⩽ η ⩽ 2.4 with bin width of η = 0.2 (for p T from 0.1 to 2 GeV/c) and a single bin of η for |η| &lt; 2.4 (for p T from 0.1 to 4 GeV/c). Pythia reproduced the p T spectra with reasonable agreement for most of the p T range. It depicts better results in the case of the |η| &lt; 2.4 than HIJING and QGSJETII which could reproduce the spectra in a limited p T range. Furthermore, to analyze the p T spectra of charged hadrons measured by the CMS Collaboration, we used a three-component function (structured from the Boltzmann distribution) and the q-dual function (from the q-dual statistics) to extract parameter values relevant for the study of bulk properties of hadronic matter at high energy. We have also applied the two analytic functions over the model predictions. The values extracted by the functions from the HIJING and Pythia models are closer to the experimental data than the QGSJETII model. Although the models could reproduce the p T spectra of all charged particles in some of the p T range but none of them could reproduce the distributions over the entire p T range and in all the pseudorapidity regions.