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Abstract A major challenge in understanding the process of nucleus-nucleus interactions is the examination of the processes that occur in the participant and spectator areas of interacting nuclei, considering the central nature of the reactions. Nearly thresholdless detection of the secondary charged particles is made possible by nuclear emulsion detectors (NED), which provide a complete 4πangular coverage. This work is mainly concerned with the multiplicity distributions (MD) and fluctuation of the average multiplicities of secondary charged particles (slow proton, fast proton, and shower) brought about by the collision of⁸⁴Kr-nuclei with emulsion nuclei at 1 A GeV. The MD of these particles has been computed by use of a modified cascade evaporation model (MCEM). The MD of each of the several charged secondary particles is correlated and analyzed. The observation demonstrates that the theoretical calculation results for the average multiplicities of shower particles, fast and slow protons agree well with the experimental data. Correlations seen experimentally between the multiplicities of different emitted particles are faithfully reproduced by the MCEM. There is good agreement between the experimental data and the theoretical calculation results.

A major challenge in understanding the process of nucleus-nucleus interactions is the examination of the processes that occur in the participant and spectator areas of interacting nuclei, considering the central nature of the reactions. Nearly thresholdless detection of the secondary charged particles is made possible by nuclear emulsion detectors (NED), which provide a complete 4π angular coverage. This work is mainly concerned with the multiplicity distributions (MD) and fluctuation of the average multiplicities of secondary charged particles (slow proton, fast proton, and shower) brought about by the collision of [Formula: see text]-nuclei with emulsion nuclei at 1 A GeV. The MD of these particles has been computed by use of a modified cascade evaporation model (MCEM). The MD of each of the several charged secondary particles is correlated and analyzed. The observation demonstrates that the theoretical calculation results for the average multiplicities of shower particles, fast and slow protons agree well with the experimental data. Correlations seen experimentally between the multiplicities of different emitted particles are faithfully reproduced by the MCEM. There is good agreement between the experimental data and the theoretical calculation results.

The main focus of this work is on the systematic examination of the dynamical fluctuation detectable by two-particle rapidity correlations σc2 in the forward–backward (FB) pseudo-rapidity windows by analyzing the experimental data obtained from the interactivity of 84Kr nuclei with AgBr target nuclei of nuclear emulsion detector (NED) at 1 A GeV. The FB multiplicity fluctuation of created pions in NED has been also conducted using the highly intense quantity technique ΣFB. The results are compared with other available experimental observations and found to be consistence. When compared to the higher energy data that have been previously analyzed, the results on very intensive fluctuation measures at a lower energy show substantially more variations.

Distributions sensitive to the underlying event in QCD jet events have been measured with the ATLAS detector at the LHC, based on 37 pb - 1 of proton–proton collision data collected at a centre-of-mass energy of 7  TeV . Charged-particle mean p T and densities of all-particle E T and charged-particle multiplicity and p T have been measured in regions azimuthally transverse to the hardest jet in each event. These are presented both as one-dimensional distributions and with their mean values as functions of the leading-jet transverse momentum from 20 to 800  GeV . The correlation of charged-particle mean p T with charged-particle multiplicity is also studied, and the E T densities include the forward rapidity region; these features provide extra data constraints for Monte Carlo modelling of colour reconnection and beam-remnant effects respectively. For the first time, underlying event observables have been computed separately for inclusive jet and exclusive dijet event selections, allowing more detailed study of the interplay of multiple partonic scattering and QCD radiation contributions to the underlying event. Comparisons to the predictions of different Monte Carlo models show a need for further model tuning, but the standard approach is found to generally reproduce the features of the underlying event in both types of event selection.

We calculate the strongly intensive observables for multiplicities in two rapidity windows in the model with independent identical strings taking into account the charge sign of particles. We express the observables through the string pair correlation functions describing the correlations between the same and opposite sign particles produced in a string decay. We extract these charge-wise string two-particle correlation functions from the ALICE data on the forward-backward correlations and the balance function. Using them we predict the behavior of the charge-wise strongly intensive observables in the model with independent identical strings. We also show that the observable between multiplicities in two acceptance windows separated in rapidity, which is a strongly intensive in the case with independent identical strings, loses this property, when we take into account string fusion effects and a formation of strings of a few different types takes place in a collision. We predict the changes in the behaviour of this observable with energy and collision centrality, arising due to the string fusion phenomena.

This paper presents an analysis on the basis of factorial correlators and oscillatory multiplicity moments among the pions extracted from Monte Carlo (MC) generated PYTHIA(v8.3), AMPT(v2.26) and UrQMD(v3.4) models in pp collisions at different center-of-mass (c.m) energies s= 2.76 – 13 TeV. During this investigation, we have found the presence of short-range correlation and our overall findings are accordant with the predictions of the α-model and log-normal approximation which indicates the existence of intermittent nature of self-similar dynamical fluctuations. Short-range Correlation strength gradually decreases with the increase in collision energies from s = 2.76-13 TeV is observed. From the analysis of oscillatory multiplicity moments, the ratios Hq (cumulant over factorial moments Kq/Fq) have been derived for each MC generated Model with LHC energies. It is extremely interesting to observe that the oscillations from PYTHIA and UrQMD are quite different from the AMPT model at s = 13 TeV.

Background The genetic diversity of Plasmodium falciparum provides the parasite with many effective immune evasion and drug resistance mechanisms. This phenomenon is a major problem in eradicating malaria globally. This study aimed to assess merozoite surface protein 2 polymorphisms in P. falciparum isolates from Northwest Ethiopia. Method A cross-sectional study was conducted to assess merozoite surface protein 2 polymorphisms in P. falciparum isolates from selected malarious areas in Northwest Ethiopia from April to June 2021. A convenience sampling technique was used to select 150 study participants. A finger prick blood sample was collected to prepare blood films and dried blood spots for molecular genotyping. The merozoite surface protein 2 allele frequency and multiplicity of infection were computed. Linear regression was employed to evaluate the associations between the multiplicity of infection, parasite density, and age by calculating Spearman’s rank correlation coefficients. A P value < 0.05 was considered to indicate statistical significance. Result Polymorphism analysis was performed on 126 P. falciparum isolates. There were 38 different merozoite surface protein 2 alleles, 20 of which corresponded to the IC/3D7 allelic family and 18 to the FC27 allelic family. Most patients contained multiple infections, and the mean multiplicity of infection was 3.46. There was no statistically significant difference in the multiplicity of infection in relation to the age of patients ( P =  0.646). However, a statistically significant correlation was found between parasite density and the multiplicity of infection ( P  = 0.046). The heterozygosity index for merozoite surface protein 2 was 0.948. Conclusion This study showed that P. falciparum isolates contain multiple genotypes with a high multiplicity of infections and mixed strain infection, suggesting extensive genetic diversity and a high level of malaria transmission. This genetic variability could complicate malaria treatment and control efforts, as it can facilitate the emergence and spread of drug-resistant strains. Consequently, the findings highlight the complex malaria epidemiology in the region and emphasize the need for intensified efforts to control malaria transmission and prevent the probable emergence of drug resistance alleles in the study area.

A procedure is presented for the substantial simplification of 2D constant-time 13C−1H heteronuclear single-quantum correlation (HSQC) spectra of 13C-enriched proteins. In this approach, a single pulse sequence simultaneously records eight sub-spectra wherein the phases of the NMR signals depend on spin topology. Signals from different chemical groups are then stratified into different sub-spectra through linear combination based on Hadamard encoding of 13CHn multiplicity (n = 1, 2, and 3) and the chemical nature of neighboring 13C nuclei (aliphatic, carbonyl/carboxyl, aromatic). This results in five sets of 2D NMR spectra containing mutually exclusive signals from: (i) 13Cβ−1Hβ correlations of asparagine and aspartic acid, 13Cγ−1Hγ correlations of glutamine and glutamic acid, and 13Cα−1Hα correlations of glycine, (ii) 13Cα−1Hα correlations of all residues but glycine, and (iii) 13Cβ−1Hβ correlations of phenylalanine, tyrosine, histidine, and tryptophan, and the remaining (iv) aliphatic 13CH2 and (v) aliphatic 13CH/13CH3 resonances. As HSQC is a common element of many NMR experiments, the spectral simplification proposed in this article can be straightforwardly implemented in experiments for resonance assignment and structure determination and should be of widespread utility.

Background Genomic surveillance of malaria parasites offers important insights into the impact of interventions on transmission reduction and changes in pathogen populations over time, especially in low-transmission areas. However, such surveillance faces challenges in high-transmission regions. Detecting temporal changes in transmission in high-transmission settings requires analytical methods tailored to high-diversity parasite populations that can differentiate between superinfection (infection through multiple mosquito bites, each bearing an unrelated strain) and co-transmission (infection through a single mosquito bite bearing more than one strain). Methods This study applied a previously developed novel Next Generation Sequencing (NGS) 24-SNP barcode assay for genotyping smear-positive samples obtained from a 2017 cross-sectional survey in the Asembo area, western Kenya, building on previous work on samples collected in the surveys conducted in 1996, 2001, 2007, and 2012. Algorithms StrainRecon and STIM were used to identify parasite strains within a sample and measure multiplicity of infection (MOI). Population genetic metrics of F ST (Fixation Index), strain-relatedness by IBD (Identity by Descent), H s (Modified Heterozygosity) and N e (Effective Population Size) were evaluated using the same 24-SNP data. This study further explored a novel slope metric of the relationship between within-host strain relatedness and MOI to infer superinfection and co-transmission. Temporal changes in the above metrics were assessed. Results There was no significant differentiation in F ST , H s , N e , and strain-relatedness at the population level over time. In contrast, the average MOI significantly decreased from 4.32 in 1996 to 3.34 in 2012, although it increased to 3.49 in 2017. Insecticide-treated bednet distribution campaigns from 1997 to 2017 did track these temporal changes in MOI. Additionally, the value of strain relatedness within-host (IBD) was inversely correlated with MOI (number of strains), and the change in the inverse relationship (within-host slopes) over time was verified by two different correlation analysis and modelling. The temporal trends in this within-host slope metric suggested that transmission dynamics shifted towards co-transmission from 2001 to 2012, and then returned to similar levels of superinfection in 2017 as in 1996. Conclusion The within-host MOI, IBD-based strain-relatedness, and their mathematical relationship (slope) provide useful metrics for understanding the transmission dynamics in our study. Notably, this study presents the first simple slope-based method using 24-SNP barcodes to distinguish superinfection from co-transmission in a high transmission area, warranting further evaluation of the novel tool in other high transmission settings.

CO2 adsorption on subnanometric metal clusters is highly sensitive to the computational protocol used to describe the potential energy surface, particularly when several low-lying geometries and spin states are accessible. In this work, CO2 adsorption on Cu4 and Sc4 clusters was investigated using density functional theory (DFT) to evaluate how the choice of functional/basis-set protocol, spin multiplicity, initial geometry, and vibrational stability affects the predicted adsorption behavior. Four representative computational protocols (TPSSh, r2SCAN-3c, PBE-D4/def2-TZVP, and PBE0-SDD) were assessed for isolated clusters and cluster–CO2 complexes. The lowest harmonic vibrational frequency, ωmin, was used as a diagnostic criterion to distinguish true minima from unstable or weakly defined stationary points. Selected cases were also cross-checked using the ORCA and Gaussian quantum-chemistry packages to assess whether comparable computational settings yielded consistent stationary-point character. The results show that Cu4 generally exhibits weak CO2 binding, whereas Sc4 displays stronger but more protocol-dependent adsorption, consistent with its higher structural flexibility and more pronounced Lewis-acid character. Low-frequency and imaginary modes were found in several optimized structures, indicating that adsorption energies should not be interpreted without prior vibrational validation. The comparison also shows that variations in functional/basis-set treatment and spin multiplicity can alter both the optimized geometry and the predicted adsorption strength. Therefore, CO2 adsorption on small metal clusters should be discussed using combined structural, vibrational, and energetic criteria rather than electronic adsorption energies alone. Overall, this study provides a protocol-oriented framework for evaluating the reliability of DFT predictions in CO2 adsorption on Cu4 and Sc4 clusters.