Flow reconstruction by multiresolution optimization of a discrete loss with automatic differentiation.

We present a potent computational method for the solution of inverse problems in fluid mechanics. We consider inverse problems formulated in terms of a deterministic loss function that can accommodate data and regularization terms. We introduce a multigrid decomposition technique that accelerates the convergence of gradient-based methods for optimization problems with parameters on a grid. We incorporate this multigrid technique to the Optimizing a DIscrete Loss (ODIL) framework. The multiresolution ODIL (mODIL) accelerates by an order of magnitude the original formalism and improves the avoidance of local minima. Moreover, mODIL accommodates the use of automatic differentiation for calculating the gradients of the loss function, thus facilitating the implementation of the framework. We demonstrate the capabilities of mODIL on a variety of inverse and flow reconstruction problems: solution reconstruction for the Burgers equation, inferring conductivity from temperature measurements, and inferring the body shape from wake velocity measurements in three dimensions. We also provide a comparative study with the related, popular Physics-Informed Neural Networks (PINNs) method. We demonstrate that mODIL has three to five orders of magnitude lower computational cost than PINNs in benchmark problems including simple PDEs and lid-driven cavity problems. Our results suggest that mODIL is a very potent, fast and consistent method for solving inverse problems in fluid mechanics.

Upper Palaeolithic Siberian genome reveals dual ancestry of Native Americans.

The origins of the First Americans remain contentious. Although Native Americans seem to be genetically most closely related to east Asians, there is no consensus with regard to which specific Old World populations they are closest to. Here we sequence the draft genome of an approximately 24,000-year-old individual (MA-1), from Mal'ta in south-central Siberia, to an average depth of 1×. To our knowledge this is the oldest anatomically modern human genome reported to date. The MA-1 mitochondrial genome belongs to haplogroup U, which has also been found at high frequency among Upper Palaeolithic and Mesolithic European hunter-gatherers, and the Y chromosome of MA-1 is basal to modern-day western Eurasians and near the root of most Native American lineages. Similarly, we find autosomal evidence that MA-1 is basal to modern-day western Eurasians and genetically closely related to modern-day Native Americans, with no close affinity to east Asians. This suggests that populations related to contemporary western Eurasians had a more north-easterly distribution 24,000 years ago than commonly thought. Furthermore, we estimate that 14 to 38% of Native American ancestry may originate through gene flow from this ancient population. This is likely to have occurred after the divergence of Native American ancestors from east Asian ancestors, but before the diversification of Native American populations in the New World. Gene flow from the MA-1 lineage into Native American ancestors could explain why several crania from the First Americans have been reported as bearing morphological characteristics that do not resemble those of east Asians. Sequencing of another south-central Siberian, Afontova Gora-2 dating to approximately 17,000 years ago, revealed similar autosomal genetic signatures as MA-1, suggesting that the region was continuously occupied by humans throughout the Last Glacial Maximum. Our findings reveal that western Eurasian genetic signatures in modern-day Native Americans derive not only from post-Columbian admixture, as commonly thought, but also from a mixed ancestry of the First Americans.

Human Y Chromosome Haplogroup N: A Non-trivial Time-Resolved Phylogeography that Cuts across Language Families.

The paternal haplogroup (hg) N is distributed from southeast Asia to eastern Europe. The demographic processes that have shaped the vast extent of this major Y chromosome lineage across numerous linguistically and autosomally divergent populations have previously been unresolved. On the basis of 94 high-coverage re-sequenced Y chromosomes, we establish and date a detailed hg N phylogeny. We evaluate geographic structure by using 16 distinguishing binary markers in 1,631 hg N Y chromosomes from a collection of 6,521 samples from 56 populations. The more southerly distributed sub-clade N4 emerged before N2a1 and N3, found mostly in the north, but the latter two display more elaborate branching patterns, indicative of regional contrasts in recent expansions. In particular, a number of prominent and well-defined clades with common N3a3'6 ancestry occur in regionally dissimilar northern Eurasian populations, indicating almost simultaneous regional diversification and expansion within the last 5,000 years. This patrilineal genetic affinity is decoupled from the associated higher degree of language diversity.

Between Lake Baikal and the Baltic Sea: genomic history of the gateway to Europe.

BACKGROUND: The history of human populations occupying the plains and mountain ridges separating Europe from Asia has been eventful, as these natural obstacles were crossed westward by multiple waves of Turkic and Uralic-speaking migrants as well as eastward by Europeans. Unfortunately, the material records of history of this region are not dense enough to reconstruct details of population history. These considerations stimulate growing interest to obtain a genetic picture of the demographic history of migrations and admixture in Northern Eurasia. RESULTS: We genotyped and analyzed 1076 individuals from 30 populations with geographical coverage spanning from Baltic Sea to Baikal Lake. Our dense sampling allowed us to describe in detail the population structure, provide insight into genomic history of numerous European and Asian populations, and significantly increase quantity of genetic data available for modern populations in region of North Eurasia. Our study doubles the amount of genome-wide profiles available for this region. We detected unusually high amount of shared identical-by-descent (IBD) genomic segments between several Siberian populations, such as Khanty and Ket, providing evidence of genetic relatedness across vast geographic distances and between speakers of different language families. Additionally, we observed excessive IBD sharing between Khanty and Bashkir, a group of Turkic speakers from Southern Urals region. While adding some weight to the "Finno-Ugric" origin of Bashkir, our studies highlighted that the Bashkir genepool lacks the main "core", being a multi-layered amalgamation of Turkic, Ugric, Finnish and Indo-European contributions, which points at intricacy of genetic interface between Turkic and Uralic populations. Comparison of the genetic structure of Siberian ethnicities and the geography of the region they inhabit point at existence of the "Great Siberian Vortex" directing genetic exchanges in populations across the Siberian part of Asia. Slavic speakers of Eastern Europe are, in general, very similar in their genetic composition. Ukrainians, Belarusians and Russians have almost identical proportions of Caucasus and Northern European components and have virtually no Asian influence. We capitalized on wide geographic span of our sampling to address intriguing question about the place of origin of Russian Starovers, an enigmatic Eastern Orthodox Old Believers religious group relocated to Siberia in seventeenth century. A comparative reAdmix analysis, complemented by IBD sharing, placed their roots in the region of the Northern European Plain, occupied by North Russians and Finno-Ugric Komi and Karelian people. Russians from Novosibirsk and Russian Starover exhibit ancestral proportions close to that of European Eastern Slavs, however, they also include between five to 10 % of Central Siberian ancestry, not present at this level in their European counterparts. CONCLUSIONS: Our project has patched the hole in the genetic map of Eurasia: we demonstrated complexity of genetic structure of Northern Eurasians, existence of East-West and North-South genetic gradients, and assessed different inputs of ancient populations into modern populations.

Solving inverse problems in physics by optimizing a discrete loss: Fast and accurate learning without neural networks.

In recent years, advances in computing hardware and computational methods have prompted a wealth of activities for solving inverse problems in physics. These problems are often described by systems of partial differential equations (PDEs). The advent of machine learning has reinvigorated the interest in solving inverse problems using neural networks (NNs). In these efforts, the solution of the PDEs is expressed as NNs trained through the minimization of a loss function involving the PDE. Here, we show how to accelerate this approach by five orders of magnitude by deploying, instead of NNs, conventional PDE approximations. The framework of optimizing a discrete loss (ODIL) minimizes a cost function for discrete approximations of the PDEs using gradient-based and Newton's methods. The framework relies on grid-based discretizations of PDEs and inherits their accuracy, convergence, and conservation properties. The implementation of the method is facilitated by adopting machine-learning tools for automatic differentiation. We also propose a multigrid technique to accelerate the convergence of gradient-based optimizers. We present applications to PDE-constrained optimization, optical flow, system identification, and data assimilation. We compare ODIL with the popular method of physics-informed neural networks and show that it outperforms it by several orders of magnitude in computational speed while having better accuracy and convergence rates. We evaluate ODIL on inverse problems involving linear and nonlinear PDEs including the Navier-Stokes equations for flow reconstruction problems. ODIL bridges numerical methods and machine learning and presents a powerful tool for solving challenging, inverse problems across scientific domains.

A Learnable Prior Improves Inverse Tumor Growth Modeling.

Biophysical modeling, particularly involving partial differential equations (PDEs), offers significant potential for tailoring disease treatment protocols to individual patients. However, the inverse problem-solving aspect of these models presents a substantial challenge, either due to the high computational requirements of model-based approaches or the limited robustness of deep learning (DL) methods. We propose a novel framework that leverages the unique strengths of both approaches in a synergistic manner. Our method incorporates a DL ensemble for initial parameter estimation, facilitating efficient downstream evolutionary sampling initialized with this DL-based prior. We showcase the effectiveness of integrating a rapid deep-learning algorithm with a high-precision evolution strategy in estimating brain tumor cell concentrations from magnetic resonance images. The DL-Prior plays a pivotal role, significantly constraining the effective sampling-parameter space. This reduction results in a fivefold convergence acceleration and a Dice-score of 95.

Computing foaming flows across scales: From breaking waves to microfluidics.

Crashing ocean waves, cappuccino froths, and microfluidic bubble crystals are examples of foamy flows. Foamy flows are critical in numerous natural and industrial processes and remain notoriously difficult to compute as they involve coupled, multiscale physical processes. Computations need to resolve the interactions of the bubbles separated by stable thin liquid films. We present the multilayer volume-of-fluid method (Multi-VOF) that advances the state of the art in simulation capabilities of foamy flows. The method introduces a scheme to handle multiple bubbles that do not coalesce. Multi-VOF is verified and validated with experimental results and complemented with open-source software. We demonstrate capturing of crystalline structures of bubbles in realistic microfluidics devices and foamy flows involving tens of thousands of bubbles in a waterfall. The present technique extends the classical volume-of-fluid methodology and allows for large-scale predictive simulations of flows with multiple interfaces.

Determination of the phylogenetic origins of the Árpád Dynasty based on Y chromosome sequencing of Béla the Third.

We set out to identify the origins of the Árpád Dynasty based on genome sequencing of DNA derived from the skeletal remains of Hungarian King Béla III (1172-1196) and eight additional individuals (six males, two females) originally interred at the Royal Basilica of Székesfehérvár. Y-chromosome analysis established that two individuals, Béla III and HU52 assign to haplogroups R-Z2125 whose distribution centres near South Central Asia with subsidiary expansions in the regions of modern Iran, the Volga Ural region and the Caucasus. Out of a cohort of 4340 individuals from these geographic areas, we acquired whole-genome data from 208 individuals derived for the R-Z2123 haplogroup. From these data we have established that the closest living kin of the Árpád Dynasty are R-SUR51 derived modern day Bashkirs predominantly from the Burzyansky and Abzelilovsky districts of Bashkortostan in the Russian Federation. Our analysis also reveals the existence of SNPs defining a novel Árpád Dynasty specific haplogroup R-ARP. Framed within the context of a high resolution R-Z2123 phylogeny, the ancestry of the first Hungarian royal dynasty traces to the region centering near Northern Afghanistan about 4500 years ago and identifies the Bashkirs as their closest kin, with a separation date between the two populations at the beginning of the first millennium CE.

Opening-wedge V-shaped corrective osteotomy for malunited fractures of metacarpal bones.

Currently, the most commonly used method of treatment of patients with fractures of the metacarpal bones is closed reposition with immobilization of short-arm cast. This often leads to dislocation of fragments, their malunion, which leads to wrist functionality disorders and reduces the quality of patients' life. The main way to eliminate the deformities ‒ osteotomy of the metacarpal bones, followed by osteosynthesis. Purpose of the study ‒ to give a clinical assessment of the results of surgical treatment of patients with posttraumatic deformities of the Metacarpals, based on the use of a new method of corrective osteotomy. Methods. The proposed new method V-shape open angle of the osteotomy of the metacarpal bones whit malunion, followed by subsequent fixation of mini-plates (RF Patent for the invention No. 2651893 from February 20, 2017). The long-term results (in one year) of treatment of five operated patients with the consequences of closed fractures of the fourth and fifth metacarpal bones are presented. The state of the bone corn was studied by standard x-rays of the hand in two projections and by computed tomography. The angular deformity of the fragments was measured, the range of active movements in the metacarpophalangeal joints and the grip force were determined. Pain intensity was assessed by visual analogue scale, day-by-day activity-by DASH test, the results were divided into excellent, good, satisfactory and unsatisfactory by Buechler table. The frequency and nature of postoperative complications were also analyzed. Results. In all clinical cases, positive outcomes were obtained: angular deformity was corrected, the range of motion in the metacarpophalangeal joints and grip strength improved, and the functional parameters of the hand increased. In one clinical case stiffness was formed in the metacarpophalangeal joint, which required revision operation. Summary. Corrective V-shaped osteotomy of the metacarpal bones at the top of their deformation allows to restore the alignment of the fragments and prevent shortening of the bone. The use of stable osteosynthesis with low-profile mini-plates makes possible early functional management of patients, which prevents stiffness in the joints of the fingers.

Structural Variability, Expression Profile, and Pharmacogenetic Properties of TMPRSS2 Gene as a Potential Target for COVID-19 Therapy.

The human serine protease serine 2 TMPRSS2 is involved in the priming of proteins of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and represents a possible target for COVID-19 therapy. The TMPRSS2 gene may be co-expressed with SARS-CoV-2 cell receptor genes angiotensin-converting enzyme 2 (ACE2) and Basigin (BSG), but only TMPRSS2 demonstrates tissue-specific expression in alveolar cells according to single-cell RNA sequencing data. Our analysis of the structural variability of the TMPRSS2 gene based on genome-wide data from 76 human populations demonstrates that a functionally significant missense mutation in exon 6/7 in the TMPRSS2 gene is found in many human populations at relatively high frequencies, with region-specific distribution patterns. The frequency of the missense mutation encoded by rs12329760, which has previously been found to be associated with prostate cancer, ranged between 10% and 63% and was significantly higher in populations of Asian origin compared with European populations. In addition to single-nucleotide polymorphisms, two copy number variants were detected in the TMPRSS2 gene. A number of microRNAs have been predicted to regulate TMPRSS2 and BSG expression levels, but none of them is enriched in lung or respiratory tract cells. Several well-studied drugs can downregulate the expression of TMPRSS2 in human cells, including acetaminophen (paracetamol) and curcumin. Thus, the interactions of TMPRSS2 with SARS-CoV-2, together with its structural variability, gene-gene interactions, expression regulation profiles, and pharmacogenomic properties, characterize this gene as a potential target for COVID-19 therapy.

Self-diffusion coefficient in smoothed dissipative particle dynamics.

Smoothed dissipative particle dynamics (SDPD) is a novel coarse grained method for the numerical simulation of complex fluids. It has considerable advantages over more traditional particle-based methods. In this paper we analyze the self-diffusion coefficient D of a SDPD solvent by using the strategy proposed by Groot and Warren [J. Chem. Phys. 107, 4423 (1997)]. An analytical expression for D in terms of the model parameters is developed and verified by numerical simulations.

Synthetic peptides as a novel approach for detecting antibodies against sand fly saliva.

BACKGROUND: Hosts repeatedly bitten by sand flies develop antibodies against sand fly saliva and screening of these immunoglobulins can be employed to estimate the risk of Leishmania transmission, to indicate the feeding preferences of sand flies, or to evaluate the effectiveness of vector control campaigns. Previously, antibodies to sand fly saliva were detected using whole salivary gland homogenate (SGH) or recombinant proteins, both of which also have their disadvantages. This is the first study on sand flies where short peptides designed based on salivary antigens were successfully utilized for antibody screening. METHODOLOGY/PRINCIPAL FINDINGS: Specific IgG was studied in hosts naturally exposed to Phlebotomus orientalis, the main vector of Leishmania donovani in East Africa. Four peptides were designed by the commercial program EpiQuest-B, based on the sequences of the two most promising salivary antigens, yellow-related protein and ParSP25-like protein. Short amino acid peptides were synthesised and modified for ELISA experiments. Specific anti-P. orientalis IgG was detected in sera of dogs, goats, and sheep from Ethiopia. The peptide OR24 P2 was shown to be suitable for antibody screening; it correlated positively with SGH and its specificity and sensitivity were comparable or even better than that of previously published recombinant proteins. CONCLUSIONS/SIGNIFICANCE: OR24 P2, the peptide based on salivary antigen of P. orientalis, was shown to be a valuable tool for antibody screening of domestic animals naturally exposed to P. orientalis. We suggest the application of this promising methodology using species-specific short peptides to other sand fly-host combinations.

Refining wet lab experiments with in silico searches: A rational quest for diagnostic peptides in visceral leishmaniasis.

BACKGROUND: The search for diagnostic biomarkers has been profiting from a growing number of high quality sequenced genomes and freely available bioinformatic tools. These can be combined with wet lab experiments for a rational search. Improved, point-of-care diagnostic tests for visceral leishmaniasis (VL), early case detection and surveillance are required. Previous investigations demonstrated the potential of IgG1 as a biomarker for monitoring clinical status in rapid diagnostic tests (RDTs), although using a crude lysate antigen (CLA) as capturing antigen. Replacing the CLA by specific antigens would lead to more robust RDTs. METHODOLOGY: Immunoblots revealed L. donovani protein bands detected by IgG1 from VL patients. Upon confident identification of these antigens by mass spectrometry (MS), we searched for evidence of constitutive protein expression and presence of antigenic domains or high accessibility to B-cells. Selected candidates had their linear epitopes mapped with in silico algorithms. Multiple high-scoring predicted epitopes from the shortlisted proteins were screened in peptide arrays. The most promising candidate was tested in RDT prototypes using VL and nonendemic healthy control (NEHC) patient sera. RESULTS: Over 90% of the proteins identified from the immunoblots did not satisfy the selection criteria and were excluded from the downstream epitope mapping. Screening of predicted epitope peptides from the shortlisted proteins identified the most reactive, for which the sensitivity for IgG1 was 84% (95% CI 60-97%) with Sudanese VL sera on RDT prototypes. None of the sera from NEHCs were positive. CONCLUSION: We employed in silico searches to reduce drastically the output of wet lab experiments, focusing on promising candidates containing selected protein features. By predicting epitopes in silico we screened a large number of peptides using arrays, identifying the most promising one, for which IgG1 sensitivity and specificity, with limited sample size, supported this proof of concept strategy for diagnostics discovery, which can be applied to the development of more robust IgG1 RDTs for monitoring clinical status in VL.

Y-chromosomal analysis of clan structure of Kalmyks, the only European Mongol people, and their relationship to Oirat-Mongols of Inner Asia.

Kalmyks, the only Mongolic-speaking population in Europe, live in the southeast of the European Plain, in Russia. They adhere to Buddhism and speak a dialect of the Mongolian language. Historical and linguistic evidence, as well a shared clan names, suggests a common origin with Oirats of western Mongolia; yet, only a limited number of genetic studies have focused on this topic. Here we compare the paternal genetic relationship of Kalmyk clans with ethnographically related groups from Mongolia, Kyrgyzstan and China, within the context of their neighbouring populations. A phylogeny of 37 high-coverage Y-chromosome sequences, together with further genotyping of larger sample sets, reveals that all the Oirat-speaking populations studied here, including Kalmyks, share, as a dominant paternal lineage, Y-chromosomal haplogroup C3c1-M77, which is also present in several geographically distant native Siberian populations. We identify a subset of this clade, C3c1b-F6379, specifically enriched in Kalmyks as well as in Oirat-speaking clans in Inner Asia. This sub-clade coalesces at around 1500 years before present, before the Genghis Khan era, and significantly earlier than the split between Kalmyks and other Oirat speakers about 400 years ago. We also show that split between the dominant hg C variant among Buryats-C3-M407-and that of C3-F6379, took place in the Early Upper Palaeolithic, suggesting an extremely long duration for the dissipation of hg C3-M217 carriers across northern Eurasia, which cuts through today's major linguistic phyla.

Shifts in the Genetic Landscape of the Western Eurasian Steppe Associated with the Beginning and End of the Scythian Dominance.

The Early Iron Age nomadic Scythians have been described as a confederation of tribes of different origins, based on ancient DNA evidence [1-3]. It is still unclear how much of the Scythian dominance in the Eurasian Steppe was due to movements of people and how much reflected cultural diffusion and elite dominance. We present new whole-genome sequences of 31 ancient Western and Eastern Steppe individuals, including Scythians as well as samples pre- and postdating them, allowing us to set the Scythians in a temporal context (in the Western, i.e., Ponto-Caspian Steppe). We detect an increase of eastern (Altaian) affinity along with a decrease in eastern hunter-gatherer (EHG) ancestry in the Early Iron Age Ponto-Caspian gene pool at the start of the Scythian dominance. On the other hand, samples of the Chernyakhiv culture postdating the Scythians in Ukraine have a significantly higher proportion of Near Eastern ancestry than other samples of this study. Our results agree with the Gothic source of the Chernyakhiv culture and support the hypothesis that the Scythian dominance did involve a demic component.

Smoothed dissipative particle dynamics model for polymer molecules in suspension.

We present a model for a polymer molecule in solution based on smoothed dissipative particle dynamics (SDPD) [Español and Revenga, Phys. Rev. E 67, 026705 (2003)]. This method is a thermodynamically consistent version of smoothed particle hydrodynamics able to discretize the Navier-Stokes equations and, at the same time, to incorporate thermal fluctuations according to the fluctuation-dissipation theorem. Within the framework of the method developed for mesoscopic multiphase flows by Hu and Adams [J. Comput. Phys. 213, 844 (2006)], we introduce additional finitely extendable nonlinear elastic interactions between particles that represent the beads of a polymer chain. In order to assess the accuracy of the technique, we analyze the static and dynamic conformational properties of the modeled polymer molecule in solution. Extensive tests of the method for the two-dimensional (2D) case are performed, showing good agreement with the analytical theory. Finally, the effect of confinement on the conformational properties of the polymer molecule is investigated by considering a 2D microchannel with gap H varying between 1 and 10 microm , of the same order as the polymer gyration radius. Several SDPD simulations are performed for different chain lengths corresponding to N=20-100 beads, giving a universal behavior of the gyration radius R_{G} and polymer stretch X as functions of the channel gap when normalized properly.

Genes reveal traces of common recent demographic history for most of the Uralic-speaking populations.

BACKGROUND: The genetic origins of Uralic speakers from across a vast territory in the temperate zone of North Eurasia have remained elusive. Previous studies have shown contrasting proportions of Eastern and Western Eurasian ancestry in their mitochondrial and Y chromosomal gene pools. While the maternal lineages reflect by and large the geographic background of a given Uralic-speaking population, the frequency of Y chromosomes of Eastern Eurasian origin is distinctively high among European Uralic speakers. The autosomal variation of Uralic speakers, however, has not yet been studied comprehensively. RESULTS: Here, we present a genome-wide analysis of 15 Uralic-speaking populations which cover all main groups of the linguistic family. We show that contemporary Uralic speakers are genetically very similar to their local geographical neighbours. However, when studying relationships among geographically distant populations, we find that most of the Uralic speakers and some of their neighbours share a genetic component of possibly Siberian origin. Additionally, we show that most Uralic speakers share significantly more genomic segments identity-by-descent with each other than with geographically equidistant speakers of other languages. We find that correlated genome-wide genetic and lexical distances among Uralic speakers suggest co-dispersion of genes and languages. Yet, we do not find long-range genetic ties between Estonians and Hungarians with their linguistic sisters that would distinguish them from their non-Uralic-speaking neighbours. CONCLUSIONS: We show that most Uralic speakers share a distinct ancestry component of likely Siberian origin, which suggests that the spread of Uralic languages involved at least some demic component.

Coverage-dependent kinetics and thermodynamics of carbon monoxide adsorption on a ternary copper catalyst derived from static adsorption microcalorimetry.

A reliable method for adsorption systems in equilibrium is established to derive coverage-dependent kinetics and thermodynamics from the volumetric data obtained during the static microcalorimetric measurement of heats of adsorption. The Wigner-Polanyi equation is applied to analyze the pressure change as a function of time during stepwise dosing of the adsorptive until thermodynamic adsorption-desorption equilibrium is established. For carbon monoxide adsorption on a hydrogen-reduced Cu/ZnO/Al2O3 catalyst, the adsorption rate constant (ka) is found to be in the range from 10(-6) to 10(-4) Pa(-1) s(-1), and the desorption rate constant (kd) from 10(-4) to 10(-2) s(-1), both increasing with fractional coverage theta. The kinetically derived equilibrium constant Ktheta is in good agreement with Ktheta obtained from the adsorption isotherm. RT ln(Kp0) and the differential heat of adsorption (qdiff) were found to decrease in parallel, reflecting a normal Temkin-type heterogeneity.

Determination of macroscopic transport coefficients of a dissipative particle dynamics solvent.

We present an approach to determine macroscopic transport coefficients of a dissipative particle dynamics (DPD) solvent. Shear viscosity, isothermal speed of sound, and bulk viscosity result from DPD-model input parameters and can be determined only a posteriori. For this reason approximate predictions of these quantities are desirable in order to set appropriate DPD input parameters. For the purpose of deriving an improved approximate prediction we analyze the autocorrelation of shear and longitudinal modes in Fourier space of a DPD solvent for Kolmogorov flow. We propose a fitting function with nonexponential properties which gives a good approximation to these autocorrelation functions. Given this fitting function we improve significantly the capability of a priori determination of macroscopic solvent transport coefficients in comparison to previously used exponential fitting functions.