Pair Distance Research Articles

Цифровая обработка фотометрических данных дистанционного зондирования полей озимой ржи

Abstract. The paper considers the possibility of using neural network structures of an artificial intelligence system for processing photometric data of remote sensing of winter rye crops grown in the conditions of the Leningrad Region on the field of the educational and experimental garden of Saint Petersburg State Agrarian University in 2014–2015. In the process of cultivating plants, various types of treatments were applied: the application of mineral fertilizers, microelements and a microbial biological product. To process the photometric data, the Rosenblatt perceptron was used, which analyzes the similarities and differences in the photometric NDVI profiles of winter rye crops obtained from different variants of the experiment. According to the numerical indicators of vegetation indices, it was possible to construct phase portraits of the trajectory of their movement on the coordinate plane of the field. Further cluster analysis of the data obtained, converted into a square matrix of paired Euclidean distances, made it possible to identify on the dendrogram a grouping of variants in which the connecting components were the use of a microbiological inoculant. When using a biological product, there is a more complete development of plants in crops and their evenness in the field improves. The minimum coefficient of variation was observed for the variant without the use of a biological product, but with the joint use of a complex of all mineral fertilizers (50 phosphorite flour + 50 KCl + 50 ammonium nitrate) and microelements at a dose of 250 kg/ha. Based on the results of the analysis, it can be concluded that the images of the trajectories of the points of the NDVI profiles provide qualitative information reflecting the dynamics of the ontogeny phases of winter rye plants. Based on the nature of the selected sections of these trajectories, it is possible to create a digital map of the experimental field, with the help of which to conduct a protocol for remote diagnostics of the state of crop productivity and make a forecast of their yield during harvesting.

Unveiling intricate transformation pathways of emerging contaminants during wastewater treatment processes through simplified network analysis

As the key stage for purifying wastewater, elimination of emerging contaminants (ECs) is found to be fairly low in wastewater treatment plants (WWTPs). However, less knowledge is obtained regarding the transformation pathways between various chemical structures of ECs under different treatment processes. This study unveiled the transformation pathways of ECs with different structures in 15 WWTPs distributed across China by simplified network analysis (SNA) we proposed. After treatment, the molecular weight of the whole component of wastewater decreased and the hydrophilicity increased. There are significant differences in the structure of eliminated, consistent and formed pollutants. Amino acids, peptides, and analogues (AAPAs) were detected most frequently and most removable. Benzenoids were refractory. Triazoles were often produced. The high-frequency reactions in different WWTPs were similar, (de)methylation and dehydration occurred most frequently. Different biological treatment processes performed similarly, while some advanced treatment processes differed, such as a significant increase of -13.976 (2HO reaction) paired mass distances (PMDs) in the chlorine alone process. Further, the common structural transformation was uncovered. 4 anti-hypertensive drugs, including irbesartan, valsartan, olmesartan, and losartan, were identified, along with 22 transformation products (TPs) of them. OH2 and H2O PMDs occurred most frequently and in 80.81 % of the parent-transformation product pairs, the intensity of the product was higher than parent in effluents, whose risk should be considered in future assessment activity. Together our results provide a macrography perspective on the transformation processes of ECs in WWTPs. In the future, selectively adopting wastewater treatment technology according to structures is conductive for eliminating recalcitrant ECs in WWTPs.

Weighted exchange distance of basis pairs

Two pairs of disjoint bases P1=(R1,B1) and P2=(R2,B2) of a matroid M are called equivalent if P1 can be transformed into P2 by a series of symmetric exchanges. In 1980, White conjectured that such a sequence always exists whenever R1∪B1=R2∪B2. A strengthening of the conjecture was proposed by Hamidoune, stating that the minimum length of an exchange is at most the rank of the matroid.We propose a weighted variant of Hamidoune’s conjecture, where the weight of an exchange depends on the weights of the exchanged elements. We prove the conjecture for several matroid classes: strongly base orderable matroids, split matroids, graphic matroids of wheels, and spikes.

Efficient similar waveform search using short binary codes obtained through a deep hashing technique

Summary A similar waveform search plays a crucial role in seismology for detecting seismic events, such as small earthquakes and low-frequency events. However, the high computational costs associated with waveform cross-correlation calculations represent bottlenecks during the analysis of long, continuous records obtained from numerous stations. In this study, we developed a deep-learning network to obtain 64-bit hash codes containing information on seismic waveforms. Using this network, we performed a similar waveform search for ∼35 million moving windows developed for the 30 min waveforms recorded continuously at 10 MHz sampling rates using 16 acoustic emission transducers during a laboratory hydraulic fracturing experiment. The sampling points of each channel corresponded to those of the 5.8-year records obtained from typical seismic observations at 100 Hz sampling rates. Of the 35 million windows, we searched for windows with small average Hamming distances among the hash codes of 16 channel waveforms against template hash codes of 6057 events that were catalogued using conventional autoprocessing techniques. The calculation of average Hamming distances is 1430–1530 times faster than that of the corresponding network correlation. This hashing-based template matching enabled the detection of 23,462 additional events. We also demonstrated the feasibility of the hashing-based autocorrelation analysis, where similar event pairs were extracted without templates, by calculating the average Hamming distances for all possible pairs of the ∼35 million windows. This calculation required only 15.5 h under 120 thread parallelisation. This deep hashing approach significantly reduced the required memory compared with locality-sensitive hashing approaches based on random permutations, enabling similar waveform searching on a large-scale dataset.

How close are the classical two-body potentials to abinitio calculations? Insights from linear machine learning based force matching.

In this work, we propose a linear machine learning force matching approach that can directly extract pair atomic interactions from abinitio calculations in amorphous structures. The local feature representation is specifically chosen to make the linear weights a force field as a force/potential function of the atom pair distance. Consequently, this set of functions is the closest representation of the abinitio forces, given the two-body approximation and finite scanning in the configurational space. We validate this approach in amorphous silica. Potentials in the new force field (consisting of tabulated Si-Si, Si-O, and O-O potentials) are significantly different than existing potentials that are commonly used for silica, even though all of them produce the tetrahedral network structure and roughly similar glass properties. This suggests that the commonly used classical force fields do not offer fundamentally accurate representations of the atomic interaction in silica. The new force field furthermore produces a lower glass transition temperature (Tg ∼ 1800K) and a positive liquid thermal expansion coefficient, suggesting the extraordinarily high Tg and negative liquid thermal expansion of simulated silica could be artifacts of previously developed classical potentials. Overall, the proposed approach provides a fundamental yet intuitive way to evaluate two-body potentials against abinitio calculations, thereby offering an efficient way to guide the development of classical force fields.

Cerrado bat community assembly is determined by both present‐day and historical factors

AbstractAimTo investigate the influence of ecological factors, geologic and climatic history on current diversity patterns of bat communities. We predicted that (i) our three different biodiversity dimensions (species richness, functional and phylogenetic diversity) will have a positive relationship with habitat heterogeneity; (ii) variation in phylogenetic diversity will be positively influenced by elevation; (iii) biodiversity dimensions will be influenced by climatic stability, with less diversity in regions with higher climatic instability.LocationNeotropical Savannah (Cerrado).MethodsWe calculated nine metrics: species richness, functional diversity, phylogenetic diversity, mean paired functional distance (MFD) and phylogenetic distances (MPD), richness‐corrected functional diversity (SES‐FD), richness‐corrected phylogenetic diversity (SES‐PD) and richness‐corrected mean functional and phylogenetic distances (SES.MFD and SES.MPD) using distribution records for 111 bat species. Habitat heterogeneity, climatic variables, elevation, floristic and climatic stability were used as independent variables. We used hierarchical Bayesian models to spatialise biodiversity dimensions based on the best predictors.ResultsCerrado habitat heterogeneity is important for phylogenetic diversity and mean functional and paired phylogenetic distances. Precipitation, temperature, elevation, habitat heterogeneity, and climatic stability were the most important predictors of Cerrado bat biodiversity. Species richness is inversely related to climatic instability, which is the best predictor of this metric. There is a decline in species richness in regions where the floristic composition has been more altered during the last 30,000 years, mainly in southern Cerrado.Main ConclusionsPresent‐day and historical factors simultaneously explain the biodiversity dimensions of bat communities in the Cerrado. Habitat heterogeneity is a major driver of phylogenetic diversity of Cerrado bats, and species of closely related lineages share habitats with homogeneous vegetation. Cerrado climatic changes and geologic history influenced the observed diversity metrics (PD and FD) and the ones corrected for species richness (SES‐PD and SES‐FD) in opposite ways. Species richness corrected metrics (SES‐PD and SES‐FD) indicate that species filtered by adaptive traits mainly occupied regions of climatic instability.

Analysis of maternal genetic structure of mitochondrial DNA control region from Tai-Kadai-speaking Buyei population in southwestern China

BackgroundEven though the Buyei are a recognised ethnic group in southwestern China, there hasn’t been much work done on forensic population genetics, notably using mitochondrial DNA. The sequences and haplogroups of mitochondrial DNA control regions of the Buyei peoples were studied to provide support for the establishment of a reference database for forensic DNA analysis in East Asia.Methods and resultsThe mitochondrial DNA control region sequences of 200 Buyei individuals in Guizhou were investigated. The haplotype frequencies and haplogroup distribution of the Buyei nationality in Guizhou were calculated. At the same time, the paired Fst values of the study population and other populations around the world were computed, to explore their genetic polymorphism and population relationship. A total of 179 haplotypes were detected in the Buyei population, with frequencies of 0.005–0.015. All haplotypes were assigned to 89 different haplogroups. The haplotype diversity and random matching probability were 0.999283 and 0.0063, respectively. The paired Fst genetic distances and correlation p-values among the 54 populations revealed that the Guizhou Buyei was most closely related to the Henan Han and the Guizhou Miao, and closer to the Hazara population in Pakistan and the Chiang Mai population.ConclusionsThe study of mitochondrial DNA based on the maternal genetic structure of the Buyei nationality in Guizhou will benefit the establishment of an East Asian forensic DNA reference database and provide a reference for anthropological research in the future.

Geometry-based cross-linking algorithm for modeling resorcinol resins through united-atom molecular dynamics simulations

The addition-condensation polymerization (ACP) of resorcinol with formaldehyde and the electrochemical polymerization (ECP) of resorcinol were desirable to improve the performances of resins. To achieve computational design, a new geometry-based cross-linking modeling algorithm for three-dimensional (3D) cross-linked network structures of resorcinol resins was developed for molecular dynamics (MD) simulations using a united-atom model. The ACP and ECP of resorcinol were successfully modeled using one algorithm by changing the parameters of the reaction rate constants of methylene, ether, and biphenyl bond formations. Furthermore, reaction judgment was performed under a reaction probability function comprising the Gaussian functions based on the interatomic distance of the reaction candidate atom pairs and interior angles regarding the spatial arrangement of two resorcinol rings. This geometry-based cross-linking algorithm successfully generated strainless 3D cross-linked network structures of the ACP and ECP resorcinol resins without the formation of highly bent unstable structures, such as U-shaped biphenyls. The MD simulation results indicated that the cross-linking of the ACP resin comprising methylene linkages proceeded with a network structure formation mechanism similar to that of phenolic resins, where the cross-linked network structure was determined at the gel point and the reactions after the gel point were to fix and freeze the network structure. For the ECP resins comprising ether and biphenyl linkages, the molar ratio of ether to biphenyl bonds affected the elastic property of the resins, and the incorporation of rigid biphenyl structures into ether-linkage networks increased the elastic modulus. Moreover, an increase in rigidity was observed as a decrease in the Poisson's ratio.

Prediction of Inter-residue Multiple Distances and Exploration of Protein Multiple Conformations by Deep Learning.

AlphaFold2 has achieved a major breakthrough in end-to-end prediction for static protein structures. However, protein conformational change is considered to be a key factor in protein biological function. Inter-residue multiple distances prediction is of great significance for research on protein multiple conformations exploration. In this study, we proposed an inter-residue multiple distances prediction method, DeepMDisPre, based on an improved network which integrates triangle update, axial attention and ResNet to predict multiple distances of residue pairs. We built a dataset which contains proteins with a single structure and proteins with multiple conformations to train the network. We tested DeepMDisPre on 114 proteins with multiple conformations. The results show that the inter-residue distance distribution predicted by DeepMDisPre tends to have multiple peaks for flexible residue pairs than for rigid residue pairs. On two cases of proteins with multiple conformations, we modeled the multiple conformations relatively accurately by using the predicted inter-residue multiple distances. In addition, we also tested the performance of DeepMDisPre on 279 proteins with a single structure. Experimental results demonstrate that the average contact accuracy of DeepMDisPre is higher than that of the comparative method. In terms of static protein modeling, the average TM-score of the 3D models built by DeepMDisPre is also improved compared with the comparative method. The executable program is freely available at https://github.com/iobio-zjut/DeepMDisPre.

Optimization of forensic identification through 3-dimensional imaging analysis of labial tooth surface using open-source software.

The objective of this study was to determine the minimum number of teeth in the anterior dental arch that would yield accurate results for individual identification in forensic contexts. The study involved the analysis of 28 sets of 3-dimensional (3D) point cloud data, focused on the labial surface of the anterior teeth. These datasets were superimposed within each group in both genuine and imposter pairs. Group A incorporated data from the right to the left central incisor, group B from the right to the left lateral incisor, and group C from the right to the left canine. A comprehensive analysis was conducted, including the evaluation of root mean square error (RMSE) values and the distances resulting from the superimposition of dental arch segments. All analyses were conducted using CloudCompare version 2.12.4 (Telecom ParisTech and R&D, Kyiv, Ukraine). The distances between genuine pairs in groups A, B, and C displayed an average range of 0.153 to 0.184 mm. In contrast, distances for imposter pairs ranged from 0.338 to 0.522 mm. RMSE values for genuine pairs showed an average range of 0.166 to 0.177, whereas those for imposter pairs ranged from 0.424 to 0.638. A statistically significant difference was observed between the distances of genuine and imposter pairs (P<0.05). The exceptional performance observed for the labial surfaces of anterior teeth underscores their potential as a dependable criterion for accurate 3D dental identification. This was achieved by assessing a minimum of 4 teeth.

Deciphering Microbe-Mediated Dissolved Organic Matter Reactome in Wastewater Treatment Plants Using Directed Paired Mass Distance.

Understanding the reaction mechanism of dissolved organic matter (DOM) during wastewater biotreatment is crucial for optimal DOM control. Here, we develop a directed paired mass distance (dPMD) method that constructs a molecular network displaying the reaction pathways of DOM. It couples direction inference and PMD analysis to extract the substrate-product relationships and delta masses of potentially paired reactants directly from sequential mass spectrometry data without formula assignment. Using this method, we analyze the influent and effluent samples from the bioprocesses of 12 wastewater treatment plants (WWTPs) and build a dPMD network to characterize the core reactome of DOM. The network shows that the first step of the transformation triggers reaction cascades that diversify the DOM, but the highly overlapped subsequent reaction pathways result in similar effluent DOM compositions across WWTPs despite varied influents. Mass changes exhibit consistent gain/loss preferences (e.g., +3.995 and -16.031) but different occurrences across WWTPs. Combined with genome-centric metatranscriptomics, we reveal the associations among dPMDs, enzymes, and microbes. Most enzymes are involved in oxygenation, (de)hydrogenation, demethylation, and hydration-related reactions but with different target substrates and expressed by various taxa, as exemplified by Proteobacteria, Actinobacteria, and Nitrospirae. Therefore, a functionally diverse community is pivotal for advanced DOM degradation.

Development and optimization of a novel response‐amplified friction damper with different friction pairs

AbstractIn order to improve the efficiency of friction dampers, a shear‐type response‐amplified friction damper (RAFD) was proposed, which utilized a lever mechanism to amplify the shear displacement and increase the sliding distance of friction pairs. Cyclic loading tests were conducted on 12 RAFD specimens to evaluate the effects of machining processes, friction materials, loading protocols, and bolt pretension on the mechanical performance of the specimens. The results showed that the RAFD specimens with NAO and brass friction pads exhibited plump hysteresis loops, and the bearing capacity, effective stiffness, energy dissipation, and equivalent viscous damping ratio all met the stability requirements of FEMA 356 for the friction damper. Reducing the clearance between pins and holes and strengthening the hole edges shortened the plateau near zero resistances of the hysteresis loops by 75%–90%. Furthermore, combined with rotational analysis of the lever, a design methodology for the RAFD specimen was developed. Based on the response amplification factor R, key mechanical indices such as bearing capacity and equivalent friction coefficient were derived, and a theoretical hysteresis model for the RAFD was constructed, which matched well with experimental results.

Interpretable Machine Learning and Reactomics Assisted Isotopically Labeled FT-ICR-MS for Exploring the Reactivity and Transformation of Natural Organic Matter during Ultraviolet Photolysis.

Isotopically labeled FT-ICR-MS combined with multiple post-analyses, including interpretable machine learning (IML) and a paired mass distance (PMD) network, was employed to unravel the reactivity and transformation of natural organic matter (NOM) during ultraviolet (UV) irradiation. FT-ICR-MS analysis was used to assign formulas, which were classified on the basis of their molecular compositions and structural categories. Isotope (deuterium, D) labeling was utilized to unequivocally determine the photochemical products and examine the development of OD radical-mediated NOM transformation. With regard to the reactive molecular formulas, CHOS formulas exhibited the highest reactivity (86.5% of precursors disappeared) followed by CHON (53.4%) and CHO (24.6%) formulas. With regard to structural categories, the degree of reactivity decreased in the following order: tannins > condensed aromatics > lignin/CRAMs. The IML algorithm demonstrated that the crucial features governing the reactivity of formulas were the molecular weight, DBE-O, NOSC, and the presence of heteroatoms (i.e., N and S), suggesting that the large and unsaturated compounds containing S and N are more prone to photodegradation. The reactomics approach using the PMD network further indicated that 11 specific molecular formulas in the CHOS and CHO class served as hubs, implying a higher photoreactivity and participation in a range of transformations. The isotope labeling analyses also found that, among the reactions observed, hydroxylation (i.e., +OD) is dominant for lignin/CRAMs and condensed aromatics, and formulas containing ≤10 D atoms were developed. Overall, this study, by adopting rigorous and interpretable techniques, could provide in-depth insights into the molecular-level dynamics of NOM under UV irradiation.

The Effect of Nutrient Deprivation on Early Life Small Intestinal Mucosal Microbiome and Host Proteome

BackgroundNutrition plays a vital role in shaping the intestinal microbiome. However, many hospitalized children undergo periods of fasting during medical treatment. Changes to the small intestinal microbiota in early life in the setting of enteral deprivation have not been well described. ObjectiveThe aim of this study was to investigate the impact of enteral deprivation on the small intestinal mucosal microbiome and to identify factors that shape this interaction in infancy. MethodsIntestinal biopsies were collected from proximal (fed) and distal (unfed) small bowel at the time of ostomy closure in children with a small intestinal enterostomy. Mucosal and luminal microbiome comparisons were performed including β-diversity and differential abundance and correlations with clinical factors were analyzed. Host proteomics were compared between fed and unfed samples and correlated with microbiome parameters. Finally, microbial results were validated in another cohort of pediatric patients. ResultsSamples from 13 children (median age 84 d) were collected. Mucosal microbiome communities in the fed and unfed segments were strikingly similar [paired UniFrac distance (β-diversity)], whereas luminal effluent differed significantly from fed samples (PERMANOVA, P = 0.003). Multivariate analysis revealed patient as the strongest predictor of the UniFrac distance. Environmental variables did not influence the intrapatient microbial dissimilarity. Host proteomics were similar intrapatient (paired fed–unfed Euclidian distance) and showed a correlation with the UniFrac distance (Spearman rho = 0.71, P < 0.001). Specific proteins and functional clusters were significantly different between paired samples, including lipid metabolism and intracellular trafficking, whereas no difference was seen in innate immune proteins. The microbiome results were validated in a different cohort with similar characteristics. ConclusionWe found the host to be the most dominant factor in the structure of the early life small intestinal mucosal microbiome. Nutrient deprivation was associated with specific changes in the host proteome. Further research is needed to better understand this host–microbe–nutrition interaction.

Ab initio Modeling of Hydrogen Bonding of Remdesivir and Adenosine with Uridine.

Remdesivir (RDV) emerged as an effective drug against the SARS-CoV-2 virus pandemic. One of the crucial steps in the mechanism of action of RDV is its incorporation into the growing RNA strand. RDV, an adenosine analogue, forms Watson-Crick (WC) type hydrogen bonds with uridine in the complementary strand and the strength of this interaction will control efficacy of RDV. While there is a plethora of structural and energetic information available about WC H-bonds in natural base pairs, the interaction of RDV with uridine has not been studied yet at the atomic level. In this article, we aim to bridge this gap, to understand RDV and its hydrogen bonding interactions, by employing density functional theory (DFT) at the M06-2X/cc-pVDZ level. The interaction energy, QTAIM analysis, NBO and SAPT2 are performed for RDV, adenosine, and their complex with uridine to gain insights into the nature of hydrogen bonding. The computations show that RDV has similar geometry, energetic, molecular orbitals, and aromaticity as adenosine, suggesting that RDV is an effective adenosine analogue. The important geometrical parameters, such as bond distances and red-shift in the stretching vibrational modes of adenosine, RDV and uridine identify two WC-type H-bonds. The relative strength of these two H-bonds is computed using QTAIM parameters and the computed hydrogen bond energy. Finally, the SAPT2 study is performed at the minima and at non-equilibrium base pair distances to understand the dominant intermolecular physical force. This study, based on a thorough analysis of a variety of computations, suggests that both adenosine and RDV have similar structure, energetic, and hydrogen bonding behaviour.

Overcoming barriers to reef restoration: field‐based method for approximate genotyping of Acropora cervicornis

Reef restoration efforts aim to enhance resilience by safeguarding the genetic diversity of coral populations. This could be facilitated by genotyping methods that are relatively inexpensive, and field‐based. A potential method for assessing coral genotypic diversity arises from self‐recognition phenomena. Past studies have shown that contact between tissues from the same genet (isogeneic) will fuse whereas tissue from different genets (allogeneic) will result in rejection. However, the accuracy of this method has been questioned. Here, we revisit the grafting method as a tool to estimate genotypic diversity in a Caribbean coral restoration target, Acropora cervicornis. Ten ramets of unknown genetic relation were arranged in 82 grafting tests consisting of 5‐fragment bundles that replicated all possible combinations between ramets. After 10 weeks, we found that outcomes of acceptance and rejection were highly consistent (96.7% across all combinations and replicates). The proposed existence of 4 genets across the 10 ramets based on response outcomes was confirmed by two SNP‐based genotyping methods. Both genet pairing (isogeneic or allogeneic pairs) and genetic distance significantly affected the odds of acceptance or rejection responses. Moreover, a significant correlation was found between the degree of fusion between fragments and their genetic distance, supporting that the most related ramets are accepted more strongly compared to those that are more unrelated. This field‐based contact method can be a powerful tool to estimate genotypic diversity in coral nurseries, facilitating the management of genetic diversity within the nursery and genotype‐level tracking of key traits like disease and bleaching resistance.

Stability analysis of a streaky boundary layer generated by miniature vortex generators

Delaying laminar-turbulent transition is an attractive method to reduce friction drag on streamlined bodies. In the case of natural transition, in which turbulence is triggered by the growth of two-dimensional Tollmien–Schlichting (TS) instabilities, this growth of TS instabilities can be attenuated by introducing steady streamwise streaks into the boundary layer. These streamwise streaks are generated by streamwise vortices, which rearrange the flow via the lift-up mechanism. Such streamwise vortices can be induced by so-called miniature vortex generators (MVGs). Although recently considerable attention has been devoted to the investigation of MVGs, and multiple studies investigated MVGs with different parameters, the previously investigated MVG configurations are likely suboptimal. This study aims at (partially) filling this knowledge gap by complementing previous studies by conducting a parametric study of rectangular MVGs and assessing them with local linear stability analysis. Three parameters are varied simultaneously: the height, the spanwise distance of the MVG pairs, and the distance between MVGs in each pair. First, the modelling approach is presented, which consist of an efficient base flow computation, and BiGlobal stability analysis. The base flow calculation is validated by comparing our results with the experiments of Shattarzadeh and Fransson (2015). Then, the streak amplitude, the growth factors of the TS-waves and the secondary shear-layer instabilities are analysed in a parametric study. It is shown that with the variation of the spanwise distances, the maximum amplitude and the streamwise extent of the streaks in the boundary layer can be controlled, reminiscent of the behaviour of the optimal vortices. The findings and the test of the methodology provide valuable insight, which may be useful for the optimisation of MVGs.

Size-refocusing fitting of small-angle X-ray scattering from polydisperse nanoparticles for shape determination

Small-angle X-ray scattering (SAXS) which records reciprocal-space signals with characteristic Bessel-type oscillations is a powerful technique for studying nanoparticles. However, the size polydispersity (or size distribution) of nanoparticles in an ensemble sample smears the oscillational peaks and valleys in the SAXS profile, making it difficult to extract accurate real-space information (e.g. three-dimensional geometry) on the nanoparticles. In this work, a method capable of eliminating the size-distribution-induced smearing effect from SAXS profiles by taking the known size-distribution function into consideration has been developed. The method employs a penalized iterative regression to fit the pair distance distribution function (PDDF) derived from a SAXS profile, recovering the representative PDDF of the nanoparticles. The method has been evaluated with a series of nanoparticle systems of various shapes and size distributions, showing their PDDF profiles to have high fidelity to the reference ideal PDDF profiles. Inverse Fourier transformation of the recovered PDDF profiles gives SAXS profiles presenting the characteristic Bessel-type oscillations, enabling reconstruction of the representative three-dimensional geometry of the nanoparticles. This method will help in the use of SAXS to image synthesized colloidal nanoparticles where size polydispersity is inevitable.

Unidirectional gene pairs in archaea and bacteria require overlaps or very short intergenic distances for translational coupling via termination-reinitiation and often encode subunits of heteromeric complexes.

Genomes of bacteria and archaea contain a much larger fraction of unidirectional (serial) gene pairs than convergent or divergent gene pairs. Many of the unidirectional gene pairs have short overlaps of -4 nt and -1 nt. As shown previously, translation of the genes in overlapping unidirectional gene pairs is tightly coupled. Two alternative models for the fate of the post-termination ribosome predict either that overlaps or very short intergenic distances are essential for translational coupling or that the undissociated post-termination ribosome can scan through long intergenic regions, up to hundreds of nucleotides. We aimed to experimentally resolve the contradiction between the two models by analyzing three native gene pairs from the model archaeon Haloferax volcanii and three native pairs from Escherichia coli. A two reporter gene system was used to quantify the reinitiation frequency, and several stop codons in the upstream gene were introduced to increase the intergenic distances. For all six gene pairs from two species, an extremely strong dependence of the reinitiation efficiency on the intergenic distance was unequivocally demonstrated, such that even short intergenic distances of about 20 nt almost completely abolished translational coupling. Bioinformatic analysis of the intergenic distances in all unidirectional gene pairs in the genomes of H. volcanii and E. coli and in 1,695 prokaryotic species representative of 49 phyla showed that intergenic distances of -4 nt or -1 nt (= short gene overlaps of 4 nt or 1 nt) were by far most common in all these groups of archaea and bacteria. A small set of genes in E. coli, but not in H. volcanii, had intergenic distances of around +10 nt. Our experimental and bioinformatic analyses clearly show that translational coupling requires short gene overlaps, whereas scanning of intergenic regions by the post-termination ribosome occurs rarely, if at all. Short overlaps are enriched among genes that encode subunits of heteromeric complexes, and co-translational complex formation requiring precise subunit stoichiometry likely confers an evolutionary advantage that drove the formation and conservation of overlapping gene pairs during evolution.

150 Repeatability of Rangeland Behavioral and Social Traits Derived from Gps Collars

Abstract The ability of an individual to cope with stressors in their environment is going to be paramount in the face of climate change. Rangeland livestock experience harsh conditions including heat and/or cold stress, water and feed restrictions and risk of predation. In extensive management systems, the ability to capture the capacity to cope with stressors of an individual in its environment is encumbered by remote locations with difficult terrain and no access to power or the internet. GPS collars can provide insights into individual land-use behavior, e.g., their impact on the environment or ability to cope with stressors, and social interactions, e.g., mothering ability. GPS collars (n = 112) developed at the University of Idaho were deployed on 57 ewes and 55 lambs (45 ewe-lamb pairs) in an extensive rangeland environment at the Great Basin Research and Extension Center in Eureka, NV. The collars recorded location data every 10 minutes from July 27th to August 18, 2022. Coordinate fixes were successfully recorded 67.11 ± 27.12% of the time and resulted in a kept record occurring every 60 ± 202 minutes. Of the ewe-lamb pair devices, 43 pairs contributed 801 ± 703 paired records (i.e., records that occurred within 5 minutes of each other). GPS coordinate locations, and their respective capture times, allow for the analysis of distance traveled, water usage, dispersion, and ewe-lamb distance. Distance traveled was analyzed on a daily basis with a weighted median distance imputed for all travel times that lasted more than 900 seconds. Dispersion was defined as the distance of an individual from the centroid of the flock in meters, and was transformed to a Z-score based on the position of individuals with GPS coordinates captured within 10 minutes of the measurement of the individual. Ewe-lamb pair distances were cube root transformed. Twin status, dam line, age, and day were fitted as fixed classes to estimate the repeatability of records for mature ewes. Repeatability estimates of daily distance traveled, daily water usage, and daily dispersion were 0.22 ± 0.05, 0.30 ± 0.06 and 0.10 ± 0.03, respectively. Daily ewe-lamb distances had a repeatability estimate of 0.45 ± 0.08. Day of recording was significant for daily distance traveled (P-value = 2.72×10-4) and water usage (P-value = 1.06×10-3). No other effects were significant in any of the models. In conclusion, PLF tools are an enabling technology that allow for passive data capture in remote locations. Our findings suggest that GPS collars can elucidate a variety of land use and social behavior traits that could serve as meaningful criteria for selection in extensive livestock production settings. Selection on these indicators of resilience may increase livestock productivity and welfare by increasing heat stress tolerance via the analysis of novel behavioral traits seen on extensive rangelands.