Hierarchical Modular Structure of the Drosophila Connectome.

The structure of neural circuitry plays a crucial role in brain function. Previous studies of brain organization generally had to trade off between coarse descriptions at a large scale and fine descriptions on a small scale. Researchers have now reconstructed tens to hundreds of thousands of neurons at synaptic resolution, enabling investigations into the interplay between global, modular organization, and cell type-specific wiring. Analyzing data of this scale, however, presents unique challenges. To address this problem, we applied novel community detection methods to analyze the synapse-level reconstruction of an adult female Drosophila melanogaster brain containing >20,000 neurons and 10 million synapses. Using a machine-learning algorithm, we find the most densely connected communities of neurons by maximizing a generalized modularity density measure. We resolve the community structure at a range of scales, from large (on the order of thousands of neurons) to small (on the order of tens of neurons). We find that the network is organized hierarchically, and larger-scale communities are composed of smaller-scale structures. Our methods identify well-known features of the fly brain, including its sensory pathways. Moreover, focusing on specific brain regions, we are able to identify subnetworks with distinct connectivity types. For example, manual efforts have identified layered structures in the fan-shaped body. Our methods not only automatically recover this layered structure, but also resolve finer connectivity patterns to downstream and upstream areas. We also find a novel modular organization of the superior neuropil, with distinct clusters of upstream and downstream brain regions dividing the neuropil into several pathways. These methods show that the fine-scale, local network reconstruction made possible by modern experimental methods are sufficiently detailed to identify the organization of the brain across scales, and enable novel predictions about the structure and function of its parts.Significance Statement The Hemibrain is a partial connectome of an adult female Drosophila melanogaster brain containing >20,000 neurons and 10 million synapses. Analyzing the structure of a network of this size requires novel and efficient computational tools. We applied a new community detection method to automatically uncover the modular structure in the Hemibrain dataset by maximizing a generalized modularity measure. This allowed us to resolve the community structure of the fly hemibrain at a range of spatial scales revealing a hierarchical organization of the network, where larger-scale modules are composed of smaller-scale structures. The method also allowed us to identify subnetworks with distinct cell and connectivity structures, such as the layered structures in the fan-shaped body, and the modular organization of the superior neuropil. Thus, network analysis methods can be adopted to the connectomes being reconstructed using modern experimental methods to reveal the organization of the brain across scales. This supports the view that such connectomes will allow us to uncover the organizational structure of the brain, which can ultimately lead to a better understanding of its function.

Perspectives on pulsed field ablation: how to judge endpoints.

PURPOSE OF REVIEW: This review highlights pulse field ablation's (PFA) significance in treating atrial fibrillation. PFA uses short-pulsed electrical fields, offering safety advantages over thermal methods. Multicenter studies' findings on PFA's safety, efficiency, and efficacy, compared with thermal techniques, are discussed. RECENT FINDINGS: The review encompasses major PFA systems utilized in multicenter studies: penta-spline, circular, and lattice catheters. These studies affirm PFA's safety, with minimal complications like esophageal injury, phrenic nerve complications, and pulmonary vein stenosis. PFA also demonstrates procedural efficiency benefits because of rapid pulse delivery. However, PFA's efficacy appears on par with thermal ablation, showing similar rates of atrial arrhythmia recurrence during follow-up periods. The studies explore diverse postablation monitoring strategies, underscoring the necessity for standardized monitoring or consistent transformation of arrhythmia data. SUMMARY: In conclusion, PFA marks a promising era for atrial fibrillation treatment with improved safety and efficiency. Efficacy is comparable to thermal methods, though technology advancements could alter this. PFA's potential as a safer and faster alternative positions it as a dominant atrial fibrillation ablation technology. Careful analysis and standardized monitoring are vital to assess PFA's potential and clinical implications.

Contrast response function estimation with nonparametric Bayesian active learning.

Multidimensional psychometric functions can typically be estimated nonparametrically for greater accuracy or parametrically for greater efficiency. By recasting the estimation problem from regression to classification, however, powerful machine learning tools can be leveraged to provide an adjustable balance between accuracy and efficiency. Contrast sensitivity functions (CSFs) are behaviorally estimated curves that provide insight into both peripheral and central visual function. Because estimation can be impractically long, current clinical workflows must make compromises such as limited sampling across spatial frequency or strong assumptions on CSF shape. This article describes the development of the machine learning contrast response function (MLCRF) estimator, which quantifies the expected probability of success in performing a contrast detection or discrimination task. A machine learning CSF can then be derived from the MLCRF. Using simulated eyes created from canonical CSF curves and actual human contrast response data, the accuracy and efficiency of the machine learning contrast sensitivity function (MLCSF) was evaluated to determine its potential utility for research and clinical applications. With stimuli selected randomly, the MLCSF estimator converged slowly toward ground truth. With optimal stimulus selection via Bayesian active learning, convergence was nearly an order of magnitude faster, requiring only tens of stimuli to achieve reasonable estimates. Inclusion of an informative prior provided no consistent advantage to the estimator as configured. MLCSF achieved efficiencies on par with quickCSF, a conventional parametric estimator, but with systematically higher accuracy. Because MLCSF design allows accuracy to be traded off against efficiency, it should be explored further to uncover its full potential.

XB2Bi2 (X = Si, Ge, Sn, Pb): Penta-Atomic Planar Tetracoordinate Si/Ge/Sn/Pb Clusters with 20 Valence Electrons.

Planar tetracoordinate silicon, germanium, tin, and lead (ptSi/Ge/Sn/Pb) species are scarce and exotic. Here, we report a series of penta-atomic ptSi/Ge/Sn/Pb XB2Bi2 (X = Si, Ge, Sn, Pb) clusters with 20 valence electrons (VEs). Ternary XB2Bi2 (X = Si, Ge, Sn, Pb) clusters possess beautiful fan-shaped structures, with a Bi-B-B-Bi chain surrounding the central X core. The unbiased density functional theory (DFT) searches and high-level CCSD(T) calculations reveal that these ptSi/Ge/Sn/Pb species are the global minima on their potential energy surfaces. Born-Oppenheimer molecular dynamics (BOMD) simulations indicate that XB2Bi2 (X = Si, Ge, Sn, Pb) clusters are robust. Bonding analyses indicate that 20 VEs are perfect for the ptX XB2Bi2 (X = Si, Ge, Sn, Pb): two lone pairs of Bi atoms; one 5c-2e π, and three σ bonds (two Bi-X 2c-2e and one B-X-B 3c-2e bonds) between the ligands and X atom; three 2c-2e σ bonds and one delocalized 4c-2e π bond between the ligands. The ptSi/Ge/Sn/Pb XB2Bi2 (X = Si, Ge, Sn, Pb) clusters possess 2π/2σ double aromaticity, according to the (4n + 2) Hückel rule.

Apparatus for Automated Continuous Hydrogen Deuterium Exchange Mass Spectrometry Measurements from Milliseconds to Hours.

Hydrogen deuterium exchange mass spectrometry (HDX-MS) is a rapidly growing technique for protein characterization in industry and academia, complementing the "static" picture provided by classical structural biology with information about the dynamic structural changes that accompany biological function. Conventional hydrogen deuterium exchange experiments, carried out on commercially available systems, typically collect 4-5 exchange timepoints on a timescale ranging from tens of seconds to hours using a workflow that can require 24 h or more of continuous data collection for triplicate measurements. A small number of groups have developed setups for millisecond timescale HDX, allowing for the characterization of dynamic shifts in weakly structured or disordered regions of proteins. This capability is particularly important given the central role that weakly ordered protein regions often play in protein function and pathogenesis. In this work, we introduce a new continuous flow injection setup for time-resolved HDX-MS (CFI-TRESI-HDX) that allows automated, continuous or discrete labeling time measurements from milliseconds to hours. The device is composed almost entirely of "off-the-shelf" LC components and can acquire an essentially unlimited number of timepoints with substantially reduced runtimes compared to conventional systems.

Amplification-Free Ratiometric Electrochemical Aptasensor for Point-of-Care Detection of Therapeutic Monoclonal Antibodies.

The rapid quantification of therapeutic monoclonal antibodies (mAbs) is of great significance to their pharmacokinetics/pharmacodynamics (PK/PD) research and the personalized medication for disease treatment. Taking advantage of the direct decoration of tens of redox tags to the target of interest, we illustrate herein an amplification-free ratiometric electrochemical aptasensor for the point-of-care (POC) detection of trace amounts of therapeutic mAbs. The POC detection of therapeutic mAbs involved the use of the methylene blue (MB)-conjugated aptamer as the affinity element and the decoration of therapeutic mAbs with ferrocene (Fc) tags via the boronate crosslinking, in which the MB-derived peak current was used as the reference signal, and the peak current of the Fc tag was used as the output signal. As each therapeutic mAb carries tens of diol sites for the site-specific decoration of the Fc output tags, the boronate crosslinking enabled the amplification-free detection, which is cost-effective and quite simple in operation. In the presence of bevacizumab (BevMab) as the target, the resulting ratiometric signal (i.e., the IFc/IMB value) exhibited a good linear response over the range of 0.025-2.5 µg/mL, and the limit of detection (LOD) of the electrochemical aptasensor was 6.5 ng/mL. Results indicated that the aptamer-based affinity recognition endowed the detection of therapeutic mAbs with high selectivity, while the ratiometric readout exhibited satisfactory reproducibility and robustness. Moreover, the ratiometric electrochemical aptasensor is applicable to the detection of therapeutic mAbs in serum samples. Taking together, the amplification-free ratiometric electrochemical aptasensor holds great promise in the POC detection of therapeutic mAbs.

First Constraints on Heavy QCD Axions with a Liquid Argon Time Projection Chamber Using the ArgoNeuT Experiment.

We present the results of a search for heavy QCD axions performed by the ArgoNeuT experiment at Fermilab. We search for heavy axions produced in the NuMI neutrino beam target and absorber decaying into dimuon pairs, which can be identified using the unique capabilities of ArgoNeuT and the MINOS near detector. This decay channel is motivated by a broad class of heavy QCD axion models that address the strong CP and axion quality problems with axion masses above the dimuon threshold. We obtain new constraints at a 95% confidence level for heavy axions in the previously unexplored mass range of 0.2-0.9 GeV, for axion decay constants around tens of TeV.

Effect of pentaerythritol tetranitrate (PETN) on the development of fetal growth restriction in pregnancies with impaired uteroplacental perfusion at midgestation-a randomized trial.

BACKGROUND: Fetal growth restriction is strongly associated with impaired placentation and abnormal uteroplacental blood flow. Nitric oxide donors such as pentaerythritol tetranitrate are strong vasodilators and protect the endothelium. Recently, we demonstrated in a randomized controlled pilot study a 38% relative risk reduction for the development of fetal growth restriction or perinatal death following administration of pentaerythritol tetranitrate to pregnant women at risk, identified by impaired uterine perfusion at midgestation. Results of this monocenter study prompted the hypothesis that pentaerythritol tetranitrate might have an effect in pregnancies with compromised placental function as a secondary prophylaxis. OBJECTIVE: This study aimed to test the hypothesis that the nitric oxide donor pentaerythritol tetranitrate reduces fetal growth restriction and perinatal death in pregnant women with impaired placental perfusion at midgestation in a multicenter trial. STUDY DESIGN: In this multicenter, randomized, double-blind, placebo-controlled trial, 2 parallel groups of pregnant women presenting with a mean uterine artery pulsatility index >95th percentile at 19+0 to 22+6 weeks of gestation were randomized to 50-mg Pentalong or placebo twice daily. Participants were assigned to high- or low-risk groups according to their medical history before randomization was performed block-wise with a fixed block length stratified by center and risk group. The primary efficacy endpoint was the composite outcome of perinatal death or development of fetal growth restriction. Secondary endpoints were neonatal and maternal outcome parameters. RESULTS: Between August 2017 and March 2020, 317 participants were included in the study and 307 were analyzed. The cumulative incidence of the primary outcome was 41.1% in the pentaerythritol tetranitrate group and 45.5% in the placebo group (unadjusted relative risk, 0.90; 95% confidence interval, 0.69-1.17; adjusted relative risk, 0.90; 95% confidence interval, 0.69-1.17; P=.43). Secondary outcomes such as preterm birth (unadjusted relative risk, 0.73; 95% confidence interval, 0.56-0.94; adjusted relative risk, 0.73; 95% confidence interval, 0.56-0.94; P=.01) and pregnancy-induced hypertension (unadjusted relative risk, 0.65; 95% confidence interval, 0.46-0.93; adjusted relative risk, 0.65; 95% confidence interval, 0.46-0.92; P=0.01) were reduced. CONCLUSION: Our study failed to show an impact of pentaerythritol tetranitrate on the development of fetal growth restriction and perinatal death in pregnant women with impaired uterine perfusion at midgestation. Pentaerythritol tetranitrate significantly reduced secondary outcome parameters such as the incidence of preterm birth and pregnancy-induced hypertension in these pregnancies.

Sparse spike trains and the limitation of rate codes underlying rapid behaviours.

Animals live in dynamic worlds where they use sensorimotor circuits to rapidly process information and drive behaviours. For example, dragonflies are aerial predators that react to movements of prey within tens of milliseconds. These pursuits are likely controlled by identified neurons in the dragonfly, which have well-characterized physiological responses to moving targets. Predominantly, neural activity in these circuits is interpreted in context of a rate code, where information is conveyed by changes in the number of spikes over a time period. However, such a description of neuronal activity is difficult to achieve in real-world, real-time scenarios. Here, we contrast a neuroscientists' post-hoc view of spiking activity with the information available to the animal in real-time. We describe how performance of a rate code is readily overestimated and outline a rate code's significant limitations in driving rapid behaviours.

The impact of maternal morbidity on cesarean section rates: exploring a Latin American network of sentinel facilities using the Robson's Ten Group Classification System.

BACKGROUND: Latin America has the highest Cesarean Section Rates (CSR) in the world. Robson's Ten Group Classification System (RTGCS) was developed to enable understanding the CSR in different groups of women, classified according to obstetric characteristics into one of ten groups. The size of each CS group may provide helpful data on quality of care in a determined region or setting. Data can potentially be used to compare the impact of conditions such as maternal morbidity on CSR. The objective of this study is to understand the impact of Severe Maternal Morbidity (SMM) on CSR in ten different groups of RTGCS. METHODS: Secondary analysis of childbirth information from 2018 to 2021, including 8 health facilities from 5 Latin American and Caribbean countries (Bolivia, Guatemala, Honduras, Nicaragua, and the Dominican Republic), using a surveillance database (SIP-Perinatal Information System, in Spanish) implemented in different settings across Latin America. Women were classified into one of RTGCS. The frequency of each group and its respective CSR were described. Furthermore, the sample was divided into two groups, according to maternal outcomes: women without SMM and those who experienced SMM, considering Potentially Life-threatening Conditions, Maternal Near Miss and Maternal Death as the continuum of morbidity. RESULTS: Available data were obtained from 92,688 deliveries using the Robson Classification. Overall CSR was around 38%. Group 5 was responsible for almost one-third of cesarean sections. SMM occurred in 6.7% of cases. Among these cases, the overall CSR was almost 70% in this group. Group 10 had a major role (preterm deliveries). Group 5 (previous Cesarean section) had a very high CSR within the group, regardless of the occurrence of maternal morbidity (over 80%). CONCLUSION: Cesarean section rate was higher in women experiencing SMM than in those without SMM in Latin America. SMM was associated with higher Cesarean section rates, especially in groups 1 and 3. Nevertheless, group 5 was the major contributor to the overall CSR.

Bacteria isolated from explosive contaminated environments transform pentaerythritol tetranitrate (PETN) under aerobic and anaerobic conditions.

Pentaerythritol tetranitrate (PETN) is a nitrate ester explosive that may be persistent with scarce reports on its environmental fate and impacts. Our main objective was to isolate and characterize bacteria that transform PETN under aerobic and anaerobic conditions. Biotransformation of PETN (100 mg L-1) was evaluated using mineral medium with (M + C) and without (M - C) additional carbon sources under aerobic conditions and with additional carbon sources under anaerobic conditions. Here, we report on the isolation of 12 PETN-transforming cultures (4 pure and 8 co-cultures) from environmental samples collected at an explosive manufacturing plant. The highest transformation of PETN was observed for cultures in M + C under aerobic conditions, reaching up to 91% ± 2% in 2 d. Under this condition, PETN biotransformation was observed in conjunction with the release of nitrites and bacterial growth. No substantial transformation of PETN (<45%) was observed during 21 d in M - C under aerobic conditions. Under anaerobic conditions, five cultures could transform PETN (up to 52% ± 13%) as the sole nitrogen source, concurrent with the formation of two unidentified metabolites. PETN-transforming cultures belonged to Alphaproteobacteria, Betaproteobacteria, Gammaproteobacteria, and Actinobacteria. In conclusion, we isolated 12 PETN-transforming cultures belonging to diverse taxa, suggesting that PETN transformation is phylogenetically widespread.

The time course of chromatic adaptation in human early visual cortex revealed by SSVEPs.

Previous studies have identified at least two components of chromatic adaptation: a rapid component with a time scale between tens of milliseconds to a few seconds, and a slow component with a half-life of about 10 to 30 seconds. The basis of the rapid adaptation probably lies in receptor adaptation at the retina. The neural substrate for the slow adaptation remains unclear, although previous psychophysical results hint at the early visual cortex. A promising approach to investigate adaptation effects in the visual cortex is to analyze steady-state visual evoked potentials (SSVEPs) elicited by chromatic stimuli, which typically use long durations of stimulation. Here, we re-analyzed the data from two previous pattern-reversal SSVEP studies. In these experiments (N = 49 observers in total), SSVEPs were elicited by counter-phase flickering color- or luminance-defined grating stimuli for 150 seconds in each trial. By analyzing SSVEPs with short time windows, we found that chromatic SSVEP responses decreased with increasing stimulation duration and reached a lower asymptote within a minute of stimulation. The luminance SSVEPs did not show any systematic adaptation. The time course of chromatic SSVEPs can be well described by an exponential decay function with a half-life of about 20 seconds, which is very close to previous psychophysical reports. Despite the difference in stimuli between the current and previous studies, the coherent time course may indicate a more general adaptation mechanism in the early visual cortex. In addition, the current result also provides a guide for future color SSVEP studies in terms of either avoiding or exploiting this adaptation effect.

A Review of Piezoelectric Footwear Energy Harvesters: Principles, Methods, and Applications.

Over the last couple of decades, numerous piezoelectric footwear energy harvesters (PFEHs) have been reported in the literature. This paper reviews the principles, methods, and applications of PFEH technologies. First, the popular piezoelectric materials used and their properties for PEEHs are summarized. Then, the force interaction with the ground and dynamic energy distribution on the footprint as well as accelerations are analyzed and summarized to provide the baseline, constraints, potential, and limitations for PFEH design. Furthermore, the energy flow from human walking to the usable energy by the PFEHs and the methods to improve the energy conversion efficiency are presented. The energy flow is divided into four processing steps: (i) how to capture mechanical energy into a deformed footwear, (ii) how to transfer the elastic energy from a deformed shoes into piezoelectric material, (iii) how to convert elastic deformation energy of piezoelectric materials to electrical energy in the piezoelectric structure, and (iv) how to deliver the generated electric energy in piezoelectric structure to external resistive loads or electrical circuits. Moreover, the major PFEH structures and working mechanisms on how the PFEHs capture mechanical energy and convert to electrical energy from human walking are summarized. Those piezoelectric structures for capturing mechanical energy from human walking are also reviewed and classified into four categories: flat plate, curved, cantilever, and flextensional structures. The fundamentals of piezoelectric energy harvesters, the configurations and mechanisms of the PFEHs, as well as the generated power, etc., are discussed and compared. The advantages and disadvantages of typical PFEHs are addressed. The power outputs of PFEHs vary in ranging from nanowatts to tens of milliwatts. Finally, applications and future perspectives are summarized and discussed.

Review of Applications of Density Functional Theory (DFT) Quantum Mechanical Calculations to Study the High-Pressure Polymorphs of Organic Crystalline Materials.

Since its inception, chemistry has been predominated by the use of temperature to generate or change materials, but applications of pressure of more than a few tens of atmospheres for such purposes have been rarely observed. However, pressure is a very effective thermodynamic variable that is increasingly used to generate new materials or alter the properties of existing ones. As computational approaches designed to simulate the solid state are normally tuned using structural data at ambient pressure, applying them to high-pressure issues is a highly challenging test of their validity from a computational standpoint. However, the use of quantum chemical calculations, typically at the level of density functional theory (DFT), has repeatedly been shown to be a great tool that can be used to both predict properties that can be later confirmed by experimenters and to explain, at the molecular level, the observations of high-pressure experiments. This article's main goal is to compile, analyze, and synthesize the findings of works addressing the use of DFT in the context of molecular crystals subjected to high-pressure conditions in order to give a general overview of the possibilities offered by these state-of-the-art calculations.

Chiral Supramolecular Multiblock Copolymerization Accompanying Chirality Transfer in Heterostructures via Living Chain Growth.

We report the unique synthesis of chiral supramolecular tri- and penta-BCPs with controllable chirality using kinetically adjusted seeded supramolecular copolymerization in THF and DMSO (99 : 1, v/v). Tetraphenylethylene (d- and l-TPE) derivatives bearing d- and l-alanine side chains formed thermodynamically favored chiral products via a kinetically trapped in monomeric state with a long lag phase. In contrast, achiral TPE-G containing glycine moieties did not form a supramolecular polymer owing to the energy barrier in its kinetically trapped state. We show that the copolymerization of the metastable states of TPE-G not only enables the generation of supramolecular BCPs by the seeded living growth method, but also transfers chirality at the seed ends. This research demonstrates the generation of chiral supramolecular tri- and penta-BCPs with B-A-B, A-B-A-B-A, and C-B-A-B-C block patterns accompanying chirality transfer via seeded living polymerization.

Prediction of the Mechanical Deformation Properties of Organic Crystals Based upon their Crystallographic Structures: Case Studies of Pentaerythritol and Pentaerythritol Tetranitrate.

PURPOSE: Development of a quantitative model and associated workflow for predicting the mechanical deformation properties (plastic deformation or cleavage fracture) of organic single crystals from their crystallographic structures using molecular and crystallographic modelling. METHODS: Intermolecular synthons, hydrogen bonding, crystal morphology and surface chemistry are modelled using empirical force fields with the data integrated into the analysis of lattice deformation as computed using a statistical approach. RESULTS: The approach developed comprises three main components. Firstly, the identification of the likely direction of deformation based on lattice unit cell geometry; secondly, the identification of likely lattice planes for deformation through the calculation of the strength and stereochemistry of interplanar intermolecular interactions, surface plane rugosity and surface energy; thirdly, identification of potential crystal planes for cleavage fracture by assessing intermolecular bonding anisotropy. Pentaerythritol is predicted to fracture by brittle cleavage on the {001} lattice planes by strong in-plane hydrogen-bond interactions in the <110>, whereas pentaerythritol tetranitrate is predicted to deform by plastic deformation through the slip system {110} < 001>, with both predictions being in excellent agreement with known experimental data. CONCLUSION: A crystallographic framework and associated workflow for predicting the mechanical deformation of molecular crystals is developed through quantitative assessment of lattice energetics, crystal surface chemistry and crystal defects. The potential for the de novo prediction of the mechanical deformation of pharmaceutical materials using this approach is highlighted for its potential importance in the design of formulated drug products process as needed for manufacture by direct compression.

Demonstration of High-Throughput Building Block and Composition Analysis of Metal-Organic Frameworks.

Metal-organic frameworks (MOFs) are composed of inorganic metal-containing nodes and organic linker groups and are promising porous materials for a wide range of applications. More than 90 000 different MOFs have been synthesized with different inorganic nodes, organic linkers, and node-linker connectivity patterns. While databases have been created to catalog this enormous number of structures, they generally do not provide functionality to easily search, sort, and understand MOFs based on composition and building blocks. Because structure-property relationships are critical to identify, here we outline our new program MOFseek and demonstrate that it can perform high-throughput structure and composition analyses of MOF structures. This program enables the fast analysis of tens of thousands of MOFs in databases based on the local chemical environment. We demonstrate the unique capabilities of MOFseek by analyzing the CoRE MOF database of structures.

Resolution and Frequency Effects on UAVs Semi-Direct Visual-Inertial Odometry (SVO) for Warehouse Logistics.

For the commercial sector, warehouses are becoming increasingly vital. Constant efforts are in progress to increase the efficiency of these facilities while reducing costs. The inventory part of the goods is a time-consuming task that impacts the company's revenue. This article presents an analysis of the performance of a state-of-the-art, visual-inertial odometry algorithm, SVO Pro Open, when varying the resolution and frequency of video streaming in an industrial environment. To perform efficiently this task, achieving an optimal system in terms of localization accuracy, robustness, and computational cost is necessary. Different resolutions are selected with a constant aspect ratio, and an accurate calibration for each resolution configuration is performed. A stable operating point in terms of robustness, accuracy of localization, and CPU utilization is found and the trends obtained are studied. To keep the system robust against sudden divergence, the feature loss factor extracted from optical sensors is analyzed. Innovative trends and translation errors on the order of a few tens of centimeters are achieved, allowing the system to navigate safely in the warehouse. The best result is obtained at a resolution of 636 × 600 px, where the localization errors (x, y, and z) are all under 0.25 m. In addition, the CPU (Central Processing Unit) usage of the onboard computer is kept below 60%, remaining usable for other relevant onboard processing tasks.

Transformation of TNT, 2,4-DNT, and PETN by Raoultella planticola M30b and Rhizobium radiobacter M109 and exploration of the associated enzymes.

The nitrated compounds 2,4-dinitrotoluene (2,4-DNT), 2,4,6-trinitrotoluene (TNT), and pentaerythritol tetranitrate (PETN) are toxic xenobiotics widely used in various industries. They often coexist as environmental contaminants. The aims of this study were to evaluate the transformation of 100 mg L-1 of TNT, 2,4-DNT, and PETN by Raoultella planticola M30b and Rhizobium radiobacter M109c and identify enzymes that may participate in the transformation. These strains were selected from 34 TNT transforming bacteria. Cupriavidus metallidurans DNT was used as a reference strain for comparison purposes. Strains DNT, M30b and M109c transformed 2,4-DNT (100%), TNT (100, 94.7 and 63.6%, respectively), and PETN (72.7, 69.3 and 90.7%, respectively). However, the presence of TNT negatively affects 2,4-DNT and PETN transformation (inhibition > 40%) in strains DNT and M109c and fully inhibited (100% inhibition) 2,4-DNT transformation in R. planticola M30b.Genomes of R. planticola M30b and R. radiobacter M109c were sequenced to identify genes related with 2,4-DNT, TNT or PETN transformation. None of the tested strains presented DNT oxygenase, which has been previously reported in the transformation of 2,4-DNT. Thus, unidentified novel enzymes in these strains are involved in 2,4-DNT transformation. Genes encoding enzymes homologous to the previously reported TNT and PETN-transforming enzymes were identified in both genomes. R. planticola M30b have homologous genes of PETN reductase and xenobiotic reductase B, while R. radiobacter M109c have homologous genes to GTN reductase and PnrA nitroreductase. The ability of these strains to transform explosive mixtures has a potentially biotechnological application in the bioremediation of contaminated environments.

Tandem Ion Mobility Spectrometry for the Detection of Traces of Explosives in Cargo at Concentrations of Parts Per Quadrillion.

A tandem ion mobility spectrometer (IMS2) built from two differential mobility analyzers (DMAs) is coupled at ambient pressure with a thermal fragmenter placed in between, such that the precursor ions selected in the first DMA are thermally decomposed at ambient pressure in the fragmenter and the product ions generated are filtered in the second DMA. A thermal desorber and a multicapillary gas chromatography (GC) column are coupled to a secondary electrospray (SESI) ion source, so the adsorption sampling filters are thermally desorbed and the liberated vapors are separated in the GC column, prior to their ionization and mobility/mobility classification. The new fragmenter allows the fragmentation of the five explosives studied: RDX, PETN, NG, EGDN, and TNT. The background of the analyzer is evaluated for the five explosives using air samples of 500 L volume. An atmospheric background of only 2.5 pg (5 ppq) is found for TNT, being somewhat higher for the rest of explosives studied. The architecture GC-IMS2 is compared with GC-IMS obtaining a 100-fold increase of sensitivity in the first configuration, confirming the high selectivity provided by the fragmentation cell and the second IMS stage for the product ion mobility analysis. The analyzer is tested also with real explosives hidden in cargo pallets achieving successful detection of four (EGDN, NG, TNT, and PETN) out of five explosives.