Response Map Research Articles

A Robust AR-DSNet Tracking Registration Method in Complex Scenarios

A robust AR-DSNet (Augmented Reality method based on DSST and SiamFC networks) tracking registration method in complex scenarios is proposed to improve the ability of AR (Augmented Reality) tracking registration to distinguish target foreground and semantic interference background, and to address the issue of registration failure caused by similar target drift when obtaining scale information based on predicted target positions. Firstly, the pre-trained network in SiamFC (Siamese Fully-Convolutional) is utilized to obtain the response map of a larger search area and set a threshold to filter out the initial possible positions of the target; Then, combining the advantage of the DSST (Discriminative Scale Space Tracking) filter tracker to update the template online, a new scale filter is trained after collecting multi-scale images at the initial possible position of target to reason the target scale change. And linear interpolation is used to update the correlation coefficient to determine the final position of target tracking based on the difference between two frames. Finally, ORB (Oriented FAST and Rotated BRIEF) feature detection and matching are performed on the accurate target position image, and the registration matrix is calculated through matching relationships to overlay the virtual model onto the real scene, achieving enhancement of the real world. Simulation experiments show that in complex scenarios such as similar interference, target occlusion, and local deformation, the proposed AR-DSNet method can complete the registration of the target in AR 3D tracking, ensuring real-time performance while improving the robustness of the AR tracking registration algorithm.

Structure-function in smokers: when a small airways test really reflects the small airways.

If multiple-breath washout (MBW)-derived acinar ventilation heterogeneity (Sacin) really represents peripheral units, the N2 phase-III of the first MBW exhalation should be curvilinear. This is essentially due to the superposed effect of gas diffusion and convection resulting in an equilibration of N2 concentrations between neighboring lung units throughout exhalation. We investigated this in smokers with computed tomography (CT)-proven functional small airway disease. Instantaneous N2-slopes were computed over 40-ms intervals throughout phase-III and normalized by mean phase-III N2 concentration. N2 phase-III (concave) curvilinearity was quantified as the rate at which the instantaneous N2-slope decreases past the phase-II peak over a 1-s interval; for a linear N2 phase-III unaffected by diffusion, this rate would amount to 0 L-1/s. N2 phase-III curvilinearity was obtained on the experimental curves and on existing model simulations of N2 curves from a normal peripheral lung model and one with missing terminal bronchioles (either 50% or 30% TB left). In 46 smokers [66 (±8) yr; 49 (±26) pack·yr] with CT-based evidence of peripheral lung destruction, instantaneous N2-slope decrease was compared between those with (fSAD+fEmphys) > 20% [-0.26 ± 0.14 (SD) L-1/s; n = 24] and those with (fSAD+fEmphys) < 20% [-0.16 ± 0.12 (SD) L-1/s; n = 22] (P = 0.014). Experimental values fell in the range predicted by a realistic peripheral lung model with progressive reduction of terminal bronchioles: values of instantaneous N2-slope decrease obtained from model simulations were -0.09 L-1/s (normal lung; 100% TB left), -0.17 L-1/s (normal lung 50% TB left), and -0.29 L-1/s (30% TB left). In smokers with CT-based evidence of functional small airway alterations, it is possible to demonstrate that Sacin really does represent the most peripheral airspaces.NEW & NOTEWORTHY In smokers with computed tomography-based evidence of functional small airway alterations by parametric response mapping, it is possible to demonstrate that the multiple-breath washout-derived Sacin, an index of acinar ventilation heterogeneity, actually does represent the most peripheral airspaces. This is done by verifying on experimental N2 washout curves of the first breath, N2 phase-III concavity predicted by the diffusion-convection interdependence model.

Structural Mapping of Polyclonal IgG Responses to HA After Influenza Virus Vaccination or Infection.

Cellular and molecular characterization of immune responses elicited by influenza virus infection and seasonal vaccination have informed efforts to improve vaccine efficacy, breadth, and longevity. Here, we use negative stain electron microscopy polyclonal epitope mapping (nsEMPEM) to structurally characterize the humoral IgG antibody responses to hemagglutinin (HA) from human patients vaccinated with a seasonal quadrivalent flu vaccine or infected with influenza A viruses. Our data show that both vaccinated and infected patients had humoral IgGs targeting highly conserved regions on both H1 and H3 subtype HAs, including the stem and anchor, which are targets for universal influenza vaccine design. Responses against H1 predominantly targeted the central stem epitope in infected patients and vaccinated donors, whereas head epitopes were more prominently targeted on H3. Responses against H3 were less abundant, but a greater diversity of H3 epitopes were targeted relative to H1. While our analysis is limited by sample size, on average, vaccinated donors responded to a greater diversity of epitopes on both H1 and H3 than infected patients. These data establish a baseline for assessing polyclonal antibody responses in vaccination and infection, providing context for future vaccine trials and emphasizing the importance of carefully designing vaccines to boost protective responses towards conserved epitopes.

Ferroelectric Texture of Individual Barium Titanate Nanocrystals.

Ferroelectric materials display exotic polarization textures at the nanoscale that could be used to improve the energetic efficiency of electronic components. The vast majority of studies were conducted in two dimensions on thin films that can be further nanostructured, but very few studies address the situation of individual isolated nanocrystals (NCs) synthesized in solution, while such structures could have other fields of applications. In this work, we experimentally and theoretically studied the polarization texture of ferroelectric barium titanate (BaTiO3, BTO) NCs attached to a conductive substrate and surrounded by air. We synthesized NCs of well-defined quasicubic shape and 160 nm average size that conserve the tetragonal structure of BTO at room temperature. We then investigated the inverse piezoelectric properties of such pristine individual NCs by vector piezoresponse force microscopy (PFM), taking particular care to suppress electrostatic artifacts. In all of the NCs studied, we could not detect any vertical PFM signal, and the maps of the lateral response all displayed larger displacement amplitude on the edges with deformations converging toward the center. Using field phase simulations dedicated to ferroelectric nanostructures, we were able to predict the equilibrium polarization texture. These simulations revealed that the NC core is composed of 180° up and down domains defining the polar axis that rotate by 90° in the two facets orthogonal to this axis, eventually lying within these planes forming a layer of about 10 nm thickness mainly composed of 180° domains along an edge. From this polarization distribution, we predicted the lateral PFM response, which was revealed to be in very good qualitative agreement with the experimental observations. This work positions PFM as a relevant tool to evaluate the potential of complex ferroelectric nanostructures to be used as sensors.

Robust Audio-Visual Contrastive Learning for Proposal-Based Self-Supervised Sound Source Localization in Videos.

By observing a scene and listening to corresponding audio cues, humans can easily recognize where the sound is. To achieve such cross-modal perception on machines, existing methods take advantage of the maps obtained by interpolation operations to localize the sound source. As semantic object-level localization is more attractive for prospective practical applications, we argue that these map-based methods only offer a coarse-grained and indirect description of the sound source. Additionally, these methods utilize a single audio-visual tuple at a time during self-supervised learning, causing the model to lose the crucial chance to reason about the data distribution of large-scale audio-visual samples. Although the introduction of Audio-Visual Contrastive Learning (AVCL) can effectively alleviate this issue, the contrastive set constructed by randomly sampling is based on the assumption that the audio and visual segments from all other videos are not semantically related. Since the resulting contrastive set contains a large number of faulty negatives, we believe that this assumption is rough. In this paper, we advocate a novel proposal-based solution that directly localizes the semantic object-level sound source, without any manual annotations. The Global Response Map (GRM) is incorporated as an unsupervised spatial constraint to filter those instances corresponding to a large number of sound-unrelated regions. As a result, our proposal-based Sound Source Localization (SSL) can be cast into a simpler Multiple Instance Learning (MIL) problem. To overcome the limitation of random sampling in AVCL, we propose a novel Active Contrastive Set Mining (ACSM) to mine the contrastive sets with informative and diverse negatives for robust AVCL. Our approaches achieve state-of-the-art (SOTA) performance when compared to several baselines on multiple SSL datasets with diverse scenarios.

Parametric response mapping of co-registered intravoxel incoherent motion magnetic resonance imaging and positron emission tomography in locally advanced cervical cancer undergoing concurrent chemoradiation therapy

Background and PurposeIntravoxel-incoherent-motion (IVIM) magnetic-resonance-imaging (MRI) and positron-emission-tomography (PET) have been investigated independently but not voxel-wise to evaluate tumor microenvironment in cervical carcinoma patients. Whether regionally combined information of IVIM and PET offers additional predictive benefit over each modality independently has not been explored. Here, we investigated parametric-response-mapping (PRM) of co-registered PET and IVIM in cervical cancer patients to identify sub-volumes that may predict tumor shrinkage to concurrent-chemoradiation-therapy (CCRT). Materials and MethodsTwenty cervical cancer patients (age: 63[41–85]) were retrospectively evaluated. Diffusion-weighted-images (DWIs) were acquired on 3.0 T MRIs using a free-breathing single-shot-spin echo-planar-imaging (EPI) sequence. Pre- and on-treatment (∼after four-weeks of CCRT) MRI and pre-treatment FDG-PET/CT were acquired. IVIM model-fitting on the DWIs was performed using a Bayesian-fitting simplified two-compartment model. Three-dimensional rigidly-registered maps of PET/CT standardized-uptake-value (SUV) and IVIM diffusion-coefficient (D) and perfusion-fraction (f) were generated. Population-means of PET-SUV, IVIM-D and IVIM-f from pre-treatment-scans were calculated and used to generate PRM via a voxel-wise joint-histogram-analysis to classify voxels as high/low metabolic-activity and with high/low (hi/lo) cellular-density. Similar PRM maps were generated for SUV and f. ResultsTumor-volume (p < 0.001) significantly decreased, while IVIM-f (p = 0.002) and IVIM-D (p = 0.03) significantly increased on-treatment. Pre-treatment tumor-volume (r = -0.45,p = 0.04) and PRM-SUVhiDlo (r = -0.65,p = 0.002) negatively correlated with ΔGTV, while pre-treatment IVIM-D (r = 0.64,p = 0.002), PRM-SUVlofhi (r = 0.52,p = 0.02), and PRM-SUVloDhi (r = 0.74,p < 0.001) positively correlated with ΔGTV. ConclusionIVIM and PET was performed on cervical cancer patients undergoing CCRT and we observed that both IVIM-f and IVIM-D increased during treatment. Additionally, PRM was applied, and sub-volumes were identified that were related to ΔGTV.

Peak response regularization for localization

Deep convolutional neural networks approaches often assume that the feature response has a Gaussian distribution with target-centered peak response, which can be used to guide the target location and classification. Nevertheless, such an assumption is implausible when there is progressive interference from other targets and/or background noise, which produces sub-peaks on the tracking response map and causes model drift. In this paper, we propose a feature response regularization approach for sub-peak response suppression and peak response enforcement and aim to handle progressive interference systematically. Our approach, referred to as Peak Response Regularization (PRR), applies simple-yet-efficient method to aggregate and align discriminative features, which convert local extremal response in discrete feature space to extremal response in continuous space, which enforces the localization and representation capability of convolutional features. Experiments on human pose detection, object detection, object tracking, and image classification demonstrate that PRR improves the performance of image tasks with a negligible computational cost.

Synergistic olfactory processing for social plasticity in desert locusts

Desert locust plagues threaten the food security of millions. Central to their formation is crowding-induced plasticity, with social phenotypes changing from cryptic (solitarious) to swarming (gregarious). Here, we elucidate the implications of this transition on foraging decisions and corresponding neural circuits. We use behavioral experiments and Bayesian modeling to decompose the multi-modal facets of foraging, revealing olfactory social cues as critical. To this end, we investigate how corresponding odors are encoded in the locust olfactory system using in-vivo calcium imaging. We discover crowding-dependent synergistic interactions between food-related and social odors distributed across stable combinatorial response maps. The observed synergy was specific to the gregarious phase and manifested in distinct odor response motifs. Our results suggest a crowding-induced modulation of the locust olfactory system that enhances food detection in swarms. Overall, we demonstrate how linking sensory adaptations to behaviorally relevant tasks can improve our understanding of social modulation in non-model organisms.

Proteomics Analysis of Proteotoxic Stress Response in In-Vitro Human Neuronal Models.

Heat stroke, a hazardous hyperthermia-related illness, is characterized by CNS injury, particularly long-lasting brain damage. A root cause for hyperthermic neurological damage is heat-induced proteotoxic stress through protein aggregation, a known causative agent of neurological disorders. Stress magnitude and enduring persistence are highly correlated with hyperthermia-associated neurological damage. We used an untargeted proteomic approach using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify and characterize time-series proteome-wide changes in dose-responsive proteotoxic stress models in medulloblastoma [Daoy], neuroblastoma [SH-SY5Y], and differentiated SH-SY5Y neuron-like cells [SH(D)]. An integrated analysis of condition-time datasets identified global proteome-wide differentially expressed proteins (DEPs) as part of the heat-induced proteotoxic stress response. The condition-specific analysis detected higher DEPs and upregulated proteins in extreme heat stress with a relatively conservative and tight regulation in differentiated SH-SY5Y neuron-like cells. Functional network analysis using ingenuity pathway analysis (IPA) identified common intercellular pathways associated with the biological processes of protein, RNA, and amino acid metabolism and cellular response to stress and membrane trafficking. The condition-wise temporal pathway analysis in the differentiated neuron-like cells detects a significant pathway, functional, and disease association of DEPs with processes like protein folding and protein synthesis, Nervous System Development and Function, and Neurological Disease. An elaborate dose-dependent stress-specific and neuroprotective cellular signaling cascade is also significantly activated. Thus, our study provides a comprehensive map of the heat-induced proteotoxic stress response associating proteome-wide changes with altered biological processes. This helps to expand our understanding of the molecular basis of the heat-induced proteotoxic stress response with potential translational connotations.

Mapping Kansas City cardiomyopathy, Seattle Angina, and minnesota living with heart failure to the MacNew-7D in patients with heart disease.

The Kansas City Cardiomyopathy Questionnaire (KCCQ), Seattle Angina Questionnaire (SAQ), and Minnesota Living with Heart Failure Questionnaire (MLHFQ) are widely used non-preference-based instruments that measure health-related quality of life (QOL) in people with heart disease. However, currently it is not possible to estimate quality-adjusted life-years (QALYs) for economic evaluation using these instruments as the summary scores produced are not preference-based. The MacNew-7D is a heart disease-specific preference-based instrument. This study provides different mapping algorithms for allocating utility scores to KCCQ, MLHFQ, and SAQ from MacNew-7D to calculate QALYs for economic evaluations. The study included 493 participants with heart failure or angina who completed the KCCQ, MLHFQ, SAQ, and MacNew-7D questionnaires. Regression techniques, namely, Gamma Generalized Linear Model (GLM), Bayesian GLM, Linear regression with stepwise selection and Random Forest were used to develop direct mapping algorithms. Cross-validation was employed due to the absence of an external validation dataset. The study followed the Mapping onto Preference-based measures reporting Standards checklist. The best models to predict MacNew-7D utility scores were determined using KCCQ, MLHFQ, and SAQ item and domain scores. Random Forest performed well for item scores for all questionnaires and domain score for KCCQ, while Bayesian GLM and Linear Regression were best for MLHFQ and SAQ domain scores. However, models tended to over-predict severe health states. The three cardiac-specific non-preference-based QOL instruments can be mapped onto MacNew-7D utilities with good predictive accuracy using both direct response mapping techniques. The reported mapping algorithms may facilitate estimation of health utility for economic evaluations that have used these QOL instruments.

SAR target recognition through adaptive kernel sparse representation model based on local contrast perception

Sparse representation-based methods have shown promising prospects in synthetic aperture radar (SAR) target recognition due to their robustness under complex application conditions. However, these methods are still susceptible to the feature representation of SAR images. In this paper, we propose a new SAR target recognition method using an adaptive kernel sparse representation model based on local contrast perception (LCP). The LCP method combines a specially designed random projection matrix with two-dimensional filtering to capture extensive intensity contrasts between local regions in SAR images. A response map reconstruction technique shows that LCP can obtain discriminative properties between target and background regions and improve feature representation. The LCP features are then transformed into the kernel representation to improve linear separability by defining a reproducing kernel Hilbert space (RKHS) and using a nonlinear kernel function. The kernel representation is utilized to construct a new kernel sparse representation model for classification. Furthermore, neighborhood analysis (NA) is proposed to establish the relationship between the parameter and feature distribution, with an adaptive regularization parameter selection strategy to mitigate the parameter sensitivity. Experiments conducted on the moving and stationary target acquisition and recognition dataset demonstrate the superiority and robustness of the proposed method under different application conditions.

Output-only response mapping of bridges for dynamic response estimation of gusset plate using convolutional neural networks

Output-only response mapping of bridges for dynamic response estimation of gusset plate using convolutional neural networks

Real-time and highly responsive hydrogen mapping in pure Fe using TiO2 thin films

A hydrogen visualization method with high responsivity and chemical stability under atmospheric corrosion is necessary to inhibit hydrogen embrittlement, which can occur with hydrogen uptake of structural materials. In this study, a highly responsive hydrogen mapping technique for steels was successfully established using a TiO2 thin film and Pd intermediate layer. The color of the TiO2 film on the hydrogen-detection side changes during hydrogen charging on the hydrogen-entry side of the Fe specimen, indicating that the color changes were attributed to the hydrogen uptake of the Fe surface and subsequent introduction of hydrogen atoms to the TiO2 film. Considering the responsivity and visibility, the optimal thickness of the TiO2 film was determined to be 20 nm. As TiO2 is a chemically stable material, the proposed mapping technique can be used to monitor the hydrogen absorbed into metallic materials under outdoor conditions.

A comprehensive genetic map of cytokine responses in Lyme borreliosis

The incidence of Lyme borreliosis has risen, accompanied by persistent symptoms. The innate immune system and related cytokines are crucial in the host response and symptom development. We characterized cytokine production capacity before and after antibiotic treatment in 1,060 Lyme borreliosis patients. We observed a negative correlation between antibody production and IL-10 responses, as well as increased IL-1Ra responses in patients with disseminated disease. Genome-wide mapping the cytokine production allowed us to identify 34 cytokine quantitative trait loci (cQTLs), with 31 novel ones. We pinpointed the causal variant at the TLR1-6-10 locus and validated the regulation of IL-1Ra responses at transcritpome level using an independent cohort. We found that cQTLs contribute to Lyme borreliosis susceptibility and are relevant to other immune-mediated diseases. Our findings improve the understanding of cytokine responses in Lyme borreliosis and provide a genetic map of immune function as an expanded resource.

The multi-omic response to exercise training across rat tissues: interactive tools for data dissemination through the MoTrPAC data hub

The Molecular Transducers of Physical Activity Consortium (MoTrPAC) aims to map the molecular responses to exercise and training to elucidate how exercise improves health and prevents disease. The first MoTrPAC data provides an extensive temporal map of the dynamic multi-omic response to endurance training across multiple rat tissues. All results can be viewed, interrogated, and downloaded in a user-friendly, publicly accessible data portal ( https://motrpac-data.org ). The MoTrPAC data compendium includes transcriptomics, proteomics, metabolomics, phosphoproteomics, acetylproteomics, ubiquitylproteomics, DNA methylation, chromatin accessibility, and multiplexed immunoassay data. This compilation of 211 datasets across 19 tissues, 25 molecular assays, and 4 training time points in adult male and female rats constitutes 19 terabytes of data. Over 35,000 analytes were found to be differentially regulated in response to endurance training, with many displaying sexual dimorphism. We observed a male-specific recruitment of immune cells to adipose tissues and an anticorrelated transcriptional response in the adrenal gland related to the stress response. Temporal multi-omic and multi-tissue integration demonstrated similar temporal responses in the heart and skeletal muscle, reflecting a concerted adaptation of mitochondrial biogenesis and metabolism. Integrative multi-omic network analysis revealed connections between the heat shock-mediated stress response and mitochondrial biogenesis. Training increased phospholipids and decreased triacylglycerols in the liver, and there were extensive changes to mitochondrial protein acetylation. Many changes were relevant for human health conditions, such as non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular wellness, and tissue damage and repair. Altogether, this MoTrPAC resource provides an unprecedented view of the effects of exercise across an organism, revealing mechanistic details of how exercise impacts mammalian health. The MoTrPAC data hub is the primary online resource to disseminate this large scale multi-omics data. The MoTrPAC Study is supported by NIH grants U24OD026629 (Bioinformatics Center), U24DK112349, U24DK112342, U24DK112340, U24DK112341, U24DK112326, U24DK112331, U24DK112348 (Chemical Analysis Sites), U24AR071113 (Consortium Coordinating Center), U01AG055133, U01AG055137 and U01AG055135 (PASS/Animal Sites). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Determining optimal surveillance techniques for the microbial community on human skin using RNAseq data analysis

Background: The largest organ in the human body, the skin, serves as a physical barrier to the outside world. It also houses millions of bacteria, viruses, and fungi that protect us against invading pathogens or result in altered physiology and disease. These microorganisms can contribute to normal skin health or predispose individuals to pathogenic disorders. Surveillance and observation of the microbiome can give insight into identifying common taxa that compose our skin and indications of new or changing pathogens. However, to do this effciently, it is important to understand what can be detected from skin samples and the differences we may see using various collection methods. Methods: We used publicly available NCBI SRA RNAseq bioprojects that queried “skin,” processing 132 bioprojects with 8,274 samples. Using FastQC, Salmon, KRAKEN2, and MiCXR/Immunarch, we aimed to analyze the quality, human gene transcripts, infections, and B/T- cell responses, respectively. We aimed to identify what skin sampling method provides the best data on the skin microbiome, human gene mapping, and B/T-cell immune repertoire. This project is based on observational methods, not a specific hypothesis. Results: From the KRAKEN2 data, there were 14,383 viruses and 14,691 bacteria assessed through all “skin” BioProjects. From the extensive data pool, we identified unique BioProject signatures for protest (Leishmania), bacteria (Mycoplasma), and viruses (HSV1 dose dependencies, HPV in human warts, Chinese transmitted tick viruses, Human T-cell lymphotropic virus, and the first-ever human case of equine infectious anemia virus). The use of read mapping and coverage is critical to confirming the presence of foreign species, noted through the observation of T4 DNA ligase RNA presence prior to 2018 RNA sequencing. Once pathogens were detected, cellular response mapping was developed, yielding insights into the pathophysiology of multiple viral infections of the skin and sex differences. Conclusion: Detecting a wide variety of microorganisms on the skin can give insight into dermatological pathologies and skin physiology. Using the publicly available skin datasets, we see many unique stories of microorganisms in the skin. This big data mapping strategy highlights the importance of broad observational mapping, possible with cutting-edge sequencing tools. This work was supported by the MI-SAPPHIRE program of MDHHS and the CDC. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

High Spatiotemporal Resolution Radial Encoding Single-Vessel fMRI.

High-field preclinical functional MRI (fMRI) is enabled the high spatial resolution mapping of vessel-specific hemodynamic responses, that is single-vessel fMRI. In contrast to investigating the neuronal sources of the fMRI signal, single-vessel fMRI focuses on elucidating its vascular origin, which can be readily implemented to identify vascular changes relevant to vascular dementia or cognitive impairment. However, the limited spatial and temporal resolution of fMRI is hindered hemodynamic mapping of intracortical microvessels. Here, the radial encoding MRI scheme is implemented to measure BOLD signals of individual vessels penetrating the rat somatosensory cortex. Radial encoding MRI is employed to map cortical activation with a focal field of view (FOV), allowing vessel-specific functional mapping with 50×50 µm2 in-plane resolution at a 1 to 2 Hz sampling rate. Besides detecting refined hemodynamic responses of intracortical micro-venules, the radial encoding-based single-vessel fMRI enables the distinction of fMRI signals from vessel and peri-vessel voxels due to the different contribution of intravascular and extravascular effects.

The Contribution of Scanning Force Microscopy on Dental Research: A Narrative Review.

Scanning force microscopy (SFM) is one of the most widely used techniques in biomaterials research. In addition to imaging the materials of interest, SFM enables the mapping of mechanical properties and biological responses with sub-nanometer resolution and piconewton sensitivity. This review aims to give an overview of using the scanning force microscope (SFM) for investigations on dental materials. In particular, SFM-derived methods such as force-distance curves (scanning force spectroscopy), lateral force spectroscopy, and applications of the FluidFM® will be presented. In addition to the properties of dental materials, this paper reports the development of the pellicle by the interaction of biopolymers such as proteins and polysaccharides, as well as the interaction of bacteria with dental materials.

Analysing the use of OpenAerialMap images for OpenStreetMap edits

ABSTRACT OpenAerialMap (OAM) is a crowdsourcing platform for uploading, hosting, sharing, displaying, searching, and downloading openly licensed Earth image data from around the world. OAM was launched with the primary goal to facilitate rapid disaster response mapping after natural events, such as floods or hurricanes. Images contributed to OAM can be used as a background layer in OpenStreetMap (OSM) editors to edit map features, such as buildings or facilities, which may have been affected by such events. This study analyzes how the provision of OAM images is associated with changes in underlying editing patterns of OSM features by comparing the number of edited OSM objects between 2 weeks before and 2 weeks after an image has been shared through OAM. The comparison also involves other aspects of OSM editing patterns, including geometry types and OSM primary feature types of edited objects, type of feature editing operations, edits per user, and contribution distribution across continents. Results show that the number of point features added to OSM more than quadrupled within the first 2 weeks after OAM image upload compared to that of 2 weeks before, and that the number of ways added almost doubled. This suggests that the OSM community utilizes provided OAM images for OSM map updates in the respective geographic areas. The study provides a showcase which demonstrates how information from one crowdsourcing platform (OAM) can be used to enhance the data quality of another (OSM) with regards to completeness and timeliness.

Suitability Study of Biofuel Blend for Light Commercial Vehicle Application under Real-World Transient Operating Conditions

&lt;div&gt;Driving schedule of every vehicle involves transient operation in the form of changing engine speed and load conditions, which are relatively unchanged during steady-state conditions. As well, the results from transient conditions are more likely to reflect the reality. So, the current research article is focused on analyzing the biofuel-like lemon peel oil (LPO) behavior under real-world transient conditions with fuel injection parameter MAP developed from steady-state experiments. At first, engine parameters and response MAPs are developed by using a response surface methodology (RSM)-based multi-objective optimization technique. Then, the vehicle model has been developed by incorporating real-world transient operating conditions. Finally, the developed injection parameters and response MAPs are embedded in the vehicle model to analyze the biofuel behavior under transient operating conditions. The results obtained for diesel-fueled light commercial vehicle (LCV) have shown better fuel economy than LPO biofuel with their developed fuel injection parameter MAP. The maximum BTE obtained was 29.7% for diesel and 29.5% for LPO at 2100 rpm and 20 Nm torque. The mean HC emissions were identified as 0.02046 g/km for diesel and 0.03488 g/km for LPO fuel over the modified Indian driving cycle (MIDC). Except for NOx emission, LPO biofuel exhibited diesel-like performance and emission characteristics under the MIDC.&lt;/div&gt;