Conventional Mapping Techniques Research Articles

Joint PAPR reduction and channel estimation in low-complexity VLC systems

In recent times, there has been a surge in interest surrounding visible light communication (VLC) as a compelling adjunct to radio frequency (RF) technology. This enthusiasm stems from deployments showcasing its efficacy in high-speed data transmission, characterized by low complexity, robust security, and high reliability. Among the variants of orthogonal frequency division multiplexing (OFDM), direct current-biased optical OFDM (DCO-OFDM) stands out in the realm of VLC systems, owing to its ability to furnish rapid data provisioning. However, a significant drawback of selective mapping (SLM) based DCO-OFDM transceivers lies in its computational complexity and practical implementation challenges. To address this limitation, this paper presents a modified SLM technique termed selective phase modulation (SPM) aimed at mitigating the peak-to-average power ratio (PAPR) in the transmitter section while simplifying the data decoding process at the receiver end. The SPM method utilizes a phase modulation and demodulation process based on clusters and assisted by pilot signals, streamlining the transceiver architecture. The SPM methodology offers reduced computational complexity at the transmitter by selectively applying phase sequences to data, circumventing the necessity for side information (SI) transmission and SI estimation at the receiver with a known pilot symbol inserted in the data. This dual-functionality mechanism not only achieves complexity reduction but also facilitates channel estimation at the receiver for proper data recovery. Based on complexity analysis and simulation outcomes, the computational complexity reduction strategy outperforms the conventional selective mapping (CSLM) technique, VLC-based pilot-assisted PAPR reduction systems, and embedded coded modulation (ECM). This allows for smooth incorporation of this technology into future VLC systems.

Optical super-resolution nanothermometry via stimulated emission depletion imaging of upconverting nanoparticles.

From engineering improved device performance to unraveling the breakdown of classical heat transfer laws, far-field optical temperature mapping with nanoscale spatial resolution would benefit diverse areas. However, these attributes are traditionally in opposition because conventional far-field optical temperature mapping techniques are inherently diffraction limited. Optical super-resolution imaging techniques revolutionized biological imaging, but such approaches have yet to be applied to thermometry. Here, we demonstrate a super-resolution nanothermometry technique based on highly doped upconverting nanoparticles (UCNPs) that enable stimulated emission depletion (STED) super-resolution imaging. We identify a ratiometric thermometry signal and maintain imaging resolution better than ~120 nm for the relevant spectral bands. We also form self-assembled UCNP monolayers and multilayers and implement a detection scheme with scan times >0.25 μm2/min. We further show that STED nanothermometry reveals a temperature gradient across a joule-heated microstructure that is undetectable with diffraction limited thermometry, indicating the potential of this technique to uncover local temperature variation in wide-ranging practical applications.

Collaboration and term usage dynamics in agricultural buffer strip research: Research weaving

Abstract Systematic maps are used to comprehensively gather and describe the literature on a topic, which is often defined by policy and practice relevance and stakeholder input, identifying trends and gaps in research. Bibliometric methods elucidate the connections between publications, for example, providing information about collaboration in research communities. Research weaving combines these approaches to produce a comprehensive view of research activity on a well‐defined research area. In this paper, we conduct and describe a bibliometric analysis on a previously published systematic map on the functional roles of buffer strips in agricultural fields. Among other findings, the original systematic map found a paucity of studies addressing multiple functional roles and a huge variation in terminology related to buffer strips. We used research weaving to deepen our understanding of these findings and shed light on collaboration within and among the research communities contributing knowledge to this field. Of the 1019 papers originally included in the systematic map, 930 were identified in Lens.org and used for subsequent analyses. Co‐authorship and bibliographic coupling networks identified distinct research communities, defined by geography, subdiscipline and characteristic usage of buffer strip terminology. Topic modelling provided further information about these subcommunities and aligned with manually extracted information about the studies' focus on functional roles, indicating potential utility for screening of records in large systematic maps. Practical Implication: We demonstrate that research weaving methods add insights in support of and in addition to the original systematic map. We provide a methodological approach and discuss limitations related to applying bibliometric analyses to a previously published systematic map. We demonstrate the feasibility of this approach and its ability to enhance and enrich the findings gained from conventional systematic mapping techniques.

Land use Change Detection Methodologies and Techniques for Remotely Sensed Images

The increasing land use changes leading to urban expansion have attracted the researches. Urbanization has become a recent growing trend in many cities around the world. In most cases to estimate the urban expansion with the conventional survey and mapping techniques is expensive and time consuming. Remote sensing is increasingly used for detection and analysis of urban expansion since it is cost effective and technologically efficient. This paper aims to give the taxonomy of various methods and techniques to analyze the land use change detection through remote sensing images in an effective manner. One of the most important functions of remote sensing data is Land Use and Land Cover maps managed through image classification. This describes the various classifiers, software and image digitization techniques that are used in estimating the urban changes. Wide database of images has been used to test the algorithms. Hence, an in-depth study of existing work related to land use change detection will help to accelerate research in the field of urban change. This paper presents a systematic analysis of work done in land use change detection area. We also present a Comparison of existing methods and techniques used for land use change detection. Based on this analysis, we finally presented a few future research directions related to land use change detection through remote sensing images, which will be reduce uncertainties in the image-processing chain to improve classification accuracy.

Mapping and discrimination of the mineralization potential in granitoids from Banyo area (Adamawa, Cameroon), using Landsat 9 OLI, ASTER images and field observations

The Banyo area is situated in the west Cameroon domain of the Central African Fold Belt. In this study, field data and remote sensing conventional mapping techniques including Red-Green-Blue (RGB) colour combination, principal component analysis (PCA), Crosta-PCA, Band Ratios (BR), Constrained Energy Minimization (CEM), Minimum Noise Fraction (MNF), Spectral Angle Mapper (SAM) classification and Linear Spectral Unmixing (LSU) algorithms were used to process Landsat 9 OLI and ASTER data in order to discriminate various rock units such as biotite-amphibole granites, hornblende-biotite orthogneiss and map associated mineral deposits (e.g., iron-oxide, hydroxyl and corundum minerals). In addition, it was found that RGB combination (743) of OLI bands, PCA of OLI bands (PC123), BR of OLI bands (4/2, 6/7, 6/5), BR of ASTER (4/2, 7/6, 8/9), Crosta-PCA of OLI bands, MNF (123) of OLI bands, SAM, and LSU techniques applied to ASTER bands ascertain potential locations of granitoids and gneisses bearing iron and hydroxyl minerals. On the other hand, this study also revealed that corundum deposits are detected by applying the CEM method to OLI band ratio 6/7 highlighting red tones and processing SAM classification algorithm both using laboratory reference spectra. Automatic (using PCI Geomatica line tool) and manual extractions of lineaments revealed three major trends (N-S, E-W, and WNW-ESE to NW-SE) and an accessory trend (NE-SW to ENE-WSW) that surround hydrothermally altered rocks recognized as containing iron oxide, hydroxyl, and corundum mineral deposits. In the field, these lineaments may group to the tree deformation phases. The D1 phase (NW-SE); the D2 phase (NE-SW to ENE-WSW) and the D3 phase (N-S). Maximum Likelihood Calssification (MLC) and SAM classification methods showed to be more effective in discriminating rocks bearing Iron-oxide, hydroxyl and corundum minerals in the study area.This result permits to confirm that, the combination of remote sensing (Landsat 9 OLI and ASTER data in this case) and field data constitute a useful tool for mineral exploration in the shear zone. However, the accuracy assessment was relied on comparing the different maps produced from Landsat 9 OLI and ASTER data with the ground truth sample points and also, with the earliest geological map of Banyo area. Thus, quantitatively the results were accurate at 99%.

Cryptic MHC-E epitope from influenza elicits a potent cytolytic T cell response.

The extent to which unconventional forms of antigen presentation drive T cell immunity is unknown. By convention, CD8 T cells recognize viral peptides, or epitopes, in association with classical major histocompatibility complex (MHC) class I, or MHC-Ia, but immune surveillance can, in some cases, be directed against peptides presented by nonclassical MHC-Ib, in particular the MHC-E proteins (Qa-1 in mice and HLA-E in humans); however, the overall importance of nonclassical responses in antiviral immunity remains unclear. Similarly uncertain is the importance of 'cryptic' viral epitopes, defined as those undetectable by conventional mapping techniques. Here we used an immunopeptidomic approach to search for unconventional epitopes that drive T cell responses in mice infected with influenza virus A/Puerto Rico/8/1934. We identified a nine amino acid epitope, termed M-SL9, that drives a co-immunodominant, cytolytic CD8 T cell response that is unconventional in two major ways: first, it is presented by Qa-1, and second, it has a cryptic origin, mapping to an unannotated alternative reading frame product of the influenza matrix gene segment. Presentation and immunogenicity of M-SL9 are dependent on the second AUG codon of the positive sense matrix RNA segment, suggesting translation initiation by leaky ribosomal scanning. During influenza virus A/Puerto Rico/8/1934 infection, M-SL9-specific T cells exhibit a low level of egress from the lungs and strong differentiation into tissue-resident memory cells. Importantly, we show that M-SL9/Qa-1-specific T cells can be strongly induced by messenger RNA vaccination and that they can mediate antigen-specific cytolysis in vivo. Our results demonstrate that noncanonical translation products can account for an important fraction of the T cell repertoire and add to a growing body of evidence that MHC-E-restricted T cells could have substantial therapeutic value.

Hot-Trim: Thermal and Reliability Management for Commercial Multicore Processors Considering Workload Dependent Hot Spots

This work proposes a new dynamic thermal and reliability management framework via task mapping and migration to improve thermal performance and reliability of commercial multi-core processors considering workload-dependent thermal hot spot stress. The new method is motivated by the observation that different workloads activate different spatial power and thermal hot spots within each core of processors. Existing run-time thermal management, which is based on on-chip location-fixed thermal sensor information, can lead to suboptimal management solutions as the temperatures provided by those sensors may not be the true hot spots. The new method, called Hot-Trim, utilizes a machine learning-based approach to characterize the power density hot spots across each core, then a new task mapping/migration scheme is developed based on the hot spot stresses. Compared to existing works, the new approach is the first to optimize VLSI reliabilities by exploring workload-dependent power hot spots. The advantages of the proposed method over the Linux baseline task mapping and the temperature-based mapping method are demonstrated and validated on real commercial chips. Experiments on a real Intel Core i7 quad-core processor executing PARSEC-3.0 and SPLASH-2 benchmarks show that, compared to the existing Linux scheduler, core and hot spot temperature can be lowered by 1.15 1.31∘C. In addition, Hot-Trim can improve the chip’s EM, NBTI and HCI related reliability by 30.2%, 7.0% and 31.1% respectively compared to Linux baseline without any performance degradation. Furthermore, it improves EM and HCI related reliability by 29.6% and 19.6% respectively, and at the same time even further reduces the temperature by half a degree compared to the conventional temperature-based mapping technique.

Mine Pit Wall Geological Mapping Using UAV-Based RGB Imaging and Unsupervised Learning

In surface mining operations, geological pit wall mapping is important since it provides significant information on the surficial geological features throughout the pit wall faces, thereby improving geological certainty and operational planning. Conventional pit wall geological mapping techniques generally rely on close visual observations and laboratory testing results, which can be both time- and labour-intensive and can expose the technical staff to different safety hazards on the ground. In this work, a case study was conducted by investigating the use of drone-acquired RGB images for pit wall mapping. High spatial resolution RGB image data were collected using a commercially available unmanned aerial vehicle (UAV) at two gold mines in Nevada, USA. Cluster maps were produced using unsupervised learning algorithms, including the implementation of convolutional autoencoders, to explore the use of unlabelled image data for pit wall geological mapping purposes. While the results are promising for simple geological settings, they deviate from human-labelled ground truth maps in more complex geological conditions. This indicates the need to further optimize and explore the algorithms to increase robustness for more complex geological cases.

Free-breathing simultaneous water-fat separation and T1 mapping of the whole liver (SWALI) with isotropic resolution using 3D golden-angle radial trajectory.

Conventional liver T1 mapping techniques are typically performed under breath-holding conditions; they have limited slice coverage and often rely on multiple acquisitions. Furthermore, liver fat affects the accuracy of T1 quantification. Therefore, we aim to propose a free-breathing technique for simultaneous water-fat separation and T1 mapping of the whole liver (SWALI) in a single scan. The proposed SWALI sequence included an inversion recovery (IR) preparation pulse followed by a series of multiecho three-dimensional (3D) golden-angle radial acquisitions. For each echo time (TE), a series of images containing a mix of water and fat were reconstructed using a sliding window method. For each inversion time (TI), water and fat were separated, and then water and fat T1 estimation was conducted. The fat fraction (FF) was calculated based on the last TI image. The FF and water T1 quantification accuracy were compared with the gold standard sequences in the phantom. The in vivo feasibility was tested in 9 healthy volunteers, 2 patients with fatty liver, and 3 patients with hepatocellular carcinoma (HCC). The reproducibility was evaluated in the patients with fatty liver and in the healthy volunteers. The mean FF and the mean water T1 values obtained by the SWALI sequence showed good agreements with chemical shift-encoded magnetic resonance imaging (CSE-MRI; r=0.998; P<0.001) and fat-suppressed (FS) IR-spin echo (SE; r=0.997; P<0.001) in the phantom. For the patients with fatty liver and the healthy volunteers, the SWALI sequence showed no significant difference with CSE-MRI in FF quantification (P=0.53). In T1 quantification, comparable T1 values were obtained with the SWALI sequence and modified Look-Locker inversion recovery (MOLLI; P=0.10) in healthy volunteers, while the water T1 estimated by the SWALI sequence was significantly lower than the water-fat compound T1 estimated by MOLLI (P<0.001) in patients with fatty liver. In the reproducibility study, the intraclass correlation coefficients (ICCs) for the estimated FF and water T1 were 0.997 and 0.943, respectively. Water T1 of the patients with HCC calculated using the SWALI sequence showed a significant reduction after the contrast administration (P<0.001). Free-breathing water-fat separation and T1 mapping of the whole liver with 2.5 mm isotropic spatial resolution were achieved simultaneously using the SWALI sequence in a 5-min scan.

Quantitative MRI in cardiometabolic disease: From conventional cardiac and liver tissue mapping techniques to multi-parametric approaches.

Cardiometabolic disease refers to the spectrum of chronic conditions that include diabetes, hypertension, atheromatosis, non-alcoholic fatty liver disease, and their long-term impact on cardiovascular health. Histological studies have confirmed several modifications at the tissue level in cardiometabolic disease. Recently, quantitative MR methods have enabled non-invasive myocardial and liver tissue characterization. MR relaxation mapping techniques such as T1, T1ρ, T2 and T2* provide a pixel-by-pixel representation of the corresponding tissue specific relaxation times, which have been shown to correlate with fibrosis, altered tissue perfusion, oedema and iron levels. Proton density fat fraction mapping approaches allow measurement of lipid tissue in the organ of interest. Several studies have demonstrated their utility as early diagnostic biomarkers and their potential to bear prognostic implications. Conventionally, the quantification of these parameters by MRI relies on the acquisition of sequential scans, encoding and mapping only one parameter per scan. However, this methodology is time inefficient and suffers from the confounding effects of the relaxation parameters in each single map, limiting wider clinical and research applications. To address these limitations, several novel approaches have been proposed that encode multiple tissue parameters simultaneously, providing co-registered multiparametric information of the tissues of interest. This review aims to describe the multi-faceted myocardial and hepatic tissue alterations in cardiometabolic disease and to motivate the application of relaxometry and proton-density cardiac and liver tissue mapping techniques. Current approaches in myocardial and liver tissue characterization as well as latest technical developments in multiparametric quantitative MRI are included. Limitations and challenges of these novel approaches, and recommendations to facilitate clinical validation are also discussed.

Dynamic Cardiac Magnetic Resonance Fingerprinting During Vasoactive Breathing Maneuvers: First Results.

Cardiac magnetic resonance fingerprinting (cMRF) enables simultaneous mapping of myocardial T1 and T2 with very short acquisition times. Breathing maneuvers have been utilized as a vasoactive stress test to dynamically characterize myocardial tissue in vivo. We tested the feasibility of sequential, rapid cMRF acquisitions during breathing maneuvers to quantify myocardial T1 and T2 changes. We measured T1 and T2 values using conventional T1 and T2-mapping techniques (modified look locker inversion [MOLLI] and T2-prepared balanced-steady state free precession), and a 15 heartbeat (15-hb) and rapid 5-hb cMRF sequence in a phantom and in 9 healthy volunteers. The cMRF5-hb sequence was also used to dynamically assess T1 and T2 changes over the course of a vasoactive combined breathing maneuver. In healthy volunteers, the mean myocardial T1 of the different mapping methodologies were: MOLLI 1,224 ± 81 ms, cMRF15-hb 1,359 ± 97 ms, and cMRF5-hb 1,357 ± 76 ms. The mean myocardial T2 measured with the conventional mapping technique was 41.7 ± 6.7 ms, while for cMRF15-hb 29.6 ± 5.8 ms and cMRF5-hb 30.5 ± 5.8 ms. T2 was reduced with vasoconstriction (post-hyperventilation compared to a baseline resting state) (30.15 ± 1.53 ms vs. 27.99 ± 2.07 ms, p = 0.02), while T1 did not change with hyperventilation. During the vasodilatory breath-hold, no significant change of myocardial T1 and T2 was observed. cMRF5-hb enables simultaneous mapping of myocardial T1 and T2, and may be used to track dynamic changes of myocardial T1 and T2 during vasoactive combined breathing maneuvers.

Road Network Planning in Tropical Forests Using GIS

This study intended to develop a road network planning for timber harvesting in tropical forests in Peru using georeferenced and field data and Geographic Information System (GIS). The Digital Elevation Model (DEM) Alos Palsar 12.5 m was used. The DEM was processed to generate the hydrography and terrain slope maps. A weighted raster was created using overlapping weights of the slope raster and the hydrography map. We created a least cost path raster by using the weighted raster origin and destination points. We used a Triangular Irregular Network (TIN) to validate the Least Cost Path. In addition, histograms of the trajectory of each path with altitude and slope values ​​ were generated. We observed that the forest road planning using GIS provided better definition (economically and environmentally) of road networks in our forest site than those traditionally defined using conventional mapping techniques.

Ventricular Tachycardia Ablation Guided by Functional Substrate Mapping: Practices and Outcomes.

Catheter ablation of ventricular tachycardia has demonstrated its important role in the treatment of ventricular tachycardia in patients with structural cardiomyopathy. Conventional mapping techniques used to define the critical isthmus, such as activation mapping and entrainment, are limited by the non-inducibility of the clinical tachycardia or its poor hemodynamic tolerance. To overcome these limitations, a voltage mapping strategy based on bipolar electrograms peak to peak analysis was developed, but a low specificity (30%) for VT isthmus has been described with this approach. Functional mapping strategy relies on the analysis of the characteristics of the electrograms but also their propagation patterns and their response to extra-stimulus or alternative pacing wavefronts to define the targets for ablation. With this review, we aim to summarize the different functional mapping strategies described to date to identify ventricular arrhythmic substrate in patients with structural heart disease.

Orthogonal high-density mapping with ventricular tachycardia isthmus analysis vs. pure substrate ventricular tachycardia ablation: A case-control study.

BackgroundSubstrate-based ablation has become a successful technique for ventricular tachycardia (VT) ablation. High-density (HD) mapping catheters provide high-resolution electroanatomical maps and better discrimination of local abnormal electrograms. The HD Grid Mapping Catheter is an HD catheter with the ability to map orthogonal signals on top of conventional bipolar signals, which could provide better discrimination of the arrhythmic substrate. On the other hand, conventional mapping techniques, such as activation mapping, when possible, help to identify the isthmus of the tachycardia.AimThe purpose of this study was to compare clinical outcomes after using two different VT ablation strategies: one based on extensive mapping with the HD Grid Mapping Catheter, including VT isthmus analysis, and the other based on pure substrate ablation.MethodsForty consecutive patients undergoing VT ablation with extensive HD mapping method in the hospital clinic (November 2018–November 2019) were included. Clinical outcomes were compared with a historical cohort of 26 consecutive patients who underwent ablation using a scar dechanneling technique before 2018.ResultsThe density of mapping points was higher in the extensive mapping group (2370.24 ± 920.78 vs. 576.45 ± 294.46; p < 0.001). After 1 year of follow-up, VT recurred in 18.4% of patients in the extensive mapping group vs. 34.6% of patients in the historical control group (p = 0.14), with a significantly greater reduction of VT burden: VT episodes (81.7 ± 7.79 vs. 43.4 ± 19.9%, p < 0.05), antitachycardia pacing (99.45 ± 2.29 vs. 33.9 ± 102.5%, p < 0.001), and implantable cardioverter defibrillator (ICD) shocks (99 ± 4.5 vs. 64.7 ± 59.9%, p = 0.02).ConclusionThe use of a method based on extensive mapping with the HD Grid Mapping Catheter and VT isthmus analysis allows better discrimination of the arrhythmic substrate and could be associated with a greater decrease in VT burden.

The Preoperative Diagnostic Performance of Multi-Parametric Quantitative Assessment in Rectal Carcinoma: A Preliminary Study Using Synthetic Magnetic Resonance Imaging.

ObjectiveSynthetic MRI (SyMRI) can reconstruct different contrast-weighted images(T1, T2, PD) and has shorter scan time, easier post-processing and better reproducibility. Some studies have shown splendid correlation with conventional mapping techniques and no degradation in the quality of syMRI images compared with conventional MRI. It is crucial to select an individualized treatment plan based on the preoperative images of rectal carcinoma (RC). We tried to explore the feasibility of syMRI on T, N stage and extramural vascular invasion (EMVI) of rectal cancer.Materials and MethodsA total of 100 patients (37 females and 63 males) diagnosed with rectal carcinoma were enrolled. All the patients underwent preoperative pelvic MR examinations including conventional MR sequence and synthetic MRI. Two radiologists evaluated the MRI findings of each rectal carcinoma and EMVI score in consensus. The values for T1, T2 relaxation times and PD value were measured in tumor(ROI-1) and pararectal fat space(ROI-2) and analyzed independently. A receiver operating characteristic (ROC) analysis was performed. Correlations between the T1, T2 and PD values and EMVI score were also evaluated.ResultsCompared with the normal rectal wall, the values of T1 and T2 relaxation times of the tumor were significantly higher (P <0.001). There was no statistically significant difference in the PD value (P >0.05). As for ROI, the ROI of pararectal fat space(ROI-2) had better significance than rectal cancer lesion (ROI-1). T2 value of ROI-1 and T1 value of ROI-2 were higher in the pEMVI positive group than in the negative group (P=0.002 and 0.001) and T1 value of ROI-2 had better performance with an AUC of 0.787, (95% CI:0.693- 0.882). T1 value, T2 value and PD value from ROI-2 were effective for both T and N stage of rectal cancer. High-grade pathological stage had showed higher T1 value (PT stage=0.013,PN stage=0.035), lower T2 value (PT stage=0.025,PN stage=0.034) and lower PD value (PT stage=0.017). We also enrolled the characteristics with P < 0.05 in the combined model which had better diagnostic efficacy. A significant positive correlation was found between the T1 value of pararectal fat space(ROI-2) and EMVI score (r value = 0.519, P<0.001). The T2 value(r=0.213,P=0.049) and PD value(r=0.354,P=0.001) from ROI-1 was correlated with EMVI score. Correlation analysis did not show any significant associations between T2 value of tumor, T2, PD values of pararectal fat space and EMVI scores.ConclusionSynthetic MRI can provide multi-parameter quantitative image maps with a easier measurement and slightly shorter acquisition time compared with conventional MRI. The measurement of multi-parametric quantitative values contributes to diagnosing the tumor and evaluating T stage, N stage and EMVI. It has the potential to be used as a preoperative diagnostic and grading technique in rectal carcinoma.

Feasibility of a novel algorithm for automated reconstruction of the left atrial anatomy based on intracardiac echocardiography

Abstract Funding Acknowledgements Type of funding sources: None. Background Intracardiac echocardiography (ICE) is frequently used to guide electrophysiology procedures. The novel pre-commercial automated algorithm is a model-based algorithm, developed using machine learning methodology, which reconstructs a 3D anatomy of the left atrium (LA) and its structures based on a set of 2D ultrasound (US) frames, without the need to manually annotate US contours. Potential advantages are shortening of mapping time and better anatomy resolution when compared to conventional anatomical mapping techniques. Purpose Determine the early feasibility of the automated LA anatomy algorithm in routine clinical setting. Methods We included 16 patients (64±9 years, 88% males, body mass index 27±3, parasternal long axis LA diameter 40±3mm) undergoing LA mapping/catheter ablation (conscious sedation in 56% and general anaesthesia in the remaining cases). 2D US frames were acquired from three ICE-positions: superior vena cava/high right atrium (RA) junction, RA and right ventricular outflow tract. The automated LA anatomy map was validated in two steps: 1) identification of anatomical structures (pulmonary veins [PV] and left atrial appendage) by alignment of the ablation catheter to the automated map; and 2) assessment of PV anatomical accuracy by analysing the relationship with the automated lesion tags (3mm lesion radius, 3mm for 8sec stability criteria and 5-20g average contact force) and the PV antrum of the automated map in 9 patients with paroxysmal atrial fibrillation undergoing first time point-by-point radiofrequency PV isolation (PVI). In step 2, PV pairs were divided into 6 segments (total of 12 segments per patient) and were classified as accurate, insufficient ("floating" lesion tags), or excessive anatomy (invisible lesion tags). Results Mean 2D US frames per patient was 29±6 and acquisition time was 16±4 min. In the step 1 validation, all anatomical structures were correctly identified in the 16 patients by the automated algorithm. The step 2 validation showed anatomical accuracy in 76% of all 108 PV segments analysed. There was a range of 0-2 and 0-5 of the total 12 segments per patient with insufficient and excessive anatomy, respectively. In all cases with PV segment anatomical discrepancy, this was corrected with standard anatomy collection with the ablation catheter in ≤2min. In the whole patient group, catheter ablation was successfully performed on the automated map without complications. Conclusions The automated ICE-based 3D LA map algorithm performed overall well and correctly identified the LA anatomical structures in all patients. Anatomical PV antrum accuracy was high, and the majority of PV segments needed no manual correction before proceeding to PVI.

Tandem Probe Analysis Mode for Synchrotron XFM: Doubling Throughput Capacity.

Synchrotron-based X-ray fluorescence microscopy (XFM) analysis is a powerful technique that can be used to visualize elemental distributions across a broad range of sample types. Compared to conventional mapping techniques such as laser ablation inductively coupled plasma mass spectrometry or benchtop XFM, synchrotron-based XFM provides faster and more sensitive analyses. However, access to synchrotron XFM beamlines is highly competitive, and as a result, these beamlines are often oversubscribed. Therefore, XFM experiments that require many large samples to be scanned can penalize beamline throughput. Our study was largely driven by the need to scan large gels (170 cm2) using XFM without decreasing beamline throughput. We describe a novel approach for acquiring two sets of XFM data using two fluorescence detectors in tandem; essentially performing two separate experiments simultaneously. We measured the effects of tandem scanning on beam quality by analyzing a range of contrasting samples downstream while simultaneously scanning different gel materials upstream. The upstream gels were thin (<200 μm) diffusive gradients in thin-film (DGT) binding gels. DGTs are passive samplers that are deployed in water, soil, and sediment to measure the concentration and distribution of potentially bioavailable nutrients and contaminants. When deployed on soil, DGTs are typically small (2.5 cm2), so we developed large DGTs (170 cm2), which can be used to provide extensive maps to visualize the diffusion of fertilizers in soil. Of the DGT gel materials tested (bis-acrylamide, polyacrylamide, and polyurethane), polyurethane gels were most suitable for XFM analysis, having favorable handling, drying, and analytical properties. This gel type enabled quantitative (>99%) transmittance with minimal (<3%) flux variation during raster scanning, whereas the other gels had a substantial effect on the beam focus. For the first time, we have (1) used XFM for mapping analytes in large DGTs and (2) developed a tandem probe analysis mode for synchrotron-based XFM, effectively doubling throughput. The novel tandem probe analysis mode described here is of broad applicability across many XFM beamlines as it could be used for future experiments where any uniform, highly transmissive sample could be analyzed upstream in the “background” of downstream samples.

Critical Approaches to GIS and Spatial Mapping in Indonesia Forest Management and Conservation

The conventional Geographic Information Systems (GIS) and spatial mapping techniques fail to understand a spatially complex forest area. This is because forest landscapes cannot be easily mapped into a two-dimensional map, which is usually used in spatial planning. In addition, planning maps are the fundamental factors of land grabbing issues. To solve this problem, counter-mapping arises at the local level as a tool to overcome the problem of land grabbing in forest areas in Indonesia. Counter mapping is defined here as part of a broader term under participatory mapping or citizen mapping. However, counter-mapping also faces critiques in terms of different epistemological and socio-economic-political conditions at the local level. This article elaborates the use of GIS and spatial mapping methods within a 'critical' social science approach based on literature review and field experiences. This article also aims to analyze counter-mapping as a ‘tool’ to solve the forest land-use problem, which can contribute to the choice of policy instruments in forest management and conservation in Indonesia.

Exploratory Study of the Clinical Value of Near-Infrared Sentinel Lymph Node Mapping With Indocyanine Green in Vulvar Cancer Patients.

BackgroundThis study aimed to evaluate the clinical value of indocyanine green sentinel lymph node (SLN) mapping in patients with vulvar cancer. The conventional procedure of SLN mapping in vulvar cancer includes peritumoral injection of technetium-99m nanocolloid before surgery and intraoperative injection of a blue dye. However, these techniques harbor some limitations. Near-infrared fluorescence imaging with indocyanine green has gained popularity in SLN mapping in different types of cancer.MethodsWe analyzed retrospectively vulvar cancer patients at our institution between 2013 and 2020 undergoing indocyanine green SLN mapping by applying video telescope operating microscope system technology.Results64 groins of 34 patients were analyzed. In 53 groins we used technetium-99m nanocolloid, in four patent blue, and in five both techniques, additionally to indocyanine green for SLN detection. In total, 120 SLNs were identified and removed. The SLN detection rate of indocyanine green was comparable to technetium-99m nanocolloid (p=.143) and higher than patent blue (p=.003). The best results were achieved using a combination of ICG and technetium-99m nanocolloid (detection rate of 96.9%). SLN detection rates of indocyanine green were significantly higher in patients with positive lymph nodes (p=.035) and lymphatic space invasion (p=.004) compared to technetium-99m nanocolloid.ConclusionIndocyanine green SLN mapping in vulvar cancer is feasible and safe, with reasonable detection rates. Due to its easy application and few side effects, it offers a sound alternative to the conventional SLN mapping techniques in vulvar cancer. In patients with lymph node metastasis, indocyanine green even outperformed technetium-99m nanocolloid in terms of detection rate.

Multi-layer value stream assessment of the reverse logistics network for inert construction waste management

Reverse logistics (RL) concepts have brought sustainable solutions to the problems pertinent to inert construction waste (ICW) management. However, the involvement of different processes and facilities across the RL value chain makes it difficult to visualize and manage the whole process conveniently. Consequently, issues such as inadequate assessment of environmental hazards, unclear cost accrual patterns, misleading information to stakeholders, and other process-related deficiencies arise, thereby questioning the overall sustainability and alike circularity concepts. Despite the prominent role of lean management (LM) concepts in process improvements across various product-oriented sectors, its integration within RL management to solve ICW problems is almost non-existent. This paper presents a unique lean thinking-based multi-layer value stream assessment (MVSA) approach deriving from a conventional value stream mapping (VSM) technique to assess the overall RL network of ICW management. RL network design entails both facility-based and non-facility-based processes, with four different value streams, i.e., time, cost, environmental quality, and process efficiency aspects. A case study of Hong Kong demonstrates the developed MVSA approach. The case study features an assessment of the RL network's current and future states, considering multiple scenarios. Furthermore, a detailed sensitivity analysis is conducted to provide valuable insights and discussions. In the end, an agenda for continuous improvement related to the proposed MVSA approach is expounded. The research findings verify that the proposed MVSA approach can significantly contribute to the overall process improvement, better visualization, and RL network assessment, leading to effective waste management systems.