Single Cluster Research Articles

Hyperbolic metamaterial induced optical pulling of distinct Rayleigh particles: Single particle or cluster of heterogeneous objects

In the field of optical manipulation, there has been a phenomenon where an illuminated object is propelled towards the direction of the light beam due to the momentum carried by the quanta of light known as photon ℏκ. Nonetheless, there is currently no work in literature that describes a method to draw all types of objects, including single and clustered nanoparticles, using a single optical setup. In this study, we propose a generic optical setup that utilizes the anomalous reflections of light generated by hyperbolic metamaterial to enable an Optical Tractor Beam (OTB) effect over a heterogeneous cluster of particles and single particle arrangements. We conducted numerous full-wave simulations to observe the optical force pattern under various conditions, such as varying wavelengths, interparticle distances, and particle distributions, as well as investigations in a variety of surrounding media, including air, half-submerged in water, and fully submerged in water. Our optical setup has been subjected to a near-field OTB effect from the clustered Rayleigh-sized particles, as well as single particles for all varied environments. This article demonstrates the mechanisms and outcomes that offer a fresh new avenue toward manipulating nanoscale homogeneous and heterogeneous objects, including dielectric, plasmonic, and chiral nanoparticles.

The role of magnetoencephalography in preoperative localization and postoperative outcome prediction in patients with posterior cortical epilepsy.

We aimed to explore the value of magnetoencephalography in the presurgical evaluation of patients with posterior cortex epilepsy. A total of 39 patients with posterior cortex epilepsy (PCE) and intact magnetoencephalography (MEG) images were reviewed from August 2019 to July 2022. MEG dipole clusters were classified into single clusters, multiple clusters, and scatter dipoles based on tightness criteria. The association of the surgical outcome with MEG dipole classifications was evaluated using Fisher's exact tests. Among the 39 cases, there were 24 cases of single clusters (61.5%), nine cases of multiple clusters (23.1%), and six cases of scattered dipoles (15.4%). Patients with single dipole clusters were more likely to become seizure-free. Among single dipole cluster cases (n = 24), complete MEG dipole resection yielded a more favorable surgical outcome than incomplete resection (83.3% vs. 16.7%, p = 0.007). Patients with concordant MRI and MEG findings achieved a significantly more favorable surgical outcome than discordant patients (66.7% vs. 33.3%, p = 0.044), especially in single dipole cluster patients (87.5% vs. 25.0%, p = 0.005). MEG can provide additional valuable information regarding surgical candidate selection, epileptogenic zone localization, electrode implantation schedule, and final surgical planning in patients with posterior cortex epilepsy.

Optimization of Distributed RSA Encryption and Decription Processing Using Process Scheduling Method In Single Board Computer Cluster Architecture (SBC)

Data security is still a major issue regarding the need for data confidentiality. The encryption process using the RSA algorithm is still the most popular method used in securing data because the complexity of the mathematical equations used in this algorithm makes it difficult to hack. However, the complexity of the RSA algorithm is still a major problem that hinders its application in a more complex application. Optimization is needed in the processing of this RSA algorithm, one of which is by running it on a distributed system. In this paper, we propose an approach with a FIFO process scheduling algorithm that runs on a single board computer cluster. The test results show that the allocation of resources in a system that uses a FIFO process scheduling algorithm is more efficient and shows a decrease in the overall processing time of RSA encryption.

Optimizing Data Acquisition to Enhance Machine Learning Performance

In this paper, we study how to acquire labeled data points from a large data pool to enrich a training set for enhancing supervised machine learning (ML) performance. The state-of-the-art solution is the clustering-based training set selection (CTS) algorithm, which initially clusters the data points in a data pool and subsequently selects new data points from clusters. The efficiency of CTS is constrained by its frequent retraining of the target ML model, and the effectiveness is limited by the selection criteria, which represent the state of data points within each cluster and impose a restriction of selecting only one cluster in each iteration. To overcome these limitations, we propose a new algorithm, called CTS with incremental estimation of adaptive score (IAS). IAS employs online learning, enabling incremental model updates by using new data, and eliminating the need to fully retrain the target model, and hence improves the efficiency. To enhance the effectiveness of IAS, we introduce adaptive score estimation, which serves as novel selection criteria to identify clusters and select new data points by balancing trade-offs between exploitation and exploration during data acquisition. To further enhance the effectiveness of IAS, we introduce a new adaptive mini-batch selection method that, in each iteration, selects data points from multiple clusters rather than a single cluster, hence eliminating the potential bias due to using only one cluster. By integrating this method into the IAS algorithm, we propose a novel algorithm termed IAS with adaptive mini-batch selection (IAS-AMS). Experimental results highlight the superior effectiveness of IAS-AMS, with IAS also outperforming other competing algorithms. In terms of efficiency, IAS takes the lead, while the efficiency of IAS-AMS is on par with that of the existing CTS algorithm.

Tracing the Origins of Mass Segregation in M35: Evidence for Primordially Segregated Binaries

M35 is a young open cluster and home to an extensive binary population. Using Gaia Data Release 3, Pan-STARRS, and Two Micron All Sky Survey photometry with the Bayesian statistical software, BASE-9, we derive precise cluster parameters, identify single and binary cluster members, and extract their masses. We identify 571 binaries down to Gaia G = 20.3 and a lower limit on the binary frequency of f b = 0.41 ± 0.02. We extend the binary demographics by many magnitudes faint-ward of previous (radial-velocity) studies of this cluster and further away from the cluster center (1.°78, roughly 10 core radii). We find the binary stars to be more centrally concentrated than the single stars in the cluster. Furthermore, we find strong evidence for mass segregation within the binary population itself, with progressively more-massive binary samples becoming more and more centrally concentrated. For the single stars, we find weaker evidence for mass segregation; only the most massive single stars (>2.5M ⊙) appear more centrally concentrated. Given the cluster age of ∼200 Myr, and our derived half-mass relaxation time for the cluster of 230 ± 84 Myr, we estimate ∼47% of the binary stars and ∼12% of single stars in the cluster have had time to become dynamically mass segregated. Importantly, when we investigate only stars with mass segregation timescales greater than the cluster age, we still find the binaries to be more centrally concentrated than the singles, suggesting the binaries may have formed with a primordially different spatial distribution from that of the single stars.

Representations of an Ebola ‘outbreak’ through Story Technologies

BackgroundAttempts to understand biosocial phenomena using scientific methods are often presented as value-neutral and objective; however, when used to reduce the complexity of open systems such as epidemics, these forms...

Exploratory analyses of homologous recombination repair (HRR) gene subgroups and potential associations with secondary efficacy endpoints in the HRR-deficient population from TALAPRO-2.

178 Background: TALAPRO-2 demonstrated statistically significant improvement in radiographic PFS with 1L talazoparib (TALA) + enzalutamide (ENZA) in patients (pts) with metastatic castration-resistant prostate cancer (mCRPC) with and without HRR gene alterations (HRRm). Tumors were prospectively determined to harbor HRRm. Pts were randomized 1:1 to TALA 0.5 mg (N=200) or placebo (PBO; N=199) + ENZA 160 mg QD. Exploratory biomarker analyses assessed HRR gene subgroups and potential associations with secondary efficacy endpoints in pts with HRRm tumors. Methods: Prospective testing used a 12-gene HRR panel (HRR12) of FoundationOne CDx/FoundationOne Liquid CDx.For single gene groups, only pts bearing alteration(s) in that gene and no other HRR12 genes were analyzed. Gene cluster alteration dominance hierarchy: any BRCA1/2 alteration ( BRCA cluster); any PALB2 ( PALB2 cluster); any CDK12 ( CDK12 cluster); any ATM ( ATM cluster); all other HRR12 genes (each pt counted once). Endpoints: ORR, time to progression or death on first subsequent antineoplastic therapy (PFS2), PSA response ≥50%, time to PSA progression (TTPP), and time to initiation of cytotoxic chemotherapy (TTCC). Results: TALA + ENZA demonstrated differential benefit for BRCA2 single gene group across endpoints: ORR, 78.9% vs 33.3% (odds ratio [OR], 0.13 [95% CI, 0.03–0.63]); PFS2, median not reached (NR) vs 26.1 mo (HR, 0.44 [0.20–0.97]); PSA response >50%, 87.0% vs 58.3%; TTPP, NR vs 9.2 mo (HR, 0.20 [0.10–0.41]); TTCC, NR vs 17.0 mo (HR, 0.27 [0.13–0.57]). Similar broad benefit was seen for BRCA cluster and BRCA1 single gene groups and to a lesser extent PALB2 single gene and cluster groups (allowing for small n in the latter 3 groupings). Broad differential benefit was evident for CDK12 single gene group : ORR 70.0% vs 28.6% (OR 0.17 [0.01–2.03]); PFS2, 36.4 vs 18.8 mo (HR, 0.29 [0.11–0.75]); PSA response ≥50%, 85.7% vs 53.3%; TTPP, 13.8 vs 11.1 mo (HR 0.61 [0.29–1.26]); the exception was TTCC, NR vs NR (HR 1.32 [0.43–4.06]). Similar benefit was seen for CDK12 cluster. For ATM single gene group, differential numerical benefit was seen for ORR, 81.8% vs 20.0% (OR 0.06 [0.00–1.17]); TTPP, 26.8 vs 15.9 mo (HR, 0.61 [0.25–1.47]); TTCC, NR vs NR (HR 0.60 [0.18–1.96]); no differential benefit was seen in other endpoints (similar for ATM cluster). The CHEK2 single gene group showed numerically differential benefit for PSA endpoints and TTCC. The other HRR12 gene cluster typically showed comparable efficacy between arms with potential exception of TTPP, 28.6 vs 14.0 mo (HR 0.65 [0.33–1.31]), and TTCC, NR vs NR (HR 0.65 [0.26–1.62]). Conclusions: Broad differential efficacy benefit was evident for TALA + ENZA vs PBO + ENZA across multiple molecular subgroups and was most pronounced for the BRCA1- PALB2- BRCA2 axis and CDK12. Additional analyses are warranted. Clinical trial information: NCT03395197 .

Galaxy cluster mass bias from projected mass maps

The determination of the mass of galaxy clusters from observations is subject to systematic uncertainties. Beyond the errors due to instrumental and observational systematic effects, in this work we investigate the bias introduced by modelling assumptions. In particular, we consider the reconstruction of the mass of galaxy clusters from convergence maps employing spherical mass density models. We made use of THE THREE HUNDRED simulations, selecting clusters in the same redshift and mass range as the NIKA2 Sunyaev-Zel’dovich Large Programme sample: 3 ≤ M500/1014 M⊙ ≤ 10 and 0.5 ≤ z ≤ 0.9. We studied different modelling and intrinsic uncertainties that should be accounted for when using the single cluster mass estimates for scaling relations. We confirm that the orientation of clusters and the radial ranges considered for the fit have an important impact on the mass bias. The effect of the projection adds uncertainties to the order of 10–16% to the mass estimates. We also find that the scatter from cluster to cluster in the mass bias when using spherical mass models is less than 9% of the true mass of the clusters.

Building Fe atom–cluster composite sites using a site occupation strategy to boost electrochemical oxygen reduction

AbstractThe high‐temperature pyrolysis process for preparing M–N–C single‐atom catalyst usually results in high heterogeneity in product structure concurrently contains multiscale metal phases from single atoms (SAs), atomic clusters to nanoparticles. Therefore, understanding the interactions among these components, especially the synergistic effects between single atomic sites and cluster sites, is crucial for improving the oxygen reduction reaction (ORR) activity of M–N–C catalysts. Accordingly, herein, we constructed a model catalyst composed of both atomically dispersed FeN4 SA sites and adjacent Fe clusters through a site occupation strategy. We found that the Fe clusters can optimize the adsorption strength of oxygen reduction intermediates on FeN4 SA sites by introducing electron‐withdrawing –OH ligands and decreasing the d‐band center of the Fe center. The as‐developed catalyst exhibits encouraging ORR activity with half‐wave potentials (E1/2) of 0.831 and 0.905 V in acidic and alkaline media, respectively. Moreover, the catalyst also represents excellent durability exceeding that of Fe–N–C SA catalyst. The practical application of Fe(Cd)–CNx catalyst is further validated by its superior activity and stability in a metal–air battery device. Our work exhibits the great potential of synergistic effects between multiphase metal species for improvements of single‐atom site catalysts.

3D Interior Design System Model Based on Computer Virtual Reality Technology

Globally, data volume is increases exponentially with increase in the proliferation with Cloud Computing. MapReduce is emerged as the prominent solution for the unprecedented growth in the efficient manner as it process both structured and unstructured data. The dynamic landscape of Virtual Reality has seen a significant shift towards technology-driven approaches, with data analytics and personalized learning becoming increasingly important. This paper introduces an innovative framework that leverages the power of Hadoop and MapReduce to elevate 3D virtual reality experiences within diverse VR Cloud settings. This paper presents the development of an efficient Cache-Based MapReduce framework (CMF) where Cache algorithms are effectively used to process queries on large-scale cloud-based data. The Hadoop System processes data in single-node Hadoop Clusters (Pseudo-distributed) as well as heterogeneous Hadoop Clusters (fully distributed nodes) within Amazon Web Services (AWS). The Hadoop System process the data in the single node Hadoop Cluster (Pseudo-distributed) heterogeneous Hadoop Cluster (fully distributed node) in the Amazon Web Services (AWS). The experimental analysis is evaluated for the SmallGutenberg and LargeGutenberg database. The developed model achieves the average reduction in job of 48.01% with reduction in execution time of 51.99%. The CMF of 7-node, 9-node, 15-node and 20-node reduction in execution time is measured as 49.91%, 51.38%, 54.71% and 45.29% respectively.

Precision MARS Mass Reconstruction of A2744: Synergizing the Largest Strong-lensing and Densest Weak-lensing Data Sets from JWST

We present a new high-resolution free-form mass model of A2744 that combines both weak-lensing (WL) and strong-lensing (SL) data sets from JWST. The SL data set comprises 286 multiple images, presenting the most extensive SL constraint to date for a single cluster. The WL data set, employing photo-z selection, yields a source density of ∼350arcmin−2 , marking the densest WL constraint ever. The combined mass reconstruction enables the highest-resolution mass map of A2744 within the ∼1.8 Mpc × 1.8 Mpc reconstruction region to date, revealing an isosceles triangular structure with two legs of ∼1 Mpc and a base of ∼0.6 Mpc. Although our algorithm, which is called MAximum-entropy ReconStruction (MARS), is entirely blind to the cluster galaxy distribution, the resulting mass reconstruction traces the brightest cluster galaxies remarkably well. The five strongest mass peaks coincide with the five most luminous cluster galaxies within ≲2″. We do not detect any unusual mass peaks that are not traced by the cluster galaxies, unlike the findings in previous studies. Our mass model shows the smallest scatter of SL multiple images in both source (∼0.″05) and image (∼0.″1) planes, which is lower than in previous studies by a factor of ∼4. Although MARS represents the mass field with an extremely large number of free parameters (∼300,000), it converges to a solution within a few hours because we use a deep-learning technique. We make our mass and magnification maps publicly available.

Impaired Well-Being and Insomnia as Residuals of Resolved Medical Conditions: Survey in the Italian Population.

Well-being encompasses physical, mental, social, and cultural aspects. Sleep quality and pathologies are among the objective conditions jeopardising it. Chronic insomnia, inflammatory-based diseases, and mood disorders often occur in a single cluster, and inflammation can negatively impact sleep, potentially harming well-being. Some evidence from specific clinical populations suggests that also some resolved past diseases could still have an impact on present sleep quality and well-being. The aim of the present study is to investigate, in the general population, whether and to what degree well-being and insomnia are associated with resolved pathologies. A cross-sectional survey (IPSAD®) was carried out using anonymous postal questionnaires that investigated past and present general health, well-being, and insomnia. A total of 10,467 subjects answered the questionnaire. Several classes of both current and resolved pathologies resulted in increased odds ratios for current insomnia (odds ratios = 1.90; 1.43, respectively) and impaired well-being (odds ratios = 1.75; 1.33, respectively), proportional to the number of the displayed pathologies. Notably, both current and resolved past psychiatric disorders were strongly associated with both current impaired well-being (odds ratios = 5.38; 1.70, respectively) and insomnia (odds ratios = 4.99; 2.15, respectively). To explain these associations, we suggest that systemic inflammation conveyed by several medical conditions disrupts homeostatic processes, with final effects on sleep quality and behaviour.

Review of Theoretical and Computational Studies of Bulk and Single Atom Catalysts for H2 S Catalytic Conversion.

Catalytic conversion of hydrogen sulfide (H2 S) plays a vital role in environmental protection and safety production. In this review, recent theoretical advances for catalytic conversion of H2 S are systemically summarized. Firstly, different mechanisms of catalytic conversion of H2 S are elucidated. Secondly, theoretical studies of catalytic conversion of H2 S on surfaces of metals, metal compounds, and single-atom catalysts (SACs) are systematically reviewed. In the meantime, various strategies which have been adopted to improve the catalytic performance of catalysts in the catalytic conversion of H2 S are also reviewed, mainly including facet morphology control, doped heteroatoms, metal deposition, and defective engineering. Finally, new directions of catalytic conversion of H2 S are proposed and potential strategies to further promote conversion of H2 S are also suggested: including SACs, double atom catalysts (DACs), single cluster catalysts (SCCs), frustrated Lewis pairs (FLPs), etc. The present comprehensive review can provide an insight for the future development of new catalysts for the catalytic conversion of H2 S.

Micro-morphological study of three members of genus <i>Plectranthus</i> L. (Lamiaceae) in Nigeria

Micro-morphological studies of three members of the Genus Plectranthus L. (Lamiaceae) in Nigeria were conducted to investigate the anatomical characteristics of taxonomic importance. The following plant samples were collected from various locations in Southwestern Nigeria, namely Plectranthus aegyptiacus (Forssk.) C. Chr., Plectranthus esculentus N.E.Br. and Plectranthus monostachyus (P. Beauv.) B. J. Pollard. The anatomical study of the lamina epidermis, venation pattern and petiole were performed. The Single Linkage Cluster Analysis (SLCA) and one-way Analysis of Variance (ANOVA) with the Duncan Multiple Range Test (DMRT) were used to analyze the parameters, and photomicrographs were employed to document the observations. Foliar epidermal characteristics such as epidermal cell shape, anticlinal wall pattern, stomata types, trichome types and ergastic substances are essential in delimiting the species. The identification of numerous starch grains delimits P. monostachyus from the other species, a straight anticlinal wall pattern delimits P. esculentus, and the presence of abundant crystal sands delimits P. aegyptiacus. Quantitatively, stomata index (S.I.) and trichome length for both adaxial and abaxial surfaces were significantly different (P≤0.05) among the species. The venation pattern of the studied plant samples also revealed specific characteristics. Irregular vein spacing, eucamptodromous secondary vein category and polygonal areole shape delimit P. esculentus from the other species.

Study on multi-cluster fracturing simulation of deep reservoir based on cohesive element modeling

With the depletion of conventional reservoir development, reservoir fracturing under deep high geo-stress and high geo-stress difference conditions is receiving increasing attention. Deep reservoirs typically require multi-cluster fracturing to achieve efficient reservoir transformation and development. In this paper, considering the relevant geological parameters of a certain reservoir in the southwest, three-dimensional multi-cluster reservoir fracturing models were established based on cohesive element modeling. Then, the propagation law of artificial fractures in reservoirs under the influence of the different number of fracturing clusters, injection displacement, and Young’s modulus in different regions of the 60 m fracturing well section is analyzed, and the quantitative law of parameters such as fracture length, maximum fracture width, injection point fracture width, fracture area, and tensile failure ratio during multi-cluster fracturing construction, as well as the propagation law of fracture morphology are revealed. The simulation results show that using multi-cluster fracturing can significantly improve the effectiveness of reservoir reconstruction, but as the number of fracturing clusters increases, it is also easy to form some small opening artificial fractures. These small opening artificial fractures may not be conducive to the transportation of proppants and fluids. During single cluster fracturing, the interface stiffness and rock Young’s modulus have a significant impact on the propagation of artificial fractures in the reservoir. As the number of fracturing clusters increases, the competition between artificial main fractures expands significantly, which may reduce the impact of interface stiffness and rock Young’s modulus. The fluid injection rate has a significant impact on reservoir fracturing, and in the same area, using high displacement injection can significantly increase the volume of reservoir reconstruction. This study can provide some reference for multi-cluster fracturing construction in deep reservoirs.

Using diagnosis-related groups in Chile: lessons and challengesLições e desafios do uso de grupos de diagnósticos relacionados no Chile

Analyze the implementation of diagnosis-related groups (DRGs) in Chile with a view to optimizing the distribution of public resources. A chronological narrative analysis of the main milestones was complemented by simulated application of DRGs through emulated competition and cluster analysis for evaluative purposes. In 2001, DRGs were introduced in Chile in an academic context. The National Health Fund (FONASA) began using DRGs in the private sector. A public sector pilot was launched in 2015. After nearly two decades of progress, in 2020 FONASA established the DRG program as a payment mechanism for public hospitals. However, the COVID-19 pandemic slowed its development. In 2022, implementation was resumed. After evaluating the program, it was evident that the hospital clusters that had been predefined for differentiated payment did not successfully differentiate homogeneous groups. In 2023, the program was reformed, financing was increased, a single cluster and base rate were defined, and greater hospital complexity was recognized, compared to previous years. Three hospitals were added to the program, for a total of 68. This experience shows that it is possible to sustain a public health financing policy that achieves greater efficiency and equity in the health system, based on the existence of robust institutions that continuously develop and improve.

Cave Levels in the Totes Gebirge (Eastern Alps)

Abstract The Totes Gebirge is not only the largest karst massif in the Northern Calcareous Alps, it also contains the most cave passages. In this area we are investigating the vertical distribution of phreatic cave passages to determine cave levels. These are vertical zones with clusters of cave passages that can be correlated with former valley floors. Since only phreatic cave passages (i.e. caves that were permanently or episodically filled with water during their formation) are to be analysed, a genetic classification is made on the basis of field observations, cave maps, 3D surveys and descriptions. As of Sept. 2023, the Totes Gebirge range, including the adjacent Warscheneck and the Hohe Schrott, contains 3172 known caves with a total length of 821 km, including the two longest cave systems in Austria, the Schönberg- (156 km) and the Schwarzmooskogel-Höhlensystem (137 km). As small caves do not contribute significantly to these statistics, only caves ≥50 m were included. The remaining 754 caves have a total length of 790 km. Only 46 % of these caves are at least partially of phreatic origin, but they contain 92 % of the total passage length. After subtracting the caves from which no data were available and cave sections that are not phreatic in origin (i.e. vadose or those created by weathering and erosion), 641 km of cave sections remained, which were analysed for their vertical distribution in 25 m increments. The histogram of cave length distribution vs. elevation for the Totes Gebirge range shows only a single significant cluster of phreatic cave sections between 1300 and 1850 m above see level (a.s.l.), with a clear maximum at 1500 m. The massif was divided into four sub-regions and all of them show this main interval, which is why it was interpreted as a cave level. It correlates well with the Giant Cave Level known from all other karst massifs in the Northern Calcareous Alps analysed so far. However, it is peculiar that in the other massifs at least three cave levels are present. Other reasons, such as the lack of known caves and the large size of the massif, which could lead to overlapping of cave levels, are unlikely. Therefore, it seems possible that the palaeo surface drainage pattern around the Totes Gebirge or its uplift history was different from the other karst massifs in the Northern Calcareous Alps and that low-lying cave levels (Spring and Berger Cave Level) or an elevated one (Ruin Cave Level) did not develop. For each of the 21 largest cave systems (≥5 km in length), the peak of the vertical distribution of the phreatic passages was determined. Vectors were calculated in order to test whether palaeo-flow directions could be inferred from their distribution. These phreatic maxima indicate a general dip from ESE to WNW, which could be interpreted either as a palaeo-drainage direction or as a tectonic tilting of the whole massif after the formation of the passages.

COVID-19 outbreak at a residential apartment building in Northern Ontario, Canada.

In February 2021, a cluster of Beta variant (B.1.351) coronavirus disease 2019 (COVID-19) cases were identified in an apartment building located in Northern Ontario, Canada. Most cases had no known contact with each other. Objectives of this multi-component outbreak investigation were to better understand the social and environmental factors that facilitated the transmission of COVID-19 through this multi-unit residential building (MURB). A case-control study examined building-specific exposures and resident behaviours that may have increased the odds of being a case. A professional engineer assessed the building's heating, ventilation, and air-conditioning (HVAC) systems. Whole-genome sequencing and an in-depth genomic analysis were performed. Forty-five outbreak-confirmed cases were identified. From the case-control study, being on the upper floors (OR: 10.4; 95% CI: 1.63-66.9) and within three adjacent vertical lines (OR: 28.3; 3.57-225) were both significantly associated with being a case of COVID-19, after adjusting for age. There were no significant differences in reported behaviours, use of shared spaces, or precautions taken between cases and controls. An assessment of the building's ventilation found uncontrolled air leakage between apartment units. A single genomic cluster was identified, where most sequences were identical to one another. Findings from the multiple components of this investigation are suggestive of aerosol transmission between units.

Genetic variations among the isolates of Bipolaris Maydis based on phenotypic and molecular markers

Abstract Maydis leaf blight, caused by Bipolaris maydis, is an important disease of maize crop in Khyber Pakhtunkhwa (KP) Pakistan. Fifteen isolates of the pathogen, collected across KP, were studied for variability based on phenotypic and molecular markers. Significant variability among the isolates was observed when assessed using phenotypic traits such as radial growth, spore concentration, fungicide sensitivity and virulence. The isolates were classified into six culture groups based on colour, texture and margins of the colony. Conidial morphology was also variable. These were either straight or slightly curved and light to dark brown in colour. Fungicide test showed significant variation in the degree of sensitivity against Carbendazim. Isolate Bm8 exhibited maximum radial growth on carbendazim spiked plates. Conversely, isolate Bm15 showed the lowest radial growth. Variations in virulence pattern of the isolates were evident when a susceptible maize variety Azam was inoculated with spores of B. maydis. Genetic variability amongst the isolates was also estimated by RAPD as well as sequencing of ITS region. The RAPD dendrogram grouped all the isolates into two major clusters. Average genetic distance ranged from 0.6% to 100%, indicating a diverse genetic gap among the isolates. Maximum genetic distance was found between isolates Bm9 and Bm10 as well as Bm2 and Bm8. Conversely, isolates Bm13 and Bm15 were at minimum genetic distance. Phylogenetic dendrogram based on sequencing of ITS region grouped all the isolates into a single major cluster. The clusters in both the dendrogram neither correlate to the geographical distribution nor to the morphological characteristics.

Similarity-driven motion-resolved reconstruction for ferumoxytol-enhanced whole-heart MRI in congenital heart disease.

A similarity-driven multi-dimensional binning algorithm (SIMBA) reconstruction of free-running cardiac magnetic resonance imaging data was previously proposed. While very efficient and fast, the original SIMBA focused only on the reconstruction of a single motion-consistent cluster, discarding the remaining data acquired. However, the redundant data clustered by similarity may be exploited to further improve image quality. In this work, we propose a novel compressed sensing (CS) reconstruction that performs an effective regularization over the clustering dimension, thanks to the integration of inter-cluster motion compensation (XD-MC-SIMBA). This reconstruction was applied to free-running ferumoxytol-enhanced datasets from 24 patients with congenital heart disease, and compared to the original SIMBA, the same XD-MC-SIMBA reconstruction but without motion compensation (XD-SIMBA), and a 5D motion-resolved CS reconstruction using the free-running framework (FRF). The resulting images were compared in terms of lung-liver and blood-myocardium sharpness, blood-myocardium contrast ratio, and visible length and sharpness of the coronary arteries. Moreover, an automated image quality score (IQS) was assigned using a pretrained deep neural network. The lung-liver sharpness and blood-myocardium sharpness were significantly higher in XD-MC-SIMBA and FRF. Consistent with these findings, the IQS analysis revealed that image quality for XD-MC-SIMBA was improved in 18 of 24 cases, compared to SIMBA. We successfully tested the hypothesis that multiple motion-consistent SIMBA clusters can be exploited to improve the quality of ferumoxytol-enhanced cardiac MRI when inter-cluster motion-compensation is integrated as part of a CS reconstruction.