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Scientific Reports May 2024In this paper, an absorptive coding metasurface (ACM) is proposed for ultra-wideband radar cross section (RCS) reduction, the design process is presented in detail, in...
In this paper, an absorptive coding metasurface (ACM) is proposed for ultra-wideband radar cross section (RCS) reduction, the design process is presented in detail, in which a lossy polarization conversion metasurface (PCM) is proposed at first. The lossy PCM is an anisotropic resistive structure with both polarization conversion and absorption performances, so that its co-polarization reflection coefficients under u- and v-polarized incidences can be kept at less than - 10 dB in magnitude in the frequency range from 7.5 to 45.2 GHz. Though the magnitude of the cross-polarization reflection coefficient cannot be very small only due to the absorption, its phase will be changed by nearly 180° when the unit-cell structure of the lossy PCM is rotated by 90°. Thus, the lossy PCM can be used as one of the two types of lossy coding elements for an ACM when its unit-cell structure is rotated by 90° or not. Based on the lossy PCM, an ACM is proposed. The simulation and experimental results show that the ACM has an excellent RCS reduction performance under arbitrary polarized incidence, it can achieve effective RCS reduction under normal incidence in the ultra-wide frequency band from 7.4 to 45.5 GHz with a ratio bandwidth (f/f) of 6.15:1; moreover, an ultra-wideband RCS reduction can still be achieved when the incident angle is increased to 45°, which indicates that the ACM has good stealth performance under the detection of various radars working in X, Ku, K and Ka bands, it is very practical.
PubMed: 38811829
DOI: 10.1038/s41598-024-63260-z -
Proceedings of the National Academy of... Dec 2023Tools are objects that are manipulated by agents with the intention to cause an effect in the world. We show that the cognitive capacity to understand tools is present...
Tools are objects that are manipulated by agents with the intention to cause an effect in the world. We show that the cognitive capacity to understand tools is present in young infants, even if these tools produce arbitrary, causally opaque effects. In experiments 1-2, we used pupillometry to show that 8-mo-old infants infer an invisible causal contact to account for the-otherwise unexplained-motion of a ball. In experiments 3, we probed 8-mo-old infants' account of a state change event (flickering of a cube) that lies outside of the explanatory power of intuitive physics. Infants repeatedly watched an intentional agent launch a ball behind an occluder. After a short delay, a cube, positioned at the other end of the occluder began flickering. Rare unoccluded events served to probe infants' representation of what happened behind the occluder. Infants exhibited larger pupil dilation, signaling more surprise, when the ball stopped before touching the cube, than when it contacted the cube, suggesting that infants inferred that the cause of the state change was contact between the ball and the cube. This effect was canceled in experiment 4, when an inanimate sphere replaced the intentional agent. Altogether, results suggest that, in the infants' eyes, a ball (an inanimate object) has the power to cause an arbitrary state change, but only if it inherits this power from an intentional agent. Eight-month-olds are thus capable of representing complex event structures, involving an intentional agent causing a change with a tool.
Topics: Infant; Humans; Intention; Intuition; Eye
PubMed: 38064512
DOI: 10.1073/pnas.2309669120 -
Nature Communications Nov 2023Safety-critical sensory applications, like medical diagnosis, demand accurate decisions from limited, noisy data. Bayesian neural networks excel at such tasks, offering...
Safety-critical sensory applications, like medical diagnosis, demand accurate decisions from limited, noisy data. Bayesian neural networks excel at such tasks, offering predictive uncertainty assessment. However, because of their probabilistic nature, they are computationally intensive. An innovative solution utilizes memristors' inherent probabilistic nature to implement Bayesian neural networks. However, when using memristors, statistical effects follow the laws of device physics, whereas in Bayesian neural networks, those effects can take arbitrary shapes. This work overcome this difficulty by adopting a variational inference training augmented by a "technological loss", incorporating memristor physics. This technique enabled programming a Bayesian neural network on 75 crossbar arrays of 1,024 memristors, incorporating CMOS periphery for in-memory computing. The experimental neural network classified heartbeats with high accuracy, and estimated the certainty of its predictions. The results reveal orders-of-magnitude improvement in inference energy efficiency compared to a microcontroller or an embedded graphics processing unit performing the same task.
PubMed: 37985669
DOI: 10.1038/s41467-023-43317-9 -
International Journal of Molecular... Nov 2023The selection of components within a formulation or for treatment must stop being arbitrary and must be focused on scientific evidence that supports the inclusion of...
Evaluation of the Antimicrobial Activity of a Formulation Containing Ascorbic Acid and Eudragit FS 30D Microparticles for the Controlled Release of a Curcumin-Boric Acid Solid Dispersion in Turkey Poults Infected with : A Therapeutic Model.
The selection of components within a formulation or for treatment must stop being arbitrary and must be focused on scientific evidence that supports the inclusion of each one. Therefore, the objective of the present study was to obtain a formulation based on ascorbic acid (AA) and Eudragit FS 30D microparticles containing curcumin-boric acid (CUR-BA) considering interaction studies between the active components carried out via Fourier transform infrared spectrometry (FTIR) and differential scanning calorimetry (DSC) to minimize antagonistic effects, and comprehensively and effectively treat turkey poults infected with (). The DSC and FTIR studies clearly demonstrated the interactions between AA, BA, and CUR. Consequently, the combination of AA with CUR and/or BA should be avoided, but not CUR and BA. Furthermore, the Eudragit FS 30D microparticles containing CUR-BA (SD CUR-BA MP) showed a limited release of CUR-BA in an acidic medium, but they were released at a pH 6.8-7.0, which reduced the interactions between CUR-BA and AA. Finally, in the infection model, turkey poults treated with the combination of AA and SD CUR-BA MP presented lower counts of in cecal tonsils after 10 days of treatment. These results pointed out that the use of an adequate combination of AA and CUR-BA as an integral treatment of infections could be a viable option to replace the indiscriminate use of antibiotics.
Topics: Animals; Curcumin; Salmonella enteritidis; Delayed-Action Preparations; Ascorbic Acid; Turkeys; Anti-Bacterial Agents
PubMed: 38003375
DOI: 10.3390/ijms242216186 -
Physica Medica : PM : An International... Dec 2023In NM-imaging, theoretical curves for the recovery coefficient (RC) of the signal maximum and mean are known for spheres and cubes, if a 3D Gaussian PSF is assumed. The...
BACKGROUND
In NM-imaging, theoretical curves for the recovery coefficient (RC) of the signal maximum and mean are known for spheres and cubes, if a 3D Gaussian PSF is assumed. The RC of the maximum is also known for cylinders. For these and other shapes empirical equations with one or two fit-parameters have been utilized.
METHODS
An equation for the RC for large objects of arbitrary shape is derived and generalized into an empirical equation for smaller objects, which is verified by numerical simulations. The proposed equation is compared to published results on SPECT kidney phantom measurements and to PET measurements on the NEMA IEC PET body phantom with six spheres.
RESULTS
The signal loss (1-RC) for large spheres is inversely proportional to the radius, where the slope is proportional to the FWHM of the spatial resolution. For non-spherical shapes the generalized instead of the volume equivalent radius should be utilized. For smaller objects, an equation with one added empirical fit-parameter is presented. It is demonstrated that the EANM-guidelines' two-parameter logistic function results in a poor fit if the theoretical slope and inverse proportionality are forced and it gives a suboptimal fit when both parameters are fitted.
CONCLUSIONS
A novel model-based equation for the mean RC-curve is derived. It can be used for arbitrary shapes as long as the sphericity is taken into account and it is accurate down to RC = 10 %. One parameter is directly related to the spatial resolution, while the other is a shape depending fit-parameter.
Topics: Positron-Emission Tomography; Tomography, X-Ray Computed; Phantoms, Imaging; Image Processing, Computer-Assisted
PubMed: 38007296
DOI: 10.1016/j.ejmp.2023.103174 -
PeerJ 2024Metabarcoding is a powerful tool, increasingly used in many disciplines of environmental sciences. However, to assign a taxon to a DNA sequence, bioinformaticians need...
Metabarcoding is a powerful tool, increasingly used in many disciplines of environmental sciences. However, to assign a taxon to a DNA sequence, bioinformaticians need to choose between different strategies or parameter values and these choices sometimes seem rather arbitrary. In this work, we present a case study on ITS2 and databases used to identify pollen collected by bees in Belgium. We blasted a random sample of sequences from the reference database against the remainder of the database using different strategies and compared the known taxonomy with the predicted one. This cross-validation (CV) approach proved to be an easy yet powerful way to (1) assess the relative accuracy of taxonomic predictions, (2) define rules to discard dubious taxonomic assignments and (3) provide a more objective basis to choose the best strategy. We obtained the best results with the best blast hit (best bit score) rather than by selecting the majority taxon from the top 10 hits. The predictions were further improved by favouring the most frequent taxon among those with tied best bit scores. We obtained better results with databases containing the full sequences available on NCBI rather than restricting the sequences to the region amplified by the primers chosen in our study. Leaked CV showed that when the true sequence is present in the database, blast might still struggle to match the right taxon at the species level, particularly with . Classical 10-fold CV-where the true sequence is removed from the database-offers a different yet more realistic view of the true error rates. Taxonomic predictions with this approach worked well up to the genus level, particularly for ITS2 (5-7% of errors). Using a database containing only the local flora of Belgium did not improve the predictions up to the genus level for local species and made them worse for foreign species. At the species level, using a database containing exclusively local species improved the predictions for local species by ∼12% but the error rate remained rather high: 25% for ITS2 and 42% for . Foreign species performed worse even when using a world database (59-79% of errors). We used classification trees and GLMs to model the % of errors . identity and consensus scores and determine appropriate thresholds below which the taxonomic assignment should be discarded. This resulted in a significant reduction in prediction errors, but at the cost of a much higher proportion of unassigned sequences. Despite this stringent filtering, at least 1/5 sequences deemed suitable for species-level identification ultimately proved to be misidentified. An examination of the variability in prediction accuracy between plant families showed that outperformed ITS2 for only two of the 27 families examined, and that the % correct species-level assignments were much better for some families (. 95% for Sapindaceae) than for others (. 35% for Salicaceae).
Topics: Bees; Animals; DNA Barcoding, Taxonomic; Pollen; Plants; Databases, Factual; Belgium
PubMed: 38313030
DOI: 10.7717/peerj.16567 -
EBioMedicine May 2024Matrix metalloproteinases (MMPs) are implied in blood-brain barrier degradation and haemorrhagic transformation following ischaemic stroke, but their local relevance in...
MMP-9 release into collateral blood vessels before endovascular thrombectomy to assess the risk of major intracerebral haemorrhages and poor outcome for acute ischaemic stroke: a proof-of-concept study.
BACKGROUND
Matrix metalloproteinases (MMPs) are implied in blood-brain barrier degradation and haemorrhagic transformation following ischaemic stroke, but their local relevance in the hyperacute disease phase is unknown. We aimed to examine ultra-early MMP-9 and MMP-2 release into collateral blood vessels, and to assess its prognostic value before therapeutic recanalisation by endovascular thrombectomy (EVT).
METHODS
We report a cross-sectional proof-of-concept study including patients undergoing EVT for large-vessel ischaemic stroke at the University Hospital Würzburg, Germany. We obtained liquid biopsies from the collateral circulation before recanalisation, and systemic control samples. Laboratory workup included quantification of MMP-9 and MMP-2 plasma concentrations by cytometric bead array, immunohistochemical analyses of cellular MMP-9 and MMP-2 expression, and detection of proteolytic activity by gelatine zymography. The clinical impact of MMP concentrations was assessed by stratification according to intracranial haemorrhagic lesions on postinterventional computed tomography (Heidelberg Bleeding Classification, HBC) and early functional outcome (modified Rankin Scale, mRS). We used multivariable logistic regression, receiver-operating-characteristic (ROC) curves, and fixed-level estimates of test accuracy measures to study the prognostic value of MMP-9 concentrations.
FINDINGS
Between August 3, 2018, and September 16, 2021, 264 matched samples from 132 patients (86 [65.2%] women, 46 [34.8%] men, aged 40-94 years) were obtained. Median (interquartile range, IQR) MMP-9 (279.7 [IQR 126.4-569.6] vs 441 [IQR 223.4-731.5] ng/ml, p < 0.0001) but not MMP-2 concentrations were increased within collateral blood vessels. The median MMP-9 expression level of invading neutrophils was elevated (fluorescence intensity, arbitrary unit: 2276 [IQR 1007-5086] vs 3078 [IQR 1108-7963], p = 0.0018). Gelatine zymography experiments indicated the locally confined proteolytic activity of MMP-9 but not of MMP-2. Pretherapeutic MMP-9 release into stroke-affected brain regions predicted the degree of intracerebral haemorrhages and clinical stroke severity after recanalisation, and independently increased the odds of space-occupying parenchymal haematomas (HBC1c-3a) by 1.54 times, and the odds of severe disability or death (mRS ≥5 at hospital discharge) by 2.33 times per 1000 ng/ml increase. Excessive concentrations of MMP-9 indicated impending parenchymal haematomas and severe disability or death with high specificity.
INTERPRETATION
Measurement of MMP-9 within collateral blood vessels is feasible and identifies patients with stroke at risk of major intracerebral haemorrhages and poor outcome before therapeutic recanalisation by EVT, thereby providing evidence of the concept validity of ultra-early local stroke biomarkers.
FUNDING
This work was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) and the Interdisciplinary Centre for Clinical Research (IZKF) at the University of Würzburg.
Topics: Humans; Matrix Metalloproteinase 9; Male; Female; Thrombectomy; Aged; Cerebral Hemorrhage; Ischemic Stroke; Middle Aged; Endovascular Procedures; Prognosis; Aged, 80 and over; Matrix Metalloproteinase 2; Biomarkers; Treatment Outcome; Cross-Sectional Studies; ROC Curve; Collateral Circulation
PubMed: 38579365
DOI: 10.1016/j.ebiom.2024.105095 -
Heliyon Jul 2023Natural killer (NK) cells are innate immune cells that can remove viral-infected tumour cells without antigen priming. This characteristic offers NK cells an edge over...
Natural killer (NK) cells are innate immune cells that can remove viral-infected tumour cells without antigen priming. This characteristic offers NK cells an edge over other immune cells as a potential therapy for nasopharyngeal carcinoma (NPC). In this study, we report how cytotoxicity was evaluated in target NPC cell lines and patient-derived xenograft (PDX) cells with effector NK-92, a commercially available NK cell line, by using xCELLigence RTCA system (a real-time, label-free impedance-based monitoring platform). Cell viability, proliferation and cytotoxicity were examined by RTCA. Cell morphology, growth and cytotoxicity were also monitored by microscopy. RTCA and microscopy showed that both target and effector cells were able to proliferate normally and to maintain original morphology in co-culture medium as they were in their own respective culture medium. As target and effector (T:E) cell ratios increased, cell viability as measured by arbitrary cell index (CI) values in RTCA decreased in all cell lines and PDX cells. NPC PDX cells were more sensitive to the cytotoxicity effect of NK-92 cells, than the NPC cell lines. These data were substantiated by GFP-based microscopy. We have shown how the RTCA system can be used for a high throughput screening of the effects of NK cells in cancer studies to obtain data such as cell viability, proliferation and cytotoxicity.
PubMed: 37415945
DOI: 10.1016/j.heliyon.2023.e17480 -
Science & Justice : Journal of the... Jan 2024In recent years, numerous studies have examined the chemical compounds of petrol and petrol data for forensic research. Standard quantitative methods often assume that...
In recent years, numerous studies have examined the chemical compounds of petrol and petrol data for forensic research. Standard quantitative methods often assume that the variables or compounds do not have compositional constraints or are not part of a constrained whole, operating within an Euclidean vector space. However, chemical compounds are typically part of a whole, and the appropriate vector space for their analysis is the simplex. Biased and arbitrary results result when statistical analysis are applied on such data without proper pre-processing of such data. Compositional analysis of data has not yet been considered in forensic science. Therefore, we compare classical statistical analysis as applied in forensic research and the new proposed paradigm of compositional data analysis (CoDa). It is demonstrated how such analysis improves the analysis in petrol and forensic science. Our study shows how principal component analysis (PCA) and classification results are affected by the preprocessing steps performed on the raw data. Our results indicate that results from a log ratio analysis provides a better separation between subgroups of the data and leads to an easier interpretation of the results. In addition, with a compositional analysis a higher classification accuracy is obtained. Even a non-linear classification method - in our case a random forest - was shown to perform poorly when applied without using compositional methods. Moreover, normalization of samples due to laboratory/unit-of-measurement effects is no longer necessary, since the composition of an observation is in compositional thinking equivalent to a multiple of it, because the used (log) ratios on raw and log ratio transformed data are equal. Petrol data from different petrol stations in Brazil are used for the demonstration. This data is highly susceptible to counterfeit petrol. Forensic analysis of its chemical elements requires non-biased statistical analysis designed for compositional data to detect fraud. Based on these results, we recommend the use of compositional data methods for gasoline and petrol chemical element analysis and gasoline product characterization, authentication and fraud detection in forensic sciences.
PubMed: 38182317
DOI: 10.1016/j.scijus.2023.11.003 -
MedRxiv : the Preprint Server For... Jul 2023Genome-wide association studies (GWAS) of human complex traits or diseases often implicate genetic loci that span hundreds or thousands of genetic variants, many of...
Genome-wide association studies (GWAS) of human complex traits or diseases often implicate genetic loci that span hundreds or thousands of genetic variants, many of which have similar statistical significance. While statistical fine-mapping in individuals of European ancestries has made important discoveries, cross-population fine-mapping has the potential to improve power and resolution by capitalizing on the genomic diversity across ancestries. Here we present SuSiEx, an accurate and computationally efficient method for cross-population fine-mapping, which builds on the single-population fine-mapping framework, Sum of Single Effects (SuSiE). SuSiEx integrates data from an arbitrary number of ancestries, explicitly models population-specific allele frequencies and LD patterns, accounts for multiple causal variants in a genomic region, and can be applied to GWAS summary statistics. We comprehensively evaluated SuSiEx using simulations, a range of quantitative traits measured in both UK Biobank and Taiwan Biobank, and schizophrenia GWAS across East Asian and European ancestries. In all evaluations, SuSiEx fine-mapped more association signals, produced smaller credible sets and higher posterior inclusion probability (PIP) for putative causal variants, and captured population-specific causal variants.
PubMed: 36711496
DOI: 10.1101/2023.01.07.23284293