Orders Of Magnitude Research Articles

Extent of magnitude representation deficit and relationship with arithmetic skills in children with 22q11.2DS

BackgroundPrevious studies have produced conflicting results concerning the extent of magnitude representation deficit and its relationship with arithmetic achievement in children with 22q11.2 deletion syndrome. More specifically, it remains unclear whether deficits are restricted to visuospatial content or are more general and whether they could explain arithmetical impairment.MethodsFifteen 5- to 12-year-old children with 22q11.2 deletion syndrome and 23 age-matched healthy controls performed a non-symbolic magnitude comparison task. Depending on the trial, participants had to compare stimuli with high or low visuospatial load (visuospatial stimuli or temporal sequence of visual stimuli). The participants also completed a battery of arithmetic skills (ZAREKI-R) and a battery of global cognitive functioning (WISC-V or WPPSI-IV), from which working memory and visuospatial indices were derived.ResultsChildren with 22q11.2DS responded as fast as healthy controls did but received fewer correct responses, irrespective of visuospatial load. In addition, their performance in the non-symbolic magnitude comparison task did not correlate with the ZAREKI total score, while the working memory index did.ConclusionChildren with 22q11.2DS might suffer from a global magnitude representation deficit rather than a specific deficit due to visuospatial load. However, this deficit alone does not seem to be related to arithmetic achievement. Working memory might be a better concern of interest in favoring arithmetic skills in patients with 22q11.2 deletion syndrome.Trial registrationClinicaltrials, NCT04373226. Registered 16 September 2020.

An Almost Deterministic Cooling by Measurements

AbstractNondeterministic measurement‐based techniques are efficient in reshaping the population distribution of a quantum system but suffer from a limited success probability of holding the system in the target state. To save the experimental cost, a two‐step protocol is proposed to cool a resonator down to the ground state with a near‐unit probability by exploiting the state‐engineering mechanisms of both conditional and unconditional measurements on an ancillary qubit. In the first step, the unconditional measurements on the ancillary qubit are applied to reshape the target resonator from a thermal state to a reserved Fock state. The measurement sequence can be efficiently optimized by reinforcement learning for maximum fidelity. In the second step, the population on the reserved state can be faithfully transferred in a stepwise way to the resonator's ground state with a near‐unit fidelity by the conditional measurements on the qubit. Properly designing the projection operator and the measurement interval enables the Kraus operator to act as a lowering operator for neighboring Fock states. Through dozens of measurements in all, the initial thermal average population of the resonator can be reduced by five orders in magnitude with a success probability of over 95%.

Fast normalized cross-correlation for template matching with rotations

Normalized cross-correlation is the reference approach to carry out template matching on images. When it is computed in Fourier space, it can handle efficiently template translations but it cannot do so with template rotations. Including rotations requires sampling the whole space of rotations, repeating the computation of the correlation each time.This article develops an alternative mathematical theory to handle efficiently, at the same time, rotations and translations. Our proposal has a reduced computational complexity because it does not require to repeatedly sample the space of rotations. To do so, we integrate the information relative to all rotated versions of the template into a unique symmetric tensor template -which is computed only once per template-. Afterward, we demonstrate that the correlation between the image to be processed with the independent tensor components of the tensorial template contains enough information to recover template instance positions and rotations. Our proposed method has the potential to speed up conventional template matching computations by a factor of several magnitude orders for the case of 3D images.

Long-term dynamics of velocities of horizontal channel erosions on the rivers of Udmurtia

The results of a study of channel displacement for 2000–2022 in 55 key areas located on rivers of different orders, draining across different landscapes of Udmurtia, are presented. The erosion rates were determined using benchmarks and tacheometric survey. To analyze the obtained results, the rivers were divided into 4 groups based on their order magnitude (according to the method of A. Scheidegger). Maximum erosion rate (up to 15 m/year) is typical for rivers of an order higher than 14, 6–8 m/year for medium rivers with an order of 9–14, 5.5 m/year for small rivers with an order of 6–9, and up to 4.2 m/year for very small rivers (of order 6 or less) under natural conditions and up to 8.1 m/year with man-made intervention. The mean annual and maximum amount of erosion were calculated for each reference areas for the period of observation. Correlation analysis showed a high significant relationship between the erosion rate and river order and, accordingly, the average annual and maximum discharges. The connection between the values of erosion and the annual amount of precipitation was found only for 3 small rivers within the Kilmez River basin. Trend analysis of erosion over a 23-year time interval was performed for the selected groups of rivers.

Optimal multiple functional regression analysis using perturbation theory

ABSTRACT A regression analysis is presented based on several functions. A normalized data are used which enables the usage of magnitude of orders in perturbation theory. The criteria to eliminate unnecessary base functions are derived with the aid of order of magnitudes in perturbations. The analysis generalizes the previous work on polynomial regression of arbitrary orders. Properties of the regression coefficients are outlined via theorems. Numerical tests are conducted to outline the usage of the analysis to eliminate unnecessary functions and obtain a reasonable approximation of the data in a continuous form.

Visible-Light Self-Powered Photodetector with High Sensitivity Based on the Type-II Heterostructure of CdPSe3/MoS2.

Transition metal thiophosphates (MTPs) are a group of emerging van der Waals materials with widely tunable band gaps. In the MTP family, CdPSe3 is demonstrated to possess a wide energy band gap and high carrier mobility, making it a potential candidate in optoelectronic applications. Here, we reported photoelectric response behaviors of both CdPSe3- and CdPSe3/MoS2-based photodetectors (noted as CPS and CM, respectively); these showed prominent photoelectric performances, and the latter proved to be significantly superior to the former. These devices exhibited ultralow dark current at a magnitude order of 10-12 A and fine cycle and air stabilities. Compared with CPS, CM demonstrated the highest responsivity (91.12 mA/W) and detectivity (1.74 × 1011 Jones) at 5 V under 425 nm light illumination. Besides, CM showed self-powered photoelectric responses at zero bias, which was attributed to the improved separation efficiency of photogenerated carriers by the built-in electric field at the interface of the p-n junction. This work proves a prospect for the CM device in portable, self-powered optoelectronic device applications.

CircHIPK3 nucleates IGF2BP2 and functions as a competing endogenous RNA.

Circular RNAs (circRNAs) represent a class of widespread endogenous RNAs that regulate gene expression and thereby influence cell biological decisions with implications for the pathogenesis of several diseases. Here, we disclose a novel gene-regulatory role of circHIPK3 by combining analyses of large genomics datasets and mechanistic cell biological follow-up experiments. Specifically, we use temporal depletion of circHIPK3 or specific RNA binding proteins (RBPs) and identify several perturbed genes by RNA sequencing analyses. Using expression-coupled motif analyses of mRNA expression data from various knockdown experiments, we identify an 11-mer motif within circHIPK3, which is also enriched in genes that become downregulated upon circHIPK3 depletion. By mining eCLIP datasets, we find that the 11-mer motif constitutes a strong binding site for IGF2BP2 and validate this circHIPK3-IGF2BP2 interaction experimentally using RNA-immunoprecipitation and competition assays in bladder cancer cell lines. Our results suggest that circHIPK3 and IGF2BP2 mRNA targets compete for binding. Since the identified 11-mer motif found in circHIPK3 is enriched in upregulated genes following IGF2BP2 knockdown, and since IGF2BP2 depletion conversely globally antagonizes the effect of circHIPK3 knockdown on target genes, our results suggest that circHIPK3 can sequester IGF2BP2 as a competing endogenous RNA (ceRNA), leading to target mRNA stabilization. As an example of a circHIPK3-regulated gene, we focus on the STAT3 mRNA as a specific substrate of IGF2BP2 and validate that manipulation of circHIPK3 regulates IGF2BP2- STAT3 mRNA binding and thereby STAT3 mRNA levels. However, absolute copy number quantifications demonstrate that IGF2BP2 outnumbers circHIPK3 by orders of magnitude, which is inconsistent with a simple 1:1 ceRNA hypothesis. Instead, we show that circHIPK3 can nucleate multiple copies of IGF2BP2, potentially via phase separation, to produce IGF2BP2 condensates. Finally, we show that circHIPK3 expression correlates with overall survival of patients with bladder cancer. Our results are consistent with a model where relatively few cellular circHIPK3 molecules function as inducers of IGF2BP2 condensation thereby regulating STAT3 and other key factors for cell proliferation and potentially cancer progression.

Suppression of Subpixel Jitter in Resonant Scanning Systems With Phase-locked Sampling.

Resonant scanning is critical to high speed and in vivo imaging in many applications of laser scanning microscopy. However, resonant scanning suffers from well-known image artifacts due to scanner jitter, limiting adoption of high-speed imaging technologies. Here, we introduce a real-time, inexpensive and all electrical method to suppress jitter more than an order of magnitude below the diffraction limit that can be applied to most existing microscope systems with no software changes. By phase-locking imaging to the resonant scanner period, we demonstrate an 86% reduction in pixel jitter, a 15% improvement in point spread function with resonant scanning and show that this approach enables two widely used models of resonant scanners to achieve comparable accuracy to galvanometer scanners running two orders of magnitude slower. Finally, we demonstrate the versatility of this method by retrofitting a commercial two photon microscope and show that this approach enables significant quantitative and qualitative improvements in biological imaging.

Mining Spatial Co-Location Patterns With a Mixed Prevalence Measure.

A co-location pattern indicates a subset of spatial features whose instances are frequently located together in proximate geographical space. Most previous studies of spatial co-location pattern mining concern what percentage of instances per feature are involved in the table instance of a pattern, but neglect the heterogeneity in the number of feature instances and the distribution of instances. As a result, the deviation may be occurred in the interest measure of co-locations. In this article, we propose a novel mixed prevalence index (MPI) incorporating the effect of feature-level and instance-level heterogeneity on the prevalence measure, which can address some dilemmas in existing interest measures. Luckily, MPI possesses the partial antimonotone property. In virtue of this property, a branch-based search algorithm equipped with some optimizing strategies of MPI calculation is proposed, namely, Branch-Opt-MPI. Comprehensive experiments are conducted on both real and synthetic spatial datasets. Experimental results reveal the superiority of MPI compared to other interest measures and also validate the efficiency and scalability of the Branch-Opt-MPI. Particularly, the Branch-Opt-MPI performs more efficiently than baselines for several times or even orders of magnitude in dense data.

New Era in Cultural Heritage Preservation: Cooperative Aerial Autonomy for Fast Digitalization of Difficult-to-Access Interiors of Historical Monuments

Digital documentation of large interiors of historical buildings is an exhausting task since most of the areas of interest are beyond typical human reach. We advocate the use of autonomous teams of multi-rotor Unmanned Aerial Vehicles (UAVs) to speed up the documentation process by several orders of magnitude while allowing for a repeatable, accurate, and condition-independent solution capable of precise collision-free operation at great heights. The proposed multi-robot approach allows for performing tasks requiring dynamic scene illumination in large-scale real-world scenarios, a process previously applicable only in small-scale laboratory-like conditions. Extensive experimental analyses range from single-UAV imaging to specialized lighting techniques requiring accurate coordination of multiple UAVs. The system's robustness is demonstrated in more than two hundred autonomous flights in fifteen historical monuments requiring superior safety while lacking access to external localization. This unique experimental campaign, cooperated with restorers and conservators, brought numerous lessons transferable to other safety-critical robotic missions in documentation and inspection tasks.

Accelerating Globally Optimal Consensus Maximization in Geometric Vision.

Branch-and-bound-based consensus maximization stands out due to its important ability of retrieving the globally optimal solution to outlier-affected geometric problems. However, while the discovery of such solutions caries high scientific value, its application in practical scenarios is often prohibited by its computational complexity growing exponentially as a function of the dimensionality of the problem at hand. In this work, we convey a novel, general technique that allows us to branch over an n-1 dimensional space for an n-dimensional problem. The remaining degree of freedom can be solved globally optimally within each bound calculation by applying the efficient interval stabbing technique. While each individual bound derivation is harder to compute owing to the additional need for solving a sorting problem, the reduced number of intervals and tighter bounds in practice lead to a significant reduction in the overall number of required iterations. Besides an abstract introduction of the approach, we present applications to four fundamental geometric computer vision problems: camera resectioning, relative camera pose estimation, point set registration, and rotation and focal length estimation. Through our exhaustive tests, we demonstrate significant speed-up factors at times exceeding two orders of magnitude, thereby increasing the viability of globally optimal consensus maximizers in online application scenarios.

Luminous giants populate the dense Cosmic Web

Context. Giant radio galaxies (GRGs, giant RGs, or giants) are megaparsec-scale, jet-driven outflows from accretion disks of supermassive black holes, and represent the most extreme pathway by which galaxies can impact the Cosmic Web around them. A long-standing but unresolved question is why giants are so much larger than other radio galaxies. Aims. It has been proposed that, in addition to having higher jet powers than most RGs, giants might live in especially low-density Cosmic Web environments. In this work, we aim to test this hypothesis by pinpointing Local Universe giants and other RGs in physically principled, Bayesian large-scale structure reconstructions. Methods. More specifically, we localised a LOFAR Two-metre Sky Survey (LoTSS) DR2–dominated sample of luminous (lν(ν = 150 MHz)≥1024 W Hz−1) giants and a control sample of LoTSS DR1 RGs, both with spectroscopic redshifts up to zmax = 0.16, in the BORG SDSS Cosmic Web reconstructions. We measured the Cosmic Web density on a smoothing scale of ∼2.9 Mpc h−1 for each RG; for the control sample, we then quantified the relation between RG radio luminosity and Cosmic Web density. With the BORG SDSS tidal tensor, we also measured for each RG whether the gravitational dynamics of its Cosmic Web environment resemble those of clusters, filaments, sheets, or voids. Results. For both luminous giants and general RGs, the Cosmic Web density distribution is gamma distribution–like. Luminous giants populate large-scale environments that tend to be denser than those of general RGs. This result is corroborated by gravitational dynamics classification and a cluster catalogue crossmatching analysis. We find that the Cosmic Web density around RGs with 150 MHz radio luminosity lν is distributed as 1 + ΔRG | Lν = lν ∼ Γ(k, θ), where k = 4.8 + 0.2 · √, θ = 1.4 + 0.02 · √, and √:= log10(lν (1023 W Hz−1)−1). Conclusions. This work presents more than a thousand inferred megaparsec-scale densities around radio galaxies, which may be correct up to a factor of order unity – except in clusters of galaxies, where the densities can be more than an order of magnitude too low. We pave the way to a future in which megaparsec-scale densities around RGs are common inferred quantities, which help to better understand their dynamics, morphology, and interaction with the enveloping Cosmic Web. Our data demonstrate that luminous giants inhabit denser environments than general RGs. This shows that – at least at high jet powers – low-density environments are no prerequisite for giant growth. Using general RGs, we quantified the relation between radio luminosity at 150 MHz and Cosmic Web density on a smoothing scale of ∼2.9 Mpc h−1. This positive relation, combined with the discrepancy in radio luminosity between known giants and general RGs, reproduces the discrepancy in Cosmic Web density between known giants and general RGs. Our findings are consistent with the view that giants are regular, rather than mechanistically special, members of the radio galaxy population.

A Frequency-Switching Inductive Power Transfer System for Wireless, Miniaturised and Large-Scale Neural Interfaces.

Three-coil inductive power transfer is the state-of-the-art solution to power multiple miniaturised neural implants. However, the maximum delivered power is limited by the efficiency of the powering link and safety constrains. Here we propose a frequency-switching inductive link, where the passive resonator normally used in a three-coil link is replaced by an active resonator. It receives power from the external transmitter via a two-coil inductive link at the low frequency of 13.56 MHz. Then, it switches the operating frequency to the higher frequency of 433.92 MHz through a dedicated circuitry. Last, it transmits power to 1024 miniaturised implants via a three-coil inductive link using an array of 37 focusing resonators for a brain coverage of 163.84 mm 2. Our simulations reported a power transfer efficiency of 0.013 % and a maximum power delivered to the load of 1970 μW under safety-constrains, which are respectively two orders of magnitude and more than six decades higher compared to an equivalent passive three-coil link. The frequency-switching inductive system is a scalable and highly versatile solution for wireless, miniaturised and large-scale neural interfaces.

P‐225: Late‐News Poster: Improving Specific Contact Resistivity of a‐IGZO Thin‐Film‐Transistors via Multi‐stack Interlayer

We report the effects of sputter‐based multi‐stack interlayer on the electrical contact properties of a‐IGZO TFTs. The a‐IGZO TFTs with a multi‐stack interlayer of TiN and IGTO showed remarkable outcomes, including the lowest specific contact resistivity (ρC) and the highest field‐effect mobility (μFET). This research suggests a highly effective approach to reduce the contact resistivity of oxide semiconductors by nearly two orders magnitude.

Study of the Accuracy of the Ronen Method at Material Interfaces

The Ronen Method (RM) is a nonlinear iterative scheme that demands successive resolutions of the diffusion equation, where local diffusion constants are modified to reproduce more accurate estimates of the neutron currents by a transport operator. The methodology is currently formulated using the formalism of the collision probability method for evaluation of the current. The RM was recently tested on a complete suite of one-dimensional (1-D) multigroup benchmark problems. Small differences in the flux (less than 2%) were reported at material interfaces and close to the vacuum boundary with respect to the reference solution from transport. This work investigates first a possible numerical equivalence between transport and diffusion in some representative 1-D problems from the same benchmark test suite. The equivalence is sought with optimal diffusion coefficients computed using reference transport solutions that allow for adjusting the diffusion model. The RM, which attempts to obtain such equivalent diffusion coefficients without knowing the reference solution, is then compared to the optimal coefficients. The accuracy of the flux distribution at material interfaces is investigated for different approximations of the vacuum boundary and by decreasing progressively the RM convergence tolerance set in the iterative scheme. Using tighter convergence criteria, the RM calculates more accurate flux distributions at all material interfaces, regardless of the value of the diffusion coefficient and the extrapolated distance set at the beginning of the iterative scheme. Maximum flux deviations are remarkably reduced when the RM convergence tolerance is set to eight or more significant digits, leading to improvements in the flux deviation of two orders in magnitude and providing numerical proof for equivalence with transport in the tested configurations.

Ultra-Sensitive Detection of the SARS-CoV-2 Nucleocapsid Protein via a Clustered Regularly Interspaced Short Palindromic Repeat/Cas12a-Mediated Immunoassay.

Tracking trace protein analytes in precision diagnostics is an ongoing challenge. Here, we developed an ultrasensitive detection method for the detection of SARS-CoV-2 nucleocapsid (N) protein by combining enzyme-linked immunosorbent assay (ELISA) with the clustered regularly interspaced short palindromic repeat/CRISPR-associated protein (CRISPR/Cas) system. First, the SARS-CoV-2 N protein bound by the capture antibody adsorbed on the well plate was sequentially coupled with the primary antibody, biotinylated secondary antibody, and streptavidin (SA), followed by biotin primer binding to SA. Subsequently, rolling circle amplification was initiated to generate ssDNA strands, which were targeted by CRISPR/Cas12a to cleave the FAM-ssDNA-BHQ1 probe in trans to generate fluorescence signals. We observed a linear relationship between fluorescence intensity and the logarithm of N protein concentration ranging from 3 fg/mL to 3 × 107 fg/mL. The limit of detection (LOD) was 1 fg/mL, with approximately nine molecules in 1 μL of the sample. This detection sensitivity was 4 orders magnitude higher than that of commercially available ELISA kits (LOD: 5.7 × 104 fg/mL). This method was highly specific and sensitive and could accurately detect SARS-CoV-2 pseudovirus and clinical samples, providing a new approach for ultrasensitive immunoassay of protein biomarkers.

Combustion performance of hydrogen fueled parallel wall-jet used for drag reduction in a supersonic combustor

Hydrogen fueled parallel wall-jet combustion is considered to be one of the most promising drag reduction technologies in supersonic combustors, researchers mainly focus on its drag reduction mechanism, while balancing its combustion efficiency and drag reduction performance is of great significance for engine performance and energy conservation. In this paper, combustion performance of hydrogen fueled parallel wall-jet is numerically investigated. Kinetic reaction rate and scalar dissipation rate are defined to decouple the chemical reaction and mixing processes. Results indicate that although hydrogen fueled parallel wall-jet combustion is a nonequilibrium chemical reaction process, the combustion process is dominated by mixing due to the much larger magnitude order of kinetic reaction rate. The investigation also reveals that, compared to the effects of mainstream total temperature, mainstream Mach number presents a more significant effect on combustion efficiency. Moreover, combustion efficiency increase first brings negative and then brings beneficial effects on drag reduction performance, which is due to the different sensibilities of the two skin friction determinants viscosity and velocity gradient to combustion efficiency. It is found that, viscosity is more sensitive to combustion efficiency, with combustion efficiency increases by 5.4 %, viscosity increases by 4.15 %, while velocity gradient only decreases by 2.19 %.

Effects of cell parameters on accurate calculation of activation dose after DT explosion for local hot spots in laser-driven ICF facilities

Instruments placed in the target chamber will be highly activated after DT explosion in laser-driven ICF experiments, especially for the part near the chamber center. Operations near those local hot spots are the main concern for radiation protection due to its high contribution to the occupation exposure dose, therefore it becomes very important to calculate the dose during the operating process accurately. Cell-based rigorous two-step (R2S) method has been introduced to deal with the activated objects with highly heterogeneous distribution, and the effects of cell size, materials as well as radiation source have also been specified to improve the accuracy of simulations. Results for a typical model sample show that with a given distribution of radiation source, cell size in the simulations placed a significant influence on the accuracy of the radiation field. A cell size of 50 cm for a 100 cm cone-shaped sample will lead to the inaccuracy of the radiation field as large as an order in magnitude within the location 50 cm from the surface of the sample. While for the same sample model, cell size should be limited to smaller than 2 cm to ensure an accuracy lower than ±10 %. In addition, the effects of the material and source energy on the calculation accuracy for the radiation field could be neglected if the cell size is limited to smaller than 5 cm. Furthermore, the influence of cell size increased as the distance from the sample surface decreased, which indicates that appropriate cell size must be chosen to ensure the accuracy of dose estimation, especially for surface contact operations. Besides, a significant difference between the effective dose and skin-equivalent dose has been observed for the typical mode used in the calculations.

FLASH FLOODS: RISK ASSESSMENT AND MITIGATION

In recent years, United Arab Emirates has experienced several flash flood events and extreme cyclonic events that resulted in flooding various parts of the country. This in return raised concerns on the preparedness of the infrastructure to such events considering the damage caused by them. Roads were blocked from the excessive rainfall water leading to heavy traffic jams, houses were drowned and cars were swept away. Therefore, an in-depth study was performed on a selected area of interest in the city of Ras Al-Khaimah (UAE) to explore the risks associated with flash flood events and to propose solutions for flood management. Hydrological and hydraulic models were used to simulate precipitation runoffs and calculate flood magnitudes in order to plan and design new flood control and hydraulic structures. Using the output of the hydrologic and hydraulic models, a dam and a protection channel were proposed as possible solutions to resolve flood issues in the selected area. It was concluded that with proper hydrologic modelling, flash floods can be managed to a great extent and damage to the infrastructure can be minimized. It is even more important in context of climate change that such modelling techniques should be part of urban planning and design of infrastructure drainage systems for areas that are prone to heavy rainfall and floods.

FLASH FLOODS: RISK ASSESSMENT AND MITIGATION

In recent years, United Arab Emirates has experienced several flash flood events and extreme cyclonic events that resulted in flooding various parts of the country. This in return raised concerns on the preparedness of the infrastructure to such events considering the damage caused by them. Roads were blocked from the excessive rainfall water leading to heavy traffic jams, houses were drowned and cars were swept away. Therefore, an in-depth study was performed on a selected area of interest in the city of Ras Al-Khaimah (UAE) to explore the risks associated with flash flood events and to propose solutions for flood management. Hydrological and hydraulic models were used to simulate precipitation runoffs and calculate flood magnitudes in order to plan and design new flood control and hydraulic structures. Using the output of the hydrologic and hydraulic models, a dam and a protection channel were proposed as possible solutions to resolve flood issues in the selected area. It was concluded that with proper hydrologic modelling, flash floods can be managed to a great extent and damage to the infrastructure can be minimized. It is even more important in context of climate change that such modelling techniques should be part of urban planning and design of infrastructure drainage systems for areas that are prone to heavy rainfall and floods.