Linear Alignment Research Articles

Kepler’s Conjunction for Two Strong Earthquakes in Türkiye in February 2023

This work is devoted to the study of the relationship between strong earthquakes and planetary configurations using the example of two consecutive strong earthquakes that occurred in Türkiye (Turkey), on February 6, 2023. It is shown that at the time of the earthquakes, linear alignment of the planets along the Jupiter-Venus-Sun line was observed, that is, the astronomical trigger belonged to the generalized Kepler conjunction scheme (gKc), when the Earth does not participate in the linearization scheme. It is shown that for the first earthquake that occurred at 01:17 UTC, the ratio of the distances between Jupiter-Earth and Jupiter-Mars was close to an integer value equal to 5.993. For the second earthquake that occurred on the same day at 10:25 UTC, no integer resonance ratios were detected, however, it was found that the terrestrial e UTC line at the time of the earthquake passed through the position of Mercury. Recall that the 12-hour line of the eUTC chart is always oriented towards the Sun. The conclusions of the work once again confirm the correctness of the theories of Archimedes and Kepler and convince us of the existence of a gravitational phenomenon that does not depend on the distances and masses of planets, has a pronounced inertial and wave character and does not fit into the general theory of relativity, developed in the last century by Albert Einstein.

On the cosmic web elongation in fuzzy dark matter cosmologies: Effects on density profiles, shapes, and alignments of haloes

ABSTRACT The fuzzy dark matter (FDM) scenario has received increased attention in recent years due to the small-scale challenges of the vanilla Lambda cold dark matter (ΛCDM) cosmological model and the lack of any experimental evidence for any candidate particle. In this study, we use cosmological N-body simulations to investigate high-redshift dark matter haloes and their responsiveness to an FDM-like power spectrum cutoff on small scales in the primordial density perturbations. We study halo density profiles, shapes, and alignments in FDM-like cosmologies (the latter two for the first time) by providing fits and quantifying departures from ΛCDM as a function of the particle mass m. Compared to ΛCDM, the concentrations of FDM-like haloes are lower, peaking at an m-dependent halo mass and thus breaking the approximate universality of density profiles in ΛCDM. The intermediate-to-major and minor-to-major shape parameter profiles are monotonically increasing with ellipsoidal radius in N-body simulations of ΛCDM. In FDM-like cosmologies, the monotonicity is broken, haloes are more elongated around the virial radius than their ΛCDM counterparts and less elongated closer to the centre. Finally, intrinsic alignment correlations, stemming from the deformation of initially spherically collapsing haloes in an ambient gravitational tidal field, become stronger with decreasing m. At z ∼ 4, we find a 6.4σ-significance in the fractional differences between the isotropized linear alignment magnitudes Diso in the m = 10−22 eV model and ΛCDM. Such FDM-like imprints on the internal properties of virialized haloes are expected to be strikingly visible in the high-z Universe.

Spatially Guided Assembly of Polyoxometalate Superlattices and Their Derivatives as High-Power Sodium-Ion Battery Anodes.

The use of polyoxometalate clusters (POMs) with multitudinous structures and surface properties as building blocks has sparked the development of cluster-assembled materials with many prospective applications. In comparison to classic molecules and assembly processes, control over the steric interactions and linkage of large POMs to achieve superlattices with multiple levels of organization remains a great challenge. This work presents a universal approach to modulate the spatial coordination behavior and configurations, and achieves a class of cluster superlattice architectures formed by linear alignment and two-dimensional arrangement of POM units. The formation mechanism is explained as a stepwise co-assembly pathway in which POMs can intervene and dictate a typical stripping-restacking combination mode with the lamellar mediator. These cluster superlattices with long-range POMs ordering impart distinct merits to their derivatives by sulfuration, for which we demonstrate the substantially promoted power and cycling life of these POM derivatives applied as sodium-ion battery anodes.

Joint spectral quantification of MR spectroscopic imaging using linear tangent space alignment-based manifold learning.

To develop a manifold learning-based method that leverages the intrinsic low-dimensional structure of MR Spectroscopic Imaging (MRSI) signals for joint spectral quantification. A linear tangent space alignment (LTSA) model was proposed to represent MRSI signals. In the proposed model, the signals of each metabolite were represented using a subspace model and the local coordinates of the subspaces were aligned to the global coordinates of the underlying low-dimensional manifold via linear transform. With the basis functions of the subspaces predetermined via quantum mechanics simulations, the global coordinates and the matrices for the local-to-global coordinate alignment were estimated by fitting the proposed LTSA model to noisy MRSI data with a spatial smoothness constraint on the global coordinates and a sparsity constraint on the matrices. The performance of the proposed method was validated using numerical simulation data and in vivo proton-MRSI experimental data acquired on healthy volunteers at 3T. The results of the proposed method were compared with the QUEST method and the subspace-based method. In all the compared cases, the proposed method achieved superior performance over the QUEST and the subspace-based methods both qualitatively in terms of noise and artifacts in the estimated metabolite concentration maps, and quantitatively in terms of spectral quantification accuracy measured by normalized root mean square errors. Joint spectral quantification using linear tangent space alignment-based manifold learning improves the accuracy of MRSI spectral quantification.

Identifying 5-Hydroxymethylcytosine without Sequence Specificity Using MOF-Derived MnOxSy Nanoflowers for Boosting Electrochemiluminescence.

It is universally recognized that the quantification of DNA hydroxymethylation at random gene sequences still remains challenging. Herein, the highly sensitive identifying strategy of 5-hydroxymethylcytosine (5-hmC) without sequence specificity was achieved with a novel electrochemiluminescence (ECL) biosensor, which deftly integrated metal-organic framework (MOF)-derived amorphous MnOxSy nanoflowers (MnOxSy NFs) as a bifunctional co-reaction accelerator and cross-shaped DNA tracks as a well-regulated signal switch. Specifically, the target recognition process of 5-hmC was performed through specific chemical modification, where the hydroxymethyl sites were first aminated and then labeled with a 5'-carboxyl-functioned DNA walker, thus forming the target labeled DNA walker (5-ghmC-walker). Subsequently, the cross-shaped DNA tracks were ingeniously designed to endow the 5-ghmC-walker with continuous mechanical motion due to the long periodic linear alignment structure and well-regulated highly ordered interfaces. Furthermore, as a bifunctional co-reaction accelerator synthesized by in situ Mn-MOF template-sacrificing strategy, the MnOxSy NFs could promote the reduction of both dissolved O2 and S2O82-, remarkably boosting the ECL intensity of a peroxydisulfate (S2O82-) solution by 5.2 times compared to the pure S2O82- solution. Benefiting from specific target recognition and a dual-pathway strategy for boosting ECL, the proposed ECL platform can quantify 5-hmC with a wide linear range of 1 fM-1 nM and a low detection limit of 0.29 fM. This simple, highly sensitive strategy without sequence specificity provides a powerful platform for 5-hmC detection in the epigenetic study and disease pathogenesis.

Synthesizing code quality rules from examples

Static Analysis tools have rules for several code quality issues and these rules are created by experts manually. In this paper, we address the problem of automatic synthesis of code quality rules from examples. We formulate the rule synthesis problem as synthesizing first order logic formulas over graph representations of code. We present a new synthesis algorithm RhoSynth that is based on Integer Linear Programming-based graph alignment for identifying code elements of interest to the rule. We bootstrap RhoSynth by leveraging code changes made by developers as the source of positive and negative examples. We also address rule refinement in which the rules are incrementally improved with additional user-provided examples. We validate RhoSynth by synthesizing more than 30 Java code quality rules. These rules have been deployed as part of Amazon CodeGuru Reviewer and their precision exceeds 75% based on developer feedback collected during live code-reviews within Amazon. Through comparisons with recent baselines, we show that current state-of-the-art program synthesis approaches are unable to synthesize most of these rules.

Alignment of single-cell trajectory trees with CAPITAL

Global alignment of complex pseudotime trajectories between different single-cell RNA-seq datasets is challenging, as existing tools mainly focus on linear alignment of single-cell trajectories. Here we present CAPITAL (comparative analysis of pseudotime trajectory inference with tree alignment), a method for comparing single-cell trajectories with tree alignment whereby branching trajectories can be automatically compared. Computational tests on synthetic datasets and authentic bone marrow cells datasets indicate that CAPITAL has achieved accurate and robust alignments of trajectory trees, revealing various gene expression dynamics including gene–gene correlation conservation between different species.

3D Gradient and Linearly Aligned Magnetic Microcapsules in Nerve Guidance Conduits with Remotely Spatiotemporally Controlled Release to Enhance Peripheral Nerve Repair.

Although numerous strategies have been implemented to develop nerve guidance conduits (NGCs) to treat peripheral nerve injury (PNI), functionalization of an NGC to make it remotely controllable for providing spatiotemporal modulation on in situ nerve tissues remains a challenge. In this study, a gelatin/silk (GS) hydrogel was used to develop an NGC based on its self-owned reversible thermoresponsive sol-to-gel phase transformation ability that permitted rapid three-dimensional (3D) micropatterning of the incorporated nerve growth factor (NGF)-loaded magnetic poly(lactic-co-glycolic acid) (PLGA) microcapsules (called NGF@MPs) via multiple magnetic guidance. The thermally controllable viscosity of GS enabled the rapid formation of a 3D gradient and linearly aligned distribution of NGF@MPs, leading to magnetically controlled 3D gradient release of NGF to enhance topographical nerve guidance and wound healing in PNIs. Particularly, the as-formed micropatterned hydrogel, called NGF@MPs-GS, showed corrugation topography with a pattern height H of 15 μm, which resulted in the linear axon alignment of more than 90% of cells. In addition, by an external magnetic field, spatiotemporal controllability of NGF release was obtained and permitted neurite elongation that was almost 2-fold longer than that in the group with external addition of NGF. Finally, an NGC prototype was fabricated and implanted into the injured sciatic nerve. The patterned implant, assisted by magnetic stimulation, demonstrated accelerated restoration of motor function within 14 days after implantation. It further contributed to the enhancement of axon outgrowth and remyelination after 28 days. This NGC, with controllable mechanical, biochemical, and topographical cues, is a promising platform for the enhancement of nerve regeneration.

OpenBHB: a Large-Scale Multi-Site Brain MRI Data-set for Age Prediction and Debiasing

Prediction of chronological age from neuroimaging in the healthy population is an important issue because the deviations from normal brain age may highlight abnormal trajectories towards brain disorders. As a first step, ML models have emerged to predict chronological age from brain MRI, as a proxy measure of biological age. However, there is currently no consensus w.r.t which Machine Learning (ML) model is best suited for this task, largely because of a lack of public benchmark. Furthermore, new large emerging population neuroimaging datasets are often biased by the acquisition center images are coming from. This bias heavily deteriorates models generalization capacities, especially for Deep Learning (DL) algorithms that are known to overfit rapidly on the simplest features (known as simplicity bias). Here we propose a new public benchmarking resource, namely Open Big Healthy Brains (OpenBHB), along with a challenge for both brain age prediction and site-effect removal through a representation learning framework. OpenBHB is large-scale, gathering >5K 3D T1 brain MRI from Healthy Controls (HC) and highly multi-sites, aggregating >60 centers worldwide and 10 studies. OpenBHB is expected to grow both in terms of available modalities and number of subjects. All OpenBHB datasets are uniformly preprocessed, including quality check, with container technologies that consist in: 3D Voxel-Based Morphometry maps (VBM from CAT12), quasi-raw (simple linear alignment of images), and Surface-Based Morphometry indices (SBM, from FreeSurfer). The OpenBHB challenge is permanent and we provide all tools, materials and tutorials for participants to easily submit and benchmark their model against each other on a public leaderboard.

The primeval optical evolving matter by optical binding inside and outside the photon beam

Optical binding has recently gained considerable attention because it enables the light-induced assembly of many-body systems; however, this phenomenon has only been described between directly irradiated particles. Here, we demonstrate that optical binding can occur outside the focal spot of a single tightly focused laser beam. By trapping at an interface, we assemble up to three gold nanoparticles with a linear arrangement which fully-occupies the laser focus. The trapping laser is efficiently scattered by this linear alignment and interacts with particles outside the focus area, generating several discrete arc-shape potential wells with a half-wavelength periodicity. Those external nanoparticles inside the arcs show a correlated motion not only with the linear aligned particles, but also between themselves even both are not directly illuminated. We propose that the particles are optically bound outside the focal spot by the back-scattered light and multi-channel light scattering, forming a dynamic optical binding network.

Template‐Free Scalable Fabrication of Linearly Periodic Microstructures by Controlling Ribbing Defects Phenomenon in Forward Roll Coating for Multifunctional Applications

AbstractPeriodic micro/nanoscale structures from nature have inspired the scientific community to adopt surface design for various applications, including superhydrophobic drag reduction. One primary concern of practical applications of such periodic microstructures remains the scalability of conventional microfabrication technologies. This study demonstrates a simple template‐free scalable manufacturing technique to fabricate periodic microstructures by controlling the ribbing defects in the forward roll coating. Viscoelastic composite coating materials are designed for roll‐coating using carbon nanotubes (CNT) and polydimethylsiloxane (PDMS), which helps achieve a controllable ribbing with a periodicity of 114–700 µm. Depending on the process parameters, the patterned microstructures transition from the linear alignment to a random structure. The periodic microstructure enables hydrophobicity as the water contact angles of the samples ranged from 128° to 158°. When towed in a static water pool, a model boat coated with the microstructure film shows 7%–8% faster speed than the boat with a flat PDMS film. The CNT addition shows both mechanical and electrical properties improvement. In a mechanical scratch test, the cohesive failure of the CNT‐PDMS film occurs in ≈90% higher force than bare PDMS. Moreover, the nonconductive bare PDMS shows sheet resistance of 747.84–22.66 Ω □−1 with 0.5 to 2.5 wt% CNT inclusion.

Field-level inference of galaxy intrinsic alignment from the SDSS-III BOSS survey

As a large-scale overdensity collapses, it affects the orientation and shape of galaxies that form, by exerting tidal shear along their axes. Therefore, the shapes of elliptical galaxies align with the tidal field of cosmic structures. This intrinsic alignment provides insights into galaxy formation and the primordial universe, complements late-time cosmological probes and constitutes a significant systematic effect for weak gravitational lensing observations. In the present study, we provide constraints on the linear alignment model using a fully Bayesian field-level approach, using galaxy shape measurements from the SDSS-III BOSS LOWZ sample and three-dimensional tidal fields constrained with the LOWZ and CMASS galaxy samples of the SDSS-III BOSS survey. We find 4σ evidence of intrinsic alignment, with an amplitude of AI = 2.9 ± 0.7 at 20 Mpch.

Automatic Mapping of Karez in Turpan Basin Based on Google Earth Images and the YOLOv5 Model

As a large-scale irrigation and water conservancy project in ancient times, karez are common in Central Asia and arid regions with a history of thousands of years. Turpan, which is located in the Xinjiang Uyghur Autonomous Region, has the most extensive and concentrated distribution of karez shafts in China. There are tens of thousands of shafts, some of which are in use and are living cultural heritage. According to radiocarbon (14C) dating, some karezs are over 600 years old. The karez is of great significance to the research on geology, hydrology, oasis, climate change, and development history of karez in Turpan. With the development of the population, arable land, industrialization, and urbanization, karez systems are facing the risk of abandonment. Detailed karez distribution mapping or dynamic monitoring data are important for their management or analysis; although there are related methods, due to Turpan’s large desert and “Gobi” environments, field surveys are time- and energy-consuming, and some areas are difficult to access. Precise shaft locations and distribution maps are scarce and often lack georeferencing. The distribution and preservation of karez have not yet been fully grasped. In this study, we evaluated the effectiveness of You Only Look Once version 5 (YOLOv5) in automatically detecting karez in high-resolution images of the Turpan region. We propose post-processing steps to reduce the false karez identified by YOLOv5. Our results demonstrate the feasibility of using YOLOv5 and post-processing techniques to detect karez automatically, and the detected results are sufficient to capture the linear alignment of karez. Target detection based on YOLOv5 and post-processing can greatly improve automatic shaft identification and is therefore useful for the fine mapping of karez. We also applied this method in Shanshan County (for which no detailed mapping data on karez has been obtained before) and successfully detected some karez that had not been archived before. The number of shafts in Turpan is 82,493. Through DBSCAN clustering, it was identified which karez line belonged to which shaft; the number of sections of karez that have been used is 5057, which have a total length of 2387.2 km. The karez line obtained was overlaid with the crop-land data, and the positional relationship between the karez line and the crop land was analyzed. The cultivated area is basically surrounded by karez. Our method can potentially be applied to construct an inventory for all karez shafts globally.

Pairwise Alignment of Archaeological Fragments Through Morphological Characterization of Fracture Surfaces

We design a computational method to align pairs of counter-fitting fracture surfaces of digitized archaeological artefacts. The challenge is to achieve an accurate fit, even though the data is inherently lacking material through abrasion, missing geometry of the counterparts, and may have been acquired by different scanning practices. We propose to use the non-linear complementarity-preserving properties of Mathematical Morphology to guide the pairwise fitting in a manner inherently insensitive to these aspects. In our approach, the fracture surface is tightly bounded by a concise set of characteristic multi-local morphological features. Such features and their descriptors are computed by analysing the discrete distance transform and its causal scale-space information. This compact morphological representation provides the information required for accurately aligning the fracture surfaces through applying a RANSAC-based algorithm incorporating weighted Procrustes to the morphological features, followed by ICP on morphologically selected ‘flank’ regions. We propose new criteria for evaluating the resulting pairwise alignment quality, taking into consideration both penetration and gap regions. Careful quantitative evaluation on real terracotta fragments confirms the accuracy of our method under the expected archaeological noise. We show that our morphological method outperforms a recent linear pairwise alignment method and briefly discuss our limitations and the effects of variations in digitization and abrasion on our proposed alignment technique.

Evaluation of diagnostic x-ray equipment performance in lindi and mtwara regions - Tanzania

The purpose of the study was to evaluate the quality control (QC) tests results of general radiography x-ray equipment in order to assess the performance of the x-ray equipment in comparison to the acceptance limits, hence advise on measures to provide quality diagnostic imaging at optimized dose. QC tests results from health facilities in Mtwara and Lindi regions were evaluated. The QC results from 2015 to 2021 were analyzed for selected QC parameters which included kV accuracy, kV reproducibility, mAs linearity, beam quality, collimation and beam alignment. All x-ray units passed the kV accuracy, kV reproducibility, and beam quality and beam alignment tests. It was noticed that the collimation test surfaced among the failed parameters, though the performance of all the tested parameters were within 76.9 %. to 100% of the acceptable limits. Furthermore, lack of QC and maintenance plan was noted. Generally, the performance of most of the x-ray units were in compliance with regulatory requirements. However, improvement is desirable especially in the areas of QC plan, preventive maintenance and repair. Managers of the facilities need to take heed that optimum equipment performance is vital if quality imaging at optimized radiation dose is to be realized.

An Improved Genome Sequence Resource of Bipolaris maydis, Causal Agent of Southern Corn Leaf Blight.

An Improved Genome Sequence Resource of Bipolaris maydis, Causal Agent of Southern Corn Leaf Blight.

A Transfer Learning Algorithm to Reduce Brain-Computer Interface Calibration Time for Long-Term Users.

Current motor imagery-based brain-computer interface (BCI) systems require a long calibration time at the beginning of each session before they can be used with adequate levels of classification accuracy. In particular, this issue can be a significant burden for long term BCI users. This article proposes a novel transfer learning algorithm, called r-KLwDSA, to reduce the BCI calibration time for long-term users. The proposed r-KLwDSA algorithm aligns the user's EEG data collected in previous sessions to the few EEG trials collected in the current session, using a novel linear alignment method. Thereafter, the aligned EEG trials from the previous sessions and the few EEG trials from the current sessions are fused through a weighting mechanism before they are used for calibrating the BCI model. To validate the proposed algorithm, a large dataset containing the EEG data from 11 stroke patients, each performing 18 BCI sessions, was used. The proposed framework demonstrated a significant improvement in the classification accuracy, of over 4% compared to the session-specific algorithm, when there were as few as two trials per class available from the current session. The proposed algorithm was particularly successful in improving the BCI accuracy of the sessions that had initial session-specific accuracy below 60%, with an average improvement of around 10% in the accuracy, leading to more stroke patients having meaningful BCI rehabilitation.

Cross-lingual alignments of ELMo contextual embeddings

Building machine learning prediction models for a specific NLP task requires sufficient training data, which can be difficult to obtain for less-resourced languages. Cross-lingual embeddings map word embeddings from a less-resourced language to a resource-rich language so that a prediction model trained on data from the resource-rich language can also be used in the less-resourced language. To produce cross-lingual mappings of recent contextual embeddings, anchor points between the embedding spaces have to be words in the same context. We address this issue with a novel method for creating cross-lingual contextual alignment datasets. Based on that, we propose several cross-lingual mapping methods for ELMo embeddings. The proposed linear mapping methods use existing Vecmap and MUSE alignments on contextual ELMo embeddings. Novel nonlinear ELMoGAN mapping methods are based on GANs and do not assume isomorphic embedding spaces. We evaluate the proposed mapping methods on nine languages, using four downstream tasks: named entity recognition (NER), dependency parsing (DP), terminology alignment, and sentiment analysis. The ELMoGAN methods perform very well on the NER and terminology alignment tasks, with a lower cross-lingual loss for NER compared to the direct training on some languages. In DP and sentiment analysis, linear contextual alignment variants are more successful.

Intrinsic alignments in IllustrisTNG and their implications for weak lensing: Tidal shearing and tidal torquing mechanisms put to the test

ABSTRACT Accurate measurements of the cosmic shear signal require a separation of the true weak gravitational lensing signal from intrinsic shape correlations of galaxies. These ‘intrinsic alignments’ of galaxies originate from galaxy formation processes and are expected to be correlated with the gravitational field through tidal processes affecting the galaxies, such as tidal shearing for elliptical galaxies and tidal torquing for spiral galaxies. In this study, we use morphologically selected samples of elliptical and spiral galaxies from the illustrisTNG simulation at z = 0 and z = 1 to test the commonly employed linear (tidal shearing) and quadratic (tidal torquing) models for intrinsic alignments. We obtain local measurements of the linear and quadratic alignment parameters, including corrections for large-scale anisotropies of the cosmologically small simulation volume, and study their dependence on galaxy and environmental properties. We find a significant alignment signal for elliptical galaxies (linear model), that increases with mass and redshift. Spiral galaxies (quadratic model), on the other hand, exhibit a significant signal only for the most massive objects at z = 1. We show the quadratic model for spiral galaxies to break down at its fundamental assumptions, and simultaneously obtain a significant signal of spiral galaxies to align according to the linear model. We use the derived alignment parameters to compute intrinsic alignment spectra and estimate the expected contamination in the weak lensing signal obtained by Euclid.

Genomic variations and epigenomic landscape of the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel

BackgroundThe teleost medaka (Oryzias latipes) is a well-established vertebrate model system, with a long history of genetic research, and multiple high-quality reference genomes available for several inbred strains. Medaka has a high tolerance to inbreeding from the wild, thus allowing one to establish inbred lines from wild founder individuals.ResultsWe exploit this feature to create an inbred panel resource: the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel. This panel of 80 near-isogenic inbred lines contains a large amount of genetic variation inherited from the original wild population. We use Oxford Nanopore Technologies (ONT) long read data to further investigate the genomic and epigenomic landscapes of a subset of the MIKK panel. Nanopore sequencing allows us to identify a large variety of high-quality structural variants, and we present results and methods using a pan-genome graph representation of 12 individual medaka lines. This graph-based reference MIKK panel genome reveals novel differences between the MIKK panel lines and standard linear reference genomes. We find additional MIKK panel-specific genomic content that would be missing from linear reference alignment approaches. We are also able to identify and quantify the presence of repeat elements in each of the lines. Finally, we investigate line-specific CpG methylation and performed differential DNA methylation analysis across these 12 lines.ConclusionsWe present a detailed analysis of the MIKK panel genomes using long and short read sequence technologies, creating a MIKK panel-specific pan genome reference dataset allowing for investigation of novel variation types that would be elusive using standard approaches.