Challenges in data-driven geospatial modeling for environmental research and practice.

Machine learning-based geospatial applications offer unique opportunities for environmental monitoring due to domains and scales adaptability and computational efficiency. However, the specificity of environmental data introduces biases in straightforward implementations. We identify a streamlined pipeline to enhance model accuracy, addressing issues like imbalanced data, spatial autocorrelation, prediction errors, and the nuances of model generalization and uncertainty estimation.

Sudden death of quantum advantage in correlation generations.

Quantum noise is one of the most profound obstacles to implementing large-scale quantum algorithms and schemes. In particular, the dynamical process by which quantum noise, varying in strength from 0 to critical levels, affects and destroys quantum advantage has not been well understood. Meanwhile, correlation generation serves as a precious theoretical model for information processing tasks, where quantum advantage can be precisely quantified.

Simulating Noisy Variational Quantum Algorithms: A Polynomial Approach.

Large-scale variational quantum algorithms are widely recognized as a potential pathway to achieve practical quantum advantages. However, the presence of quantum noise might suppress and undermine these advantages, which blurs the boundaries of classical simulability. To gain further clarity on this matter, we present a novel polynomial-scale method based on the path integral of observable's backpropagation on Pauli paths (OBPPP).

Exploring geometry of genome space via Grassmann manifolds.

It is important to understand the geometry of genome space in biology. After transforming genome sequences into frequency matrices of the chaos game representation (FCGR), we regard a genome sequence as a point in a suitable Grassmann manifold by analyzing the column space of the corresponding FCGR. To assess the sequence similarity, we employ the generalized Grassmannian distance, an intrinsic geometric distance that differs from the traditional Euclidean distance used in the classical k-mer frequency-based methods.

CryoTRANS: predicting high-resolution maps of rare conformations from self-supervised trajectories in cryo-EM.

Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, enabling efficient determination of structures at near-atomic resolutions. However, a common challenge arises from the severe imbalance among various conformations of vitrified particles, leading to low-resolution reconstructions in rare conformations due to a lack of particle images in these quasi-stable states. We introduce CryoTRANS, a method that predicts high-resolution maps of rare conformations by constructing a self-supervised pseudo-trajectory between density maps of varying resolutions.

An integrative multi-context Mendelian randomization method for identifying risk genes across human tissues.

Mendelian randomization (MR) provides valuable assessments of the causal effect of exposure on outcome, yet the application of conventional MR methods for mapping risk genes encounters new challenges. One of the issues is the limited availability of expression quantitative trait loci (eQTLs) as instrumental variables (IVs), hampering the estimation of sparse causal effects. Additionally, the often context- or tissue-specific eQTL effects challenge the MR assumption of consistent IV effects across eQTL and GWAS data.

Enhancing Density Maps by Removing the Majority of Particles in Single Particle Cryogenic Electron Microscopy Final Stacks.

Over the past decade, advancements in technology and methodology within the field of cryogenic electron microscopy (cryo-EM) single-particle analysis (SPA) have substantially improved our capacity for high-resolution structural examination of biological macromolecules. This advancement has ushered in a new era of molecular insights, replacing X-ray crystallography as the dominant method and providing answers to longstanding questions in biology. Since cryo-EM does not depend on crystallization, which is a significant limitation of X-ray crystallography, it captures particles of varying quality.

Geometric analysis of SARS-CoV-2 variants.

SARS-CoV-2 as a severe respiratory disease has been prevalent around the world since its first discovery in 2019.As a single-stranded RNA virus, its high mutation rate makes its variants manifold and enables some of them to have high pathogenicity, such as Omicron variant, the most prevalent virus now. Research on the relationship of these SARS-CoV-2 variants, especially exploring their difference is a hot issue.

Genome-Wide Network Analysis of Above- and Below-Ground Co-growth in .

Tree growth is the consequence of developmental interactions between above- and below-ground compartments. However, a comprehensive view of the genetic architecture of growth as a cohesive whole is poorly understood. We propose a systems biology approach for mapping growth trajectories in genome-wide association studies viewing growth as a complex (phenotypic) system in which above- and below-ground components (or traits) interact with each other to mediate systems behavior.

A minority of final stacks yields superior amplitude in single-particle cryo-EM.

Cryogenic electron microscopy (cryo-EM) is widely used to determine near-atomic resolution structures of biological macromolecules. Due to the low signal-to-noise ratio, cryo-EM relies on averaging many images. However, a crucial question in the field of cryo-EM remains unanswered: how close can we get to the minimum number of particles required to reach a specific resolution in practice? The absence of an answer to this question has impeded progress in understanding sample behavior and the performance of sample preparation methods.

Affinity, value homophily, and opinion dynamics: The coevolution between affinity and opinion.

We propose two analytical relationships between affinity and opinion change. The first one focuses on value homophily, while the second one incorporates affinity in opinion dynamics. Three analytical test models are derived based on these relationships: the value homophily model, the temporal evolution of opinion summation, and the evolution of opinion difference between two individuals.

Bulk Operator Reconstruction in Topological Tensor Network and Generalized Free Fields.

In this paper, we study operator reconstruction in a class of holographic tensor networks describing renormalization group flows studied in arXiv:2210.12127. We study examples of 2D bulk holographic tensor networks constructed from Dijkgraaf-Witten theories and find that for both the Zn group and the S3 group, the number of bulk operators behaving like a generalized free field in the bulk scales as the order of the group.

Quantitative proteomics profiling reveals the inhibition of trastuzumab antitumor efficacy by phosphorylated RPS6 in gastric carcinoma.

Background: The anti-HER2 antibody trastuzumab is a standard treatment for gastric carcinoma with HER2 overexpression, but not all patients benefit from treatment with HER2-targeted therapies due to intrinsic and acquired resistance. Thus, more precise predictors for selecting patients to receive trastuzumab therapy are urgently needed.

Methods: We applied mass spectrometry-based proteomic analysis to 38 HER2-positive gastric tumor biopsies from 19 patients pretreated with trastuzumab (responders n = 10; nonresponders, n = 9) to identify factors that may influence innate sensitivity or resistance to trastuzumab therapy and validated the results in tumor cells and patient samples.

Non-line-of-sight imaging with arbitrary illumination and detection pattern.

Non-line-of-sight (NLOS) imaging aims at reconstructing targets obscured from the direct line of sight. Existing NLOS imaging algorithms require dense measurements at regular grid points in a large area of the relay surface, which severely hinders their availability to variable relay scenarios in practical applications such as robotic vision, autonomous driving, rescue operations and remote sensing. In this work, we propose a Bayesian framework for NLOS imaging without specific requirements on the spatial pattern of illumination and detection points.

Utilizing the codon adaptation index to evaluate the susceptibility to HIV-1 and SARS-CoV-2 related coronaviruses in possible target cells in humans.

Comprehensive identification of possible target cells for viruses is crucial for understanding the pathological mechanism of virosis. The susceptibility of cells to viruses depends on many factors. Besides the existence of receptors at the cell surface, effective expression of viral genes is also pivotal for viral infection.

Spontaneous symmetry breaking and ghost states supported by the fractional PT-symmetric saturable nonlinear Schrödinger equation.

We report a novel spontaneous symmetry breaking phenomenon and ghost states existed in the framework of the fractional nonlinear Schrödinger equation with focusing saturable nonlinearity and PT-symmetric potential. The continuous asymmetric soliton branch bifurcates from the fundamental symmetric one as the power exceeds some critical value. Intriguingly, the symmetry of fundamental solitons is broken into two branches of asymmetry solitons (alias ghost states) with complex conjugate propagation constants, which is solely in fractional media.

Path Topology in Molecular and Materials Sciences.

The structures of molecules and materials determine their functions. Understanding the structure and function relationship is the holy grail of molecular and materials sciences. However, the rational design of molecules and materials with desirable functions remains a grand challenge despite decades of efforts.

Generating Minimal Models of H1N1 NS1 Gene Sequences Using Alignment-Based and Alignment-Free Algorithms.

For virus classification and tracing, one idea is to generate minimal models from the gene sequences of each virus group for comparative analysis within and between classes, as well as classification and tracing of new sequences. The starting point of defining a minimal model for a group of gene sequences is to find their longest common sequence (LCS), but this is a non-deterministic polynomial-time hard (NP-hard) problem. Therefore, we applied some heuristic approaches of finding LCS, as well as some of the newer methods of treating gene sequences, including multiple sequence alignment (MSA) and k-mer natural vector (NV) encoding.

Persistent Path-Spectral (PPS) Based Machine Learning for Protein-Ligand Binding Affinity Prediction.

Molecular descriptors are essential to quantitative structure activity/property relationship (QSAR/QSPR) models and machine learning models. Here we propose persistent path-spectral (PPS), PPS-based molecular descriptors, and PPS-based machine learning model for the prediction of the protein-ligand binding affinity, for the first time. For the graph, simplicial complex, and hypergraph representation of molecular structures and interactions, the path-Laplacian can be constructed and the derived path-spectral naturally gives a quantitative description of molecules.

Assortative mating on blood type: Evidence from one million Chinese pregnancies.

Blood type is one of the most fundamental phenotypes in biological, medical, and psychological studies. Using a unique dataset of one million Chinese pregnancies, we find strong evidence from a group of statistical tests for assortative mating on blood type. After controlling for anthropometric and socioeconomic confounders, assortative mating remains robust.

In-depth investigation of the point mutation pattern of HIV-1.

Mutations may produce highly transmissible and damaging HIV variants, which increase the genetic diversity, and pose a challenge to develop vaccines. Therefore, it is of great significance to understand how mutations drive the virulence of HIV. Based on the 11897 reliable genomes of HIV-1 retrieved from HIV sequence Database, we analyze the 12 types of point mutation (A>C, A>G, A>T, C>A, C>G, C>T, G>A, G>C, G>T, T>A, T>C, T>G) from multiple statistical perspectives for the first time.