Miracle-dz/UniFAR-FTUs huggingface dataset:
HOW COMPLETE ARE ASTROPHYSICAL CATALOGS FOR THE MILLIMETER AND SUBMILLIMETER SPECTRAL REGION?

With the growth in sensitivity and angular resolution of millimeter and submillimeter telescopes, the number of unidentified molecular spectral lines in surveys of the interstellar medium has grown rapidly. While some of these unidentified lines are due to as yet unidentified astrophysical species, it is the general consensus that most are due to lines from a limited number of well-known interstellar species, the interstellar weeds. These unidentified lines do not appear in astrophysical line catalogs, which are based on quantum mechanical models and are incomplete primarily because of the difficulty of performing the usual bootstrap assignment and analysis process in their often highly perturbed low-lying vibrational states. To address this problem, we have proposed and demonstrated an alternative catalog approach that is based on the analysis of intensity-calibrated spectra taken over a range of temperatures in the laboratory. These analyses also make it possible to quantitatively address the astrophysical completeness of existing catalogs. In this Letter, we use extensive new experimental data in the 210–270 GHz window to address this question for eight molecules that are considered to be the leading candidates for astronomical weeds—methyl formate, methanol, dimethyl ether, acetaldehyde, sulfur dioxide, methyl cyanide, vinyl cyanide, and ethyl cyanide. Additionally, for each of the eight molecules, we use these results and knowledge of the molecular vibrational/torsional energy levels to predict completeness as a function of astronomical source temperature.
3D microscopy in industrial measurements

Quality control is essential to ensure the performance and yield of microdevices in industrial processing and manufacturing. In particular, 3D microscopy can be considered as a separate branch of microscopic instruments and plays a pivotal role in monitoring processing quality. For industrial measurements, 3D microscopy is mainly used for both the inspection of critical dimensions to ensure the design performance and detection of defects for improving the yield of microdevices. However, with the progress of advanced manufacturing technology and the increasing demand for high‐performance microdevices, 3D microscopy has ushered in new challenges and development opportunities, such as breakthroughs in diffraction limit, 3D characterisation and calibrations of critical dimensions, high‐precision detection and physical property determination of defects, and application of artificial intelligence. In this review, we provide a comprehensive survey about the state of the art and challenges in 3D microscopy for industrial measurements, and provide development ideas for future research. By describing techniques and methods with their advantages and limitations, we provide guidance to researchers and developers about the most suitable technique available for their intended industrial measurements.
Would you like fries with that? Investigating fast‐food outlet availability near schools in Perth, Western Australia

Abstract Issue addressed Locating fast‐food outlets near schools is a potential public health risk to schoolchildren, given the easy access and repeated exposure to energy‐dense, nutrient‐poor foods they provide. Fast‐food outlet availability near schools has not been previously investigated in Perth, Western Australia. This study aimed to quantify fast‐food outlet availability near Perth schools and determine whether differences in area‐level disadvantage and school type exist. Methods Fast‐food outlet locations were sourced from Perth Local Governments in 2018/2019. All Perth Primary (n = 454), Secondary (n = 107) and K‐12 (n = 94) schools were assigned an area‐level disadvantage decile ranking based on the Australian Bureau of Statistics Socio‐Economic Index for Areas (SEIFA). Regression models assessed whether fast‐food outlet availability within 400 m, 800 m and 1 km of schools differed by school type (ie, Primary/Secondary/K‐12) or SEIFA. Results Secondary schools were significantly more likely than Primary and K‐12 schools to have a higher presence and density of fast‐food outlets and the “Top 4” fast‐food outlet chains (McDonalds, Hungry Jacks, KFC and Red Rooster) nearby. Schools located in low socio‐economic status (SES) areas had a significantly higher density of fast‐food outlets within 400 m, and “Top 4” fast‐food outlet chains within 400 m and 1 km, than schools located in high SES area. Conclusions Perth schools are surrounded by fast‐food outlets with densities significantly higher around secondary schools and schools located in lower SES areas. So what? Policies and regulations aimed at reducing fast‐food outlets near schools is an essential strategy to improve dietary intakes and reduce obesity in schoolchildren.
A Special Case of Variational Formulation for Two-Point Boundary Value Problem in L2(Ω)

We consider the nonlinear boundary value problems for elliptic partial differential equations and using a maximum principle for this problem we show uniqueness and continuous dependence on data. We use the strong version of the maximum principle to prove that all solutions of two-point BVP are positives and we also show a numerical example by applying finite difference method for a two-point BVP in one dimension based on discrete version of the maximum principle.
Hierarchical regression with misaligned spatial data: relating ambient ozone and pediatric asthma ER visits in Atlanta

Recent work by the authors enabled a hierarchical modeling solution to the general change of support problem (COSP), where they seek to make inferences about the values of a variable at either points or regions different from those at which it has been observed. The approach presumes an underlying continuous stationary spatial process X (s) for locations s ∈ D, a region of interest. It is straightforwardly extended to the spatio‐temporal setting by assuming a space–time separable covariance function for the X (s, t) process, t ∈ T and again s ∈ D. In this article they take up the associated misaligned regression problem, where, for example, the explanatory variable is envisioned from the X (s, t) process, while the response is available only as areal summaries over a particular grid at particular times. They illustrate using a dataset relating several air quality indicators (ozone, particulate matter, nitrogen oxides, etc.) and a range of sociodemographic variables (age, gender, race, and a socioeconomic status surrogate) to the response, pediatric emergency room (ER) visit counts for asthma in Atlanta, Georgia. Here the air quality data is collected at fixed monitoring stations (point locations) while the sociodemographic covariates and response variable is collected by zip code (areal summaries). In fact, the air quality data are available as daily averages at each monitoring station, and the response is available as daily counts of visits in each zip code. As is now common in hierarchical Bayesian spatial applications, computing is implemented via a carefully tailored Metropolis–Hastings algorithm, with map summaries created using a geographic information system (GIS). Like many recent investigations of the ozone–asthma link, our results suggest a small positive association, though our data can permit this conclusion only for those children living in the city of Atlanta who use the ER to manage their asthma. Copyright © 2003 John Wiley & Sons, Ltd.
3D electrostatic field analysis of periodic two-dimensional SAW transducers with closed-form formulae

A 3-D field analysis method is developed for the analysis of the 2-D charge distribution in surface acoustic wave (SAW) transducers. The method employs a periodic Green's function constructed by superposition of the potential responses of a set of single point sources. A modified inverse-capacitance matrix that describes the whole structure has been established. Discretization has to be performed only in the main period. To obtain a prescribed accuracy, generally only a few periods at the left and at the right side with respect to the main cell have to be included in the analysis. Computational results for interdigital transducer (IDT) structures or YZ-LiNbO/sub 3/ are presented. The influence of bus-bars, floating fingers, and the aperture on the charge distribution is demonstrated. <<ETX>>
Machine learning analysis of the T cell receptor repertoire identifies sequence features that predict self-reactivity

The T cell receptor (TCR) determines the specificity and affinity for both foreign and self-peptides presented by MHC. It is established that self-pMHC reactivity impacts T cell function, but it has been challenging to identify TCR sequence features that predict T cell fate. To discern patterns distinguishing TCRs from naïve CD4+ T cells with low versus high self-pMHC reactivity, we used data from 42 mice to train a machine learning (ML) algorithm that predicts self-reactivity directly from TCRβ sequences. This approach revealed that n-nucleotide additions and acidic amino acids weaken self-reactivity. We tested our ML predictions of TCRβ sequence self-reactivity using retrogenic mice. Extrapolating our analyses to independent datasets, we found high predicted self-reactivity for regulatory CD4+ T cells and low predicted self-reactivity for T cells responding to chronic infection. Our analyses suggest a potential trade-off between repertoire diversity and self-reactivity intrinsic to the architecture of a TCR repertoire.
CYRI-B mediated macropinocytosis drives metastasis via lysophosphatidic acid receptor uptake

Pancreatic ductal adenocarcinoma carries a dismal prognosis, with high rates of metastasis and few treatment options. Hyperactivation of KRAS in almost all tumours drives RAC1 activation, conferring enhanced migratory and proliferative capacity as well as macropinocytosis. Macropinocytosis is well understood as a nutrient scavenging mechanism, but little is known about its functions in trafficking of signaling receptors. We find that CYRI-B is highly expressed in pancreatic tumours in a mouse model of KRAS and p53- driven pancreatic cancer. Deletion of CYRI-B accelerates tumourigenesis, leading to enhanced ERK and JNK-induced proliferation in precancerous lesions, indicating a role as a buffer of RAC1 hyperactivation in early stages. However, as disease progresses, loss of CYRI-B inhibits metastasis. CYRI-B depleted tumour cells show reduced chemotactic responses to lysophosphatidic acid, a major driver of tumour spread, due to impaired macropinocytic uptake of LPAR1 receptor. Overall, we implicate CYRI-B as a mediator of growth and signaling in pancreatic cancer, providing new insights into pathways controlling metastasis.
Temporal characteristics of gamma rhythm constrain properties of noise in an inhibition-stabilized network model

Gamma rhythm refers to oscillatory neural activity between 30-80 Hz, often induced in visual cortex by presentation of stimuli such as iso-luminant hues or gratings. Further, the power and peak frequency of gamma depend on the properties of the stimulus such as size and contrast. Gamma also has a typical arch shape, with a narrow trough and a broad peak, which can be replicated by a self-oscillating Wilson-Cowan (WC) model operating in an appropriate regime. However, oscillations in this model are infinitely long, unlike physiological gamma that occurs in short bursts. Further, unlike the model, gamma is faster after stimulus onset and slows down over time. Here, we first characterized gamma burst duration in LFP data recorded from two monkeys while they viewed full screen iso-luminant hues. We then added different types of noise in the inputs to the WC model and tested how that affected duration and temporal dynamics of gamma. While the model failed with the often-used Poisson noise, Ornstein-Uhlenbeck (OU) noise applied to both the excitatory and inhibitory populations in the WC model replicated the duration and slowing of gamma, and also replicated the shape and stimulus dependencies. Therefore, temporal dynamics of gamma oscillations put constraints on the type and properties of underlying neural noise.
The evolution and structure of snake venom phosphodiesterase (svPDE) highlight its importance in venom actions

For decades, studies of snake venoms focused on the venom-ome-specific toxins (VSTs). VSTs are dominant soluble proteins believed to contribute to the main venomous effects and emerged into gene clusters for fast adaptation and diversification of snake venoms. However, the conserved minor venom components, such as snake venom phosphodiesterase (svPDE), remain largely unexplored. Here, we focus on svPDE by genomic and transcriptomic analysis across snake clades and demonstrate that soluble svPDE is co-opted from the ancestral membrane-attached ENPP3 (ectonucleotide pyrophosphatase/phosphodiesterase 3) gene by replacing the original 5’ exon with the exon encoding a signal peptide. Notably, the exons, promoters and transcription/translation starts have been replaced multiple times during snake evolution, suggesting the evolutionary necessity of svPDE. The structural and biochemical analyses also show that svPDE shares the similar functions with ENPP family, suggesting its perturbation to the purinergic signaling and insulin transduction in venomous effects. Significance Statement We provided a case of the evolutionary co-option strategy in which the secretory svPDE, one of the minor venom components, is generated from the ancestral membrane-anchored ENPP3 gene by using an alternative 5’ exon. The first exon of the svPDE transcript encodes a signal peptide instead of the transmembrane domain of the ENPP3. Multiple replacement events of genomic elements during snake evolution maintain the expression of the svPDE transcripts, suggesting the crucial function of svPDE. Also, the structures and biochemical analyses indicate that svPDE reuse the original functions of ENPP3 in the bitten tissues and may interfere with normal cell signaling. Together, our study reveals the evolution of svPDE and suggests the importance of minor venom components.
ALMT-independent guard cell R-type anion currents

Plant transpiration is controlled by stomata, with S- and R-type anion channels playing key roles in guard cell action. Arabidopsis mutants lacking the ALMT12/QUAC1 R-type anion channel function in guard cells show only a partial reduction in R-type channel currents. To identify the molecular nature of the remaining R-type anion channel population, patch clamp studies were performed. This R-type current fraction in the almt12 mutant exhibited the same voltage dependence, susceptibility to ATP block and lacked a chloride permeability as the wildtype. Therefore, we asked whether the R-type anion currents in the ALMT12/QUAC1-free mutant are caused by additional ALMT isoforms. In wildtype guard cells ALMT12, ALMT13 and ALMT14 transcripts were detected, whereas only ALMT13 was found expressed in the almt12 mutant. Substantial R-type anion currents still remained active in the almt12/13 and almt12/14 double mutants as well as the almt12/13/14 triple mutant. This situation, supported by transpiration measurements, suggests that, with the exception of ALMT12, channel species other than ALMTs carry the guard cell R-type anion currents.
Fault Detection and Diagnosis in Industrial Systems

algorithm. The author shows that, as a class of nonlinear mappings between vector spaces, neural networks (including radial basis functions) can indeed be a useful method of dimension reduction. Chapter 9 is, as the author claims, “the basic goal of the book, that is the development of methods for constructing empirical dimensionality-reducing mappings of data” (p. 299). The so-called WRN (Whitney reduction network), based on Whitney’s embedding theorem as a global approach, is covered in detail. However, in these global approaches, as the author notes, “when the domain dimension is large, are far less practical. ” The local approach is the Taylor expansion of the nonlinear mapping. Thus the linear term of the Taylor expansion can be applied by the KL procedure; a local KL algorithm is also given (p. 326). This book provides a valuable summary of data reduction. Of course, mathematical theory is an important part of the foundation for data analysis. But due to the limitation of the book’s purely mathematical viewpoint, only the least squares–type criteria are discussed for determining an optimal basis. Many other approaches, including maximum likelihood, are not mentioned at all. This view limits the book’s applicability.
IMPASTO: Multiplexed cyclic imaging without signal removal via self-supervised neural unmixing

Spatially resolved proteomics requires a highly multiplexed imaging modality. Cyclic imaging techniques, which repeat staining, imaging, and signal erasure, have been adopted for this purpose. However, due to tissue distortion, it is challenging to obtain high fluorescent signal intensities and complete signal erasure in thick tissue with cyclic imaging techniques. Here, we propose an “erasureless” cyclic imaging method named IMPASTO. In IMPASTO, specimens are iteratively stained and imaged without signal erasure. Then, images from two consecutive rounds are unmixed to retrieve the images of single proteins through self-supervised machine learning without any prior training. Using IMPASTO, we demonstrate 30-plex imaging from brain slices in 10 rounds, and when used in combination with spectral unmixing, in five rounds. We show that IMPASTO causes negligible tissue distortion and demonstrate 3D multiplexed imaging of brain slices. Further, we show that IMPASTO can shorten the signal removal processes of existing cyclic imaging techniques.
Tissue microenvironment dictates the state of human induced pluripotent stem cell-derived endothelial cells of distinct developmental origin in 3D cardiac microtissues

Each tissue and organ in the body has its own type of vasculature. Here we demonstrate that organotypic vasculature for the heart can be recreated in a three-dimensional cardiac microtissue (MT) model composed of human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CMs), cardiac fibroblasts (CFs) and endothelial cells (ECs). ECs in cardiac MTs upregulated expression of markers enriched in human intramyocardial ECs (iECs), such as CD36, CLDN5, APLNR, NOTCH4, IGFBP3, ARHGAP18, which were previously identified in the single-cell RNA-seq dataset from the human fetal heart (6.5-7 weeks post coitum). We further show that the local microenvironment largely dictates the organ-specific identity of hiPSC-derived ECs: we compared ECs of different developmental origins derived from two distinct mesoderm subtypes (cardiac and paraxial mesoderm) and found that independent of whether the ECs were cardiac or paraxial mesoderm derived, they acquired similar identities upon integration into cardiac microtissues. This was confirmed by single-cell RNA-seq. Overall, the results indicated that whilst the initial gene profile of ECs was dictated by developmental origin, this could be modified by the local tissue environment such that the original identity was lost and the organotypic identity acquired through local environmental signals. This developmental “plasticity” in ECs has implications for multiple pathological and disease states.
Database of recurrent mutations (DORM), a web tool to browse recurrent mutations in cancers

Advances in sequencing technologies have facilitated the genetic characterization of large numbers of clinical cancer samples, leading to accumulation of extensive amounts of data. While potentially very useful for directing research and for clinical decision making, the increasing quantity of data generates challenges in its optimal management, and translation to informing clinical and research questions. Here, we present Database Of Recurrent Mutations (DORM), a database listing recurrent mutations (tissue-agnostic population frequency > 1) identified from cancer samples analyzed with whole genome or whole exome sequencing. The DORM database is a fast and feature-rich database supporting searching for several proteins, amino acid substitutions as well as queries using regular expressions.
MERISTEM-DEFECTIVE regulates the balance between stemness and differentiation in the root meristem through RNA splicing control

Plants respond to environmental stresses through controlled stem cell maintenance and meristem activity. One level of transcriptional control is RNA alternative splicing. However the mechanistic link between stress, meristem function and RNA splicing is poorly understood. The MERISTEM-DEFECTIVE (MDF)/DEFECTIVELY ORGANIZED TRIBUTARIES (DOT2) gene of Arabidopsis encodes a SR-related family protein, required for meristem function and leaf vascularization, and is the likely orthologue of the human SART1 and yeast snu66 splicing factors. MDF is required for the correct splicing and expression of key transcripts associated with root meristem function. We identified RSZ33 and ACC1, both known to regulate cell patterning, as splicing targets required for MDF function in the meristem. MDF expression is modulated by osmotic and cold stress, associated with differential splicing and specific isoform accumulation and shuttling between nucleus and cytosol, and acts in part via a splicing target SR34. We propose a model in which MDF controls splicing in the root meristem to promote stemness and repress stress response and cell differentiation pathways. Summary statement The protein MERISTEM-DEFECTIVE regulates Arabidopsis meristem function through its role as a splicing factor, mediated through splicing targets RSZ33, ACC1 and SR34.
Instability of the finite-difference split-step method on the background of a soliton of the nonlinear Schrodinger equation

We consider the implementation of the split-step method where the linear part of the nonlinear Schr\"odinger equation is solved using a finite-difference discretization of the spatial derivative. The von Neumann analysis predicts that this method is unconditionally stable on the background of a constant-amplitude plane wave. However, simulations show that the method can become unstable on the background of a soliton. We present an analysis explaining this instability. Both this analysis and the instability itself are substantially different from those of the Fourier split-step method, which computes the spatial derivative by spectral discretization. We also found that the modes responsible for the numerical instability are supported by the sides of the soliton, in contrast to unstable modes of linearized nonlinear wave equations, which (the modes) are supported by the soliton's core.