Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceptions of Risk for Dating Violence Among Rural Adolescent Males: An Interpretive Analysis

About one in eight U.S. high school students in Grades 9 to 12 report experiencing teen dating violence (TDV) in the form of physical, sexual, or psychological dating violence in the past year in person, on school grounds, and online. Compared with their urban counterparts, rural teens face nearly double the rate of physical dating abuse and an elevated risk of experiencing multiple forms of violence. Rural young males are exposed to regional masculinities and gender norms that may simultaneously promote female subordination (a prelude to dating violence) while impeding help-seeking intentions. We used an interpretive and dialectical approach grounded in Relational Dialectics Theory to explore how rural young males perceive and describe their own risk of experiencing and perpetrating dating violence and the factors contributing to their help-seeking intentions and behaviors. Data from three focus groups and individual interviews with 27 rural young males (ages 15–24) were collated. We identified two central dialectical themes described as (a) Social Tension Dialectics (subthemes include: Abusive vs. Unhealthy Relationships: A Dialectic of Language; #MeToo vs. #WeToo: A Dialectic of Victimhood; “It’s All Country Boys”: A Dialectic of Masculinity) and (b) Help-Seeking Dialectics demonstrating the dual roles Religion, School Guidance Counselors, Peer Mentors, and Social Cohesion play in promoting or preventing dating violence. Overall, we found dialectic tensions in rural youth risk perceptions about dating violence. These findings bear implications for advocates and practitioners working with rural youth in planning developmentally and culturally appropriate TDV prevention programs, offering policy and research-relevant insight.
Shepherding in a Self-gravitating Disk of Trans-Neptunian Objects

A relatively massive and moderately eccentric disk of trans-Neptunian objects (TNOs) can effectively counteract apse precession induced by the outer planets, and in the process shepherd highly eccentric members of its population into nearly stationary configurations that are antialigned with the disk itself. We were sufficiently intrigued by this remarkable feature to embark on an extensive exploration of the full spatial dynamics sustained by the combined action of giant planets and a massive trans-Neptunian debris disk. In the process, we identified ranges of disk mass, eccentricity, and precession rate that allow apse-clustered populations that faithfully reproduce key orbital properties of the much-discussed TNO population. The shepherding disk hypothesis is, to be sure, complementary to any potential ninth member of the solar system pantheon, and could obviate the need for it altogether. We discuss its essential ingredients in the context of solar system formation and evolution, and argue for their naturalness in view of the growing body of observational and theoretical knowledge about self-gravitating disks around massive bodies, extra-solar debris disks included.
Natural products from medicinal plants in Asia and the Pacific for RNA viruses: Hercules’ fifth labour

Abstract Context The emergence of zoonotic viruses in the last decades culminating with COVID-19 and challenges posed by the resistance of RNA viruses to antiviral drugs requires the development of new antiviral drugs. Objective This review identifies natural products isolated from Asian and Pacific medicinal plants with in vitro and in vivo antiviral activity towards RNA viruses and analyses their distribution, molecular weights, solubility and modes of action. Materials and methods All data in this review was compiled from Google Scholar, PubMed, Science Direct, Web of Science, ChemSpider, PubChem and library search from 1961 to 2022. Results Out of about 350 molecules identified, 43 phenolics, 31 alkaloids, and 28 terpenes were very strongly active against at least one type of RNA virus. These natural products are mainly planar and amphiphilic, with a molecular mass between 200 and 400 g/mol and target viral genome replication. Hydroxytyrosol, silvestrol, lycorine, tylophorine and 12-O-tetradecanoylphorbol 13-acetate with IC50 below 0.01 µg/mL and selectivity index (S.I.) above 100 have the potential to be used for the development of anti-RNA virus leads. Discussion and conclusions The medicinal plants of Asia and the Pacific are a rich source of natural products with the potential to be developed as lead for the treatment of RNA viral infections.
IQC‐synthesis with general dynamic multipliers

Analogously to the existing μ‐synthesis tools, we propose an alternative algorithm for the systematic design of robust controllers based on an iteration of standard nominal controller synthesis and integral quadratic constraint (IQC) analysis with general dynamic multipliers. The suggested algorithm enables us to perform robust controller synthesis for a significantly larger class of uncertainties if compared with the existing methods. Indeed, while the classical approaches are restricted to the use of real/complex time invariant or arbitrarily fast time‐varying parametric uncertainties, the IQC framework also offers, for example, the possibility to efficiently handle sector‐bounded and slope restricted nonlinearities or time‐varying parametric uncertainties and uncertain time‐varying time‐delays, both with bounds on the rate‐of‐variation. Secondly, in contrast to the classical approaches, the proposed techniques completely avoid gridding and curve‐fitting. We present new insights that allow us to reformulate the robust IQC analysis LMIs into a standard quadratic performance problem. This enables us to generate suitable initial conditions for each subsequent iteration step. Depending on the size of the problem, this can significantly speed up the synthesis process. The results are illustrated by means of two numerical examples. Copyright © 2013 John Wiley & Sons, Ltd.
Prospects for Measuring Abundances of >20 Elements with Low-resolution Stellar Spectra

Understanding the evolution of the Milky Way calls for the precise abundance determination of many elements in many stars. A common perception is that deriving more than a few elemental abundances ([Fe/H], [α/Fe], perhaps [C/H], [N/H]) requires medium-to-high spectral resolution, R ≳ 10,000, mostly to overcome the effects of line blending. In a recent work, we presented an efficient and practical way to model the full stellar spectrum, even when fitting a large number of stellar labels simultaneously. In this paper, we quantify to what precision the abundances of many different elements can be recovered, as a function of spectroscopic resolution and wavelength range. In the limit of perfect spectral models and spectral normalization, we show that the precision of elemental abundances is nearly independent of resolution, for a fixed exposure time and number of detector pixels; low-resolution spectra simply afford much higher S/N per pixel and generally larger wavelength range in a single setting. We also show that estimates of most stellar labels are not strongly correlated with one another once R ≳ 1000. Modest errors in the line-spread function, as well as small radial velocity errors, do not affect these conclusions, and data-driven models indicate that spectral (continuum) normalization can be achieved well enough in practice. These results, to be confirmed with an analysis of observed low-resolution data, open up new possibilities for the design of large spectroscopic stellar surveys and for the reanalysis of archival low-resolution data sets.
Forbush Decreases during the DeepMin and MiniMax of Solar Cycle 24

After a prolong and deep solar minimum at the end of solar cycle 23, the current cycle 24 is one of the lowest cycles. The two periods of deep minimum and mini-maximum of the cycle 24 are connected by a period of increasing solar activity. In this work, the Forbush decreases of cosmic ray intensity during the period from January 2008 to December 2014 are studied. A statistical analysis of 749 events using the IZMIRAN database of Forbush effects obtained by processing the data of the worldwide neutron monitor network using the global survey method is performed. A further study of the events that happened on the Sun and affected the interplanetary space, and finally provoked the decreases of the galactic cosmic rays near Earth is performed. A statistical analysis of the amplitude of the cosmic ray decreases with solar and geomagnetic parameters is carried out. The results will be useful for space weather studies and especially for Forbush decreases forecasting.
ReLMole: Molecular Representation Learning Based on Two-Level Graph Similarities

Molecular representation is a critical part of various prediction tasks for physicochemical properties of molecules and drug design. As graph notations are common in expressing the structural information of chemical compounds, graph neural networks (GNNs) have become the mainstream backbone model for learning molecular representation. However, the scarcity of task-specific labels in the biomedical domain limits the power of GNNs. Recently, self-supervised pretraining for GNNs has been leveraged to deal with this issue, while the existing pretraining methods are mainly designed for graph data in general domains without considering the specific data properties of molecules. In this paper, we propose a representation learning method for molecular graphs, called ReLMole, which is featured by a hierarchical graph modeling of molecules and a contrastive learning scheme based on two-level graph similarities. We assess the performance of ReLMole on two types of downstream tasks, namely, the prediction of molecular properties (MPs) and drug-drug interaction (DDIs). ReLMole achieves promising results for all the tasks. It outperforms the baseline models by over 2.6% on ROC-AUC averaged across six MP prediction tasks, and it improves the F1 value by 7-18% in DDI prediction for unseen drugs compared with other self-supervised models.
lncRNA Malat1 and miR-26 cooperate in the regulation of neuronal progenitor cell proliferation and differentiation

Neurogenesis is a finely tuned process, which depends on the balanced execution of expression programs that regulate cellular differentiation and proliferation. Different molecular players ranging from transcription factors to chromatin modulators control these programs. Adding to the complexity, noncoding (nc)RNAs also take part in this process. Here we analyzed the function of the long noncoding (lnc)RNA Malat1 during neural embryonic stem cell (ESC) differentiation. We find that deletion of Malat1 leads to inhibition of proliferation of neural progenitor cells (NPCs). Interestingly, this coincides with an increase in the expression of miR-26 family members miR-26a and miR-26b in differentiating ESCs. Inactivation of miR-26a/b rescues the proliferative phenotype of Malat1 knockout (KO) cells and leads to accelerated neuronal differentiation of compound Malat1KO/mir-26KO ESCs. Together our work identifies a so far unknown interaction between Malat1 and miR-26 in the regulation of NPC proliferation and neuronal differentiation.
NeX360: Real-Time All-Around View Synthesis With Neural Basis Expansion

We present NeX, a new approach to novel view synthesis based on enhancements of multiplane images (MPI) that can reproduce view-dependent effects in real time. Unlike traditional MPI, our technique parameterizes each pixel as a linear combination of spherical basis functions learned from a neural network to model view-dependent effects and uses a hybrid implicit-explicit modeling strategy to improve fine detail. Moreover, we also present an extension to NeX, which leverages <italic>knowledge distillation</italic> to train multiple MPIs for unbounded 360<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mo>∘</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="phongthawee-ieq1-3217957.gif"/></alternatives></inline-formula> scenes. Our method is evaluated on several benchmark datasets: NeRF-Synthetic dataset, Light Field dataset, Real Forward-Facing dataset, Space dataset, as well as <italic>Shiny</italic>, our new dataset that contains significantly more challenging view-dependent effects, such as the rainbow reflections on the CD. Our method outperforms other real-time rendering approaches on PSNR, SSIM, and LPIPS and can render <italic>unbounded</italic> 360<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math><alternatives><mml:math><mml:msup><mml:mrow/><mml:mo>∘</mml:mo></mml:msup></mml:math><inline-graphic xlink:href="phongthawee-ieq2-3217957.gif"/></alternatives></inline-formula> scenes in real time.
The Systematic Variation of Optical Properties of Alkali Halides: an Ab Initio Study

In this paper we study a correlation between the optical properties, electronic structure and anion-cation electronegativity difierence in three groups of alkali halides MX (M = Li, Na, K; X = F, Cl, Br, I). The electronic structure was calculated by flrst-principle, density-functional theory based full-potential linear augmented plane wave method. Then the complex dielectric function was computed, allowing determination of the optical absorption spectra in all compounds, up to incident radiation energy of 40 eV. The results were interpreted in terms of calculated band structures and correlated with the electronegativity difierence in each compound, which was estimated on the basis of topological theory of Bader. PACS numbers:
Symplectic and Hamiltonian Deformations of Gabor Frames

We study symplectic deformations of Gabor frames using the covariance properties of the Heisenberg operators. This allows us to recover in a very simple way known results. We thereafter propose a general deformation scheme by Hamiltonian isotopies, which are paths of Hamiltonian flows. We define and study in detail a weak notion of Hamiltonian deformations, using ideas from semiclassical analysis due to Heller and Hagedorn. This method can be easily implemented using symplectic integrators.
Palmitate impairs circadian transcriptomics in muscle cells through histone modification of enhancers

The disruption of circadian rhythms because of lipid overload may lead to epigenomic changes that influence metabolism. Thus, a dietary or therapeutic modulation of lipid levels, a cornerstone in the treatment of metabolic disorders, may prevent circadian misalignment in peripheral tissues. Obesity and elevated circulating lipids may impair metabolism by disrupting the molecular circadian clock. We tested the hypothesis that lipid overload may interact with the circadian clock and alter the rhythmicity of gene expression through epigenomic mechanisms in skeletal muscle. Palmitate reprogrammed the circadian transcriptome in myotubes without altering the rhythmic mRNA expression of core clock genes. Genes with enhanced cycling in response to palmitate were associated with post-translational modification of histones. The cycling of histone 3 lysine 27 acetylation (H3K27ac), a marker of active gene enhancers, was modified by palmitate treatment. Chromatin immunoprecipitation and sequencing confirmed that palmitate exposure altered the cycling of DNA regions associated with H3K27ac. The overlap between mRNA and DNA regions associated with H3K27ac and the pharmacological inhibition of histone acetyltransferases revealed novel cycling genes associated with lipid exposure of primary human myotubes. Palmitate exposure disrupts transcriptomic rhythmicity and modifies enhancers through changes in histone H3K27 acetylation in a circadian manner. Thus, histone acetylation is responsive to lipid overload and may redirect the circadian chromatin landscape, leading to the reprogramming of circadian genes and pathways involved in lipid biosynthesis in skeletal muscle.
Targeted co‐delivery of paclitaxel and anti P‐gp shRNA by low molecular weight PEI decorated with L‐3,4‐dihydroxyphenylalanine

Co‐delivery of small chemotherapeutic molecules and nucleic acid materials via targeted carriers has attracted great attention for treatment of resistant tumors and reducing adverse effects. In this study, a targeted carrier for co‐delivery was prepared based on low‐molecular weight polyethylenimine (LMW PEI). Paclitaxel (PTX) was covalently conjugated onto PEI via a succinate linker. The PEI conjugate was decorated with L‐DOPA in order to target large neutral amino acid transporter‐1 (LAT‐1) that is over‐expressed on various cancer cells. This PEI conjugate was complexed with human ABCB1 shRNA plasmid to down‐regulate the expression of P‐glycoprotein, as one of the major efflux pumps inducing resistance against chemotherapeutics. The formation of PEI conjugate enhanced the solubility of PTX and resulted in the condensation and protection of plasmid DNA in nanosized polyplexes. The results of targeted delivery into the cells demonstrated that PEI conjugate transferred the payloads to the cells over‐expressing LAT‐1 transporter, while the biological effects on the cells lacking the transporter was negligible. Also, shRNA‐mediated down‐regulation of P‐gp led to the increase of toxic effects on the cells over‐expressing P‐gp. This study suggests a promising approach for co‐delivery of small molecules and nucleic acid materials in a targeted manner for cancer therapy.
Predicting Bone Health Using Machine Learning in Patients undergoing Spinal Reconstruction Surgery

Study Design. Retrospective study of data collected prospectively. Objective. The goal of this study is to create a predictive model of preoperative bone health status in adult patients undergoing adult spinal reconstructive (ASR) surgery using machine learning (ML). Summary of Background Data. Despite understanding that bone health impacts spine surgery outcomes, spine surgeons lack the tools to risk stratify patients preoperatively to determine who should undergo bone health screening. An ML approach mines patterns in data to determine the risk for poor bone health in ASR patients. Materials and Methods. Two hundred and eleven subjects over the age of 30 with dual energy X-ray absorptiometry scans, who underwent spinal reconstructive surgery were reviewed. Data was collected by manual and automated collection from the electronic health records. The Weka software was used to develop predictive models for multiclass classification of healthy, osteopenia, and osteoporosis (OPO) bone status. Bone status was labeled according to the World Health Organization (WHO) criteria using dual energy X-ray absorptiometry T scores. The accuracy, sensitivity, specificity, and area under the receiver operating curve (AUC) were calculated. The model was evaluated on a test set of unseen data for generalizability. Results. The prevalence of OPO was 23.22% and osteopenia was 52.61%. The random forest model achieved optimal performance with an average sensitivity of 0.81, specificity of 0.95, and AUC of 0.96 on the training set. The model yielded an averaged sensitivity of 0.64, specificity of 0.78, and AUC of 0.69 on the test set. The model was best at predicting OPO in patients. Numerous patient features exhibited predictive value, such as body mass index, insurance type, serum sodium level, serum creatinine level, history of bariatric surgery, and the use of medications such as selective serotonin reuptake inhibitors. Conclusion. Predicting bone health status in ASR patients is possible with an ML approach. Additionally, data mining using ML can find unrecognized risk factors for bone health in ASR surgery patients.
A novel domain‐duplicated SlitFAR3 gene involved in sex pheromone biosynthesis in Spodoptera litura

Fatty acyl reductases (FARs) are key enzymes that participate in sex pheromone biosynthesis by reducing fatty acids to fatty alcohols. Lepidoptera typically harbor numerous FAR gene family members. Although FAR genes are involved in the biosynthesis of sex pheromones in moths, the key FAR gene of Spodoptera litura remains unclear. In this work, we predicted 30 FAR genes from the S. litura genome and identified a domain duplication within gene SlitFAR3, which exhibited high and preferential expression in the sexually mature female pheromone glands (PGs) and a rhythmic expression pattern during the scotophase of sex pheromone production. The molecular docking of SlitFAR3, as predicted using a 3D model, revealed a co‐factor NADPH binding cavity and 2 substrate binding cavities. Functional expression in yeast cells combined with comprehensive gas chromatography indicated that the SlitFAR3 gene could produce fatty alcohol products. This study is the first to focus on the special phenomenon of FAR domain duplication, which will advance our understanding of biosynthesis‐related genes from the perspective of evolutionary biology.
Prosodic Analysis and Burmese Syllable-Initial Features

0. Main characteristics of prosodic analysis 1. Phonemic analysis and the plurality of phonemic forms 2.0. Prosodic analysis and the unity of its formulae 3. Prosodic analysis and variant syllable-initial features 3.1. Intraverbal junction, stressed 3.2. Intraverbal junction, non-stressed 3.3. Interverbal junction 4.1. Summary of exponents of v, h, and h 4.2. Additional exponency for verb lexical items 5. The aspiration system and the grammatical classification of lexical items
Activity in a prefrontal-periaqueductal gray circuit overcomes behavioral and endocrine features of the passive coping stress response

Significance The question of how the brain links behavioral and biological features of defensive stress responses has remained elusive. Here, we show that active stress-coping behavior in rats is associated with activity increases along a caudal medial prefrontal cortex–midbrain periaqueductal gray circuit. Optogenetic manipulations of this pathway bidirectionally modulated active coping behavior. However, under more aversive conditions that provoked behavioral passivity and exaggerated stress-hormone responses, excitation of this same pathway significantly reduced each of these response features. These results highlight a neural circuit that may redirect multiple aspects of the organism’s defensive repertoire away from passive coping and may be of importance for understanding how activated neural systems promote stress resilience.
Antibody therapeutics for epithelial ovarian cancer

ABSTRACT Introduction High-grade serous ovarian carcinoma (HGSC) is an aggressive subtype of epithelial ovarian carcinoma (EOC) and remains the most lethal gynecologic cancer. A lack of effective and tolerable therapeutic options and nonspecific symptoms at presentation with advanced stage of disease are among the challenges in the management of the disease. Areas covered An overview of ovarian cancer, followed by a discussion of the current therapeutic regimes and challenges that arise during and after the treatment of EOC. We discuss different formats of antibody therapeutics and their usage in targeting validated targets implicated in ovarian cancer, as well as three emerging novel proteins as examples recently implicated in their contribution to adaptive resistance in ovarian cancer. Expert opinion Antibody therapeutics allow for a unique and effective way to target proteins implicated in cancer and other diseases, and have the potential to radically change the outcomes of patients suffering from ovarian cancer. The vast array of targets that have been implicated in ovarian cancer and yet the lack of effective therapeutic options for patients further stresses the importance of discovering novel proteins that can be targeted, as well as predictive biomarkers that can inform the stratification of patients into treatment-specific populations.