Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment Strategies for Data-Limited Chinook Salmon Stocks of Western Alaska

ii Acknowledgements . iii List of Figures . vi List of Tables . ix Chapter 1: Thesis Introduction.1 Chapter 2: From Sequential to Integrated Bayesian Analyses: Exploring the Continuum with a Pacific Salmon Spawner-Recruit Model . 16 Abstract . 16 Introduction . 17 Methods.20 Results . 35 Discussion . 39 References . 45 Figures.49 Tables . 59 Appendix I: Integrated Model Code . 62
Railways' stability observed in Campania (Italy) by InSAR data

Abstract Campania region is characterized by intense urbanization, active volcanoes, subsidence, and landslides; therefore, the stability of public transportation structures is highly concerned. We have applied DInSAR technique to a stack of 25 X-band radar images of Cosmo-SkyMed (CSK) satellites collected over an area in Campania, in order to monitor the railways' stability. The study area was already investigated with older, low-resolution sensors like ERS1/2 and ENVISAT-ASAR before, but the number of obtained persistent scatterers (PSs) was too limited to get useful results. Here, for the first time we apply CSK high resolution imagery to this study area, so obtaining a number of PSs sufficient to detect possible deformations on the railways. We focused on a bridge at Triflisco, over the Volturno River. Our results demonstrate a stable condition. Comparison with the local thermal data shows that the main deformation on the bridge is limited to periodical deformation of the steel structure.
Mass extinctions over the last 500 myr: an astronomical cause?

A Fourier analysis of the magnitudes and timing of the Phanerozoic mass extinctions (MEs) demonstrates that many of the periodicities claimed in other analyses are not statistically significant. Moreover we show that the periodicities associated with oscillations of the Solar System about the galactic plane are too irregular to give narrow peaks in the Fourier periodograms. This leads us to conclude that, apart from possibly a small number of major events, astronomical causes for MEs can largely be ruled out.
Viscoelastic Characterization of Phantoms for Ultrasound Elastography Created Using Low- and High-Viscosity Poly(vinyl alcohol) with Ethylene Glycol as the Cryoprotectant

Ultrasound elastography enables noninvasive characterization of the tissue mechanical properties. Phantoms are widely used in ultrasound elastography for developing, testing, and validating imaging techniques. Creating phantoms with a range of viscoelastic properties relevant to human organs and pathological conditions remains an active area of research. Poly(vinyl alcohol) (PVA) cryogel phantoms offer a long shelf life, robustness, and convenient handling and storage. The goal of this study was to develop tunable phantoms using PVA with a clinically relevant range of viscoelastic properties. We combined low- and high-viscosity PVA to tune the viscoelastic properties of the phantom. Further, phantoms were created with an ethylene glycol-based cryoprotectant to determine whether it reduces the variability in the viscoelastic properties. Scanning electron microscopy (SEM) was performed to evaluate the differences in microstructure between phantoms. The density, longitudinal sound speed, and acoustic attenuation spectra (5–20 MHz) of the phantoms were measured. The phantoms were characterized using a shear wave viscoelastography approach assuming the Kelvin–Voigt model. Microstructural differences were revealed by SEM between phantoms with and without a cryoprotectant and with different PVA mixtures. The longitudinal sound speed and attenuation power-law fit exponent of the phantoms were within the clinical range (1510–1571 m/s and 1.23–1.38, respectively). The measured shear modulus (G) ranged from 3.3 to 17.7 kPa, and the viscosity (η) ranged from 2.6 to 7.3 Pa·s. The phantoms with the cryoprotectant were more homogeneous and had lower shear modulus and viscosity (G = 2.17 ± 0.2 kPa; η = 2.0 ± 0.05 Pa·s) than those without a cryoprotectant (G = 3.93 ± 0.7 kPa; η = 2.6 ± 0.14 Pa·s). Notably, phantoms with relatively constant viscosities and varying shear moduli were achieved by this method. These findings advance the development of well-characterized viscoelastic phantoms for use in elastography.
Extending DeepTrio for sensitive detection of complex de novo mutation patterns

Abstract De novo mutations (DNMs), and among them clustered DNMs within 20 bp of each other (cDNMs) are known to be a potential cause of genetic disorders. However, identifying DNM in whole genome sequencing (WGS) data is a process that often suffers from low specificity. We propose a deep learning framework for DNM and cDNM detection in WGS data based on Google's DeepTrio software for variant calling, which considers regions of 110 bp up- and downstream from possible variants to take information from the surrounding region into account. We trained a model each for the DNM and cDNM detection tasks and tested it on data generated on the HiSeq and NovaSeq platforms. In total, the model was trained on 82 WGS trios generated on the NovaSeq and 16 on the HiSeq. For the DNM detection task, our model achieves a sensitivity of 95.7% and a precision of 89.6%. The extended model adds confidence information for cDNMs, in addition to standard variant classes and DNMs. While this causes a slight drop in DNM sensitivity (91.96%) and precision (90.5%), on HG002 cDNMs can be isolated from other variant classes in all cases (5 out of 5) with a precision of 76.9%. Since the model emits confidence probabilities for each variant class, it is possible to fine-tune cutoff thresholds to allow users to select a desired trade-off between sensitivity and specificity. These results show that DeepTrio can be retrained to identify complex mutational signatures with only little modification effort.
Assessment and Removal of Emerging Water Contaminants

This review summarizes recent literature related to analytical method development, assessment, and removal of emerging contaminants in natural water resources and drinking water. This review mainly focuses on the following four groups of chemical contaminants: pharmaceuticals and personal care products (PPCPs); major disinfection byproducts, cyanotoxins, and pesticides and herbicides. Because of the large volume publications on various emerging environmental contaminants, articles relating to specific water treatment, health risk assessments and ecological impact are not included in this review. In addition, literature pertinent to emerging contaminants in air and other environments are also not covered in this review.
TDSTF: Transformer-based Diffusion probabilistic model for Sparse Time series Forecasting

—Time series probabilistic forecasting with multi-dimensional and sporadic data (known as sparse data) has potential to implement monitoring kinds of physiological indices of patients in Intensive Care Unit (ICU). In this paper, we propose Transformer-based Diffusion probabilistic model for Sparse Time series Forecasting (TDSTF), a new model to predict distribution of highly sparse time series. There are many works that focus on probabilistic forecasting, but few of them avoid noise that come from extreme sparsity of data. We take advantage of Triplet, a data organization that represents sparse time series in a much efﬁcient way, for our model to bypass data redundancy in the traditional matrix form. The proposed model performed better on MIMIC-III ICU dataset than the current state-of-the-art probabilistic forecasting models. We obtained normalized average continuous ranked probability score (CRPS) of 0 . 4379 , and mean squared error (MSE) of 0 . 4008 when adopting the median of the model samplings as the deterministic forecasting. Our code is provided at https://github.com/PingChang818/TDSTF.
Optimization of Affinity Chromatography Based on Sepharose 4B- chitin for Rapid Purification of Urtica dioica Agglutinin

Background: Today, numerous antimicrobial and anticancer properties have been reported for plant lectins due to their ability to bind to carbohydrates. The Urtica dioica agglutinin (UDA lectin) is a monomeric, small, and low molecular weight glycoprotein. It has attracted the attention of many researchers for identification, treatment, and other clinical purposes. Objectives: The aim of this study is the optimization of the chitin affinity chromatography based on Sepharose 4B (CNBr-activated Sepharose 4B) for the rapid purification of UDA lectin from Urtica dioica rhizome. Materials and Methods: The chitin ligands were dissolved in 40% Trichloroacetic acid and attached to Sepharose 4B according to the Amersham-Biosciences instructions. The attachment of the ligand to the Sepharose 4B beads was investigated by Fourier transform infrared (FTIR) spectroscopy. An acidic crude extract of nettle rhizome passes from chromatographic columns in two sizes with dimensions: 24 x 0.51 cm and 8.44 x 0.86 cm. Quantity and quality of purified lectin were calculated by the Bradford microplate method: SDS-PAGE gel electrophoresis and human erythrocyte cell (RBC) hemagglutination, respectively. Results: The analysis of FTIR spectrograms showed that major changes were observed in the fingerprint regions. Besides, due to the dissolution of Sepharose 4B and chitin in the aqueous phase, this difference was not significant in the Imine and Nitrile regions. On the other hand, the comparative results of purification chromatograms showed that increasing the column length causes a smaller half-width and increases the length of the purified peak. Also, it leads to high-quality purified UDA lectin, with a molecular weight of almost 12.5 kDa in gel electrophoresis. Hemagglutination activity on trypsinized red blood cells was displayed, and agglutination of purified UDA lectin started at least at 300 μg. mL-1 concentration. Conclusion: According to our findings, we suggested that dissolving chitin in the polar solvent of Trichloroacetic acid, using Sepharose 4B as the beads of a matrix, and increasing the column length might lead to a decrease in the half-width of the peak. These can increase the purity and concentration of purified UDA lectin, and speed up the purification process. These findings could be used by researchers to accelerate the purification of UDA lectin in other studies, dealing with drug delivery systems, ELISA techniques, and cell growth.
Production of Childinan SF-2 as Bioactive Compound from Daldinia childiae: A Survey on Antioxidant, Antibacterial and Antitumor Properties

Background: Fungal extracts have received increased attention due to their great medicinal applications including antitumor, immune-modulating, antioxidant, radical scavenging, antiviral, antibacterial, antifungal and detoxificating properties. Objectives: This study is the first report on a novel bioactive compound, namely Childinan SF-2 which was isolated from soil ascomycete fungus. The significant antibacterial, antioxidant and cytotoxic properties of the extract may lead to development of novel, safe and useful substances. Materials and Methods: The isolate was identified on the basis of molecular approach. Spore suspension was inoculated in the culture medium and the bioactive compound was isolated from the viscous fermented broth via ethanol precipitation of the extracellular compound. The basic chemical composition of the extract including protein, carbohydrate, sulfate radical and uronic acid content were measured. FTIR (Fourier-transform infrared spectroscopy) and GC–MS (Gas chromatography–mass spectrometry) analysis were used for further structural characterization. The extract was utilized for treatment of AGS and MDA cell lines to assess the cell cycle and apoptosis. The antioxidant activity was examined using DPPH, hydroxyl radicals scavenging, β-carotene bleaching inhibition and ferric reducing power assay methods. The extract was tested for evaluation of antibacterial activity using different Gram-positive and Gram-negative bacterial strains. Results: The fungal isolate was identified as the new strain Daldinia childiae SF-2. Initial biochemical characterization of the extract showed that the fungal biopolymer was composed of total sugars, protein, uronic acids and sulfated groups with values of 91.6%, 2.15%, 2.25% and 1.05% (w/w), respectively. FTIR and GC–MS analysis revealed that Childinan SF-2 might be mainly constructed from D-glucose, D-mannitol and D-galactofuranose. The in vitro experiments revealed that Childinan SF-2 enhanced the percentage of necrosis and apoptosis of cancer cells and blocked the cell cycle progression as shown by flowcytometry. Childinan SF-2 represented a considerable antioxidant and antibacterial activity. Conclusions: These results indicated that Childinan SF-2 can serve as a potential source in medicinal applications. Keywords Exopolysaccharides; Fungal Biopolymers; Mycelial Secretions; Natural Pharmaceuticals; Xylariaceae;
Monitoring vegetation- and geodiversity with remote sensing and traits

Geodiversity has shaped and structured the Earth's surface at all spatio-temporal scales, not only through long-term processes but also through medium- and short-term processes. Geodiversity is, therefore, a key control and regulating variable in the overall development of landscapes and biodiversity. However, climate change and land use intensity are leading to major changes and disturbances in bio- and geodiversity. For sustainable ecosystem management, temporal, economically viable and standardized monitoring is needed to monitor and model the effects and changes in vegetation- and geodiversity. RS approaches have been used for this purpose for decades. However, to understand in detail how RS approaches capture vegetation- and geodiversity, the aim of this paper is to describe how five features of vegetation- and geodiversity are captured using RS technologies, namely: (i) trait diversity, (ii) phylogenetic/genese diversity, (iii) structural diversity, (iv) taxonomic diversity and (v) functional diversity. Trait diversity is essential for establishing the other four. Traits provide a crucial interface between in situ, close-range, aerial and space-based RS monitoring approaches. The trait approach allows complex data of different types and formats to be linked using the latest semantic data integration techniques, which will enable ecosystem integrity monitoring and modelling in the future. This article is part of the Theo Murphy meeting issue ‘Geodiversity for science and society’.
Universal insertion of molecules in ionic compounds under pressure

ABSTRACT Using first-principles calculations and crystal structure search methods, we found that many covalently bonded molecules such as H2, N2, CO2, NH3, H2O and CH4 may react with NaCl, a prototype ionic solid, and form stable compounds under pressure while retaining their molecular structure. These molecules, despite whether they are homonuclear or heteronuclear, polar or non-polar, small or large, do not show strong chemical interactions with surrounding Na and Cl ions. In contrast, the most stable molecule among all examples, N2, is found to transform into cyclo-N5− anions while reacting with NaCl under high pressures. It provides a new route to synthesize pentazolates, which are promising green energy materials with high energy density. Our work demonstrates a unique and universal hybridization propensity of covalently bonded molecules and solid compounds under pressure. This surprising miscibility suggests possible mixing regions between the molecular and rock layers in the interiors of large planets.
Anti-Inflammatory Properties of Extract of the Hairy Root of Native Portulaca Oleracea L. and Its Effect on Some Inflammatory Genes Expression in Rat Microglial Cells

Background: Most herbs play significant roles in the treatment of various diseases. Because dopamine functions in the anti-inflammatory process and the presence of this substance in Portulaca Oleracea L. native plant, investigating this plant’s anti-inflammatory properties in treating neurological diseases is interesting. Objectives: The objective of this study was to estimate the NO production and the expression level of inflammatory genes in lipopolysaccharide (LPS)-treated microglial cells affected by P. oleracea L. extraction. Materials and Methods: P. oleracea L. hairy root extract was isolated, and the primary microglial cell of the rat was isolated from glial cells and confirmed by immunocytochemistry analysis. Microglial cells were pretreated with different concentrations of P. oleracea L. extract and then treated with 1 μg. mL-1 LPS. The control group did not receive any treatment. The NO level in culture supernatants was measured by the Griess method. The mRNA expression levels of iNOS (inducible Nitric oxide synthase) and TNF-α (tumor necrosis factor-alpha) in LPS-treated microglial cells were evaluated using Real-Time PCR. Results: The present study determined that 0.1 mg. mL-1 of the P. oleracea L. extract decreased the NO production in rat microglial cells. Different concentrations of the P. oleracea L. extract had no prominent effects on LPS-treated cell viability. The results of real-time PCR indicated that P. oleracea L extracts suppressed the mRNA expression levels of iNOS and TNF-α in LPS-treated cells. MTT assay determined that P. oleracea L. extract was not cytotoxic, and the anti-inflammatory P. oleracea L. extract effects observed were not because of cell death. Conclusion: P. oleracea L. extract might be helpful as an anti-inflammatory agent in treating inflammatory diseases.
Upstream-binding factor is sequestered into herpes simplex virus type 1 replication compartments

Previous reports have shown that adenovirus recruits nucleolar protein upstream-binding factor (UBF) into adenovirus DNA replication centres. Here, we report that despite having a different mode of viral DNA replication, herpes simplex virus type 1 (HSV-1) also recruits UBF into viral DNA replication centres. Moreover, as with adenovirus, enhanced green fluorescent protein-tagged fusion proteins of UBF inhibit viral DNA replication. We propose that UBF is recruited to the replication compartments to aid replication of HSV-1 DNA. In addition, this is a further example of the role of nucleolar components in viral life cycles.
Arthropod diversity in the alpine tundra using metabarcoding: Spatial and temporal differences in alpha‐ and beta‐diversity

Abstract All ecosystems face ecological challenges in this century. Therefore, it is becoming increasingly important to understand the ecology and degree of local adaptation of functionally important Arctic‐alpine biomes by looking at the most diverse taxon of metazoans: the Arthropoda. This is the first study to utilize metabarcoding in the Alpine tundra, providing insights into the effects of micro‐environmental parameters on alpha‐ and beta‐diversity of arthropods in such unique environments. To characterize arthropod diversity, pitfall traps were set at three middle‐alpine sampling sites in the Scandinavian mountain range in Norway during the snow‐free season in 2015. A metabarcoding approach was then used to determine the small‐scale biodiversity patterns of arthropods in the Alpine tundra. All DNA was extracted directly from the preservative EtOH from 27 pitfall traps. In order to identify the controlling environmental conditions, all sampling locations were equipped with automatic data loggers for permanent measurement of the microenvironmental conditions. The variables measured were: air temperature [°C] at 15 cm height, soil temperature [°C] at 15 cm depth, and soil moisture [vol.%] at 15 cm depth. A total of 233 Arthropoda OTUs were identified. The number of unique OTUs found per sampling location (ridge, south‐facing slope, and depression) was generally higher than the OTUs shared between the sampling locations, demonstrating that niche features greatly impact arthropod community structure. Our findings emphasize the fine‐scale heterogeneity of arctic–alpine ecosystems and provide evidence for trait‐based and niche‐driven adaptation. The spatial and temporal differences in arthropod diversity were best explained by soil moisture and soil temperature at the respective locations. Furthermore, our results show that arthropod diversity is underestimated in alpine‐tundra ecosystems using classical approaches and highlight the importance of integrating long‐term functional environmental data and modern taxonomic techniques into biodiversity research to expand our ecological understanding of fine‐ and meso‐scale biogeographical patterns.
Bioprinting of Vascularized Tissue Scaffolds: Influence of Biopolymer, Cells, Growth Factors, and Gene Delivery

Over the past decades, tissue regeneration with scaffolds has achieved significant progress that would eventually be able to solve the worldwide crisis of tissue and organ regeneration. While the recent advancement in additive manufacturing technique has facilitated the biofabrication of scaffolds mimicking the host tissue, thick tissue regeneration remains challenging to date due to the growing complexity of interconnected, stable, and functional vascular network within the scaffold. Since the biological performance of scaffolds affects the blood vessel regeneration process, perfect selection and manipulation of biological factors (i.e., biopolymers, cells, growth factors, and gene delivery) are required to grow capillary and macro blood vessels. Therefore, in this study, a brief review has been presented regarding the recent progress in vasculature formation using single, dual, or multiple biological factors. Besides, a number of ways have been presented to incorporate these factors into scaffolds. The merits and shortcomings associated with the application of each factor have been highlighted, and future research direction has been suggested.
Title : Adaptive exponential integrate-and-fire model as an effective description of neuronal activity

We introduce a two-dimensional integrate-and-fire model which combines an exponential spike mechanism with an adaptation equation, based on recent theoretical findings. We describe a systematic method to estimate its parameters with simple electrophysiological protocols (current-clamp injection of pulses and ramps), and apply it to a detailed conductance-based model of a regular spiking neuron. Our simple model predicts correctly the timing of 96% of the spikes (±2 ms) of the detailed model in response to injection of noisy synaptic conductances. The model is especially reliable in high-conductance states, typical of cortical activity in vivo, in which intrinsic conductances were found to have a reduced role in shaping spike trains. These results are promising because this simple model has enough expressive power to reproduce qualitatively several electrophysiological classes described in vitro.
Adaptive Exponential Integrate-and-Fire Model as an Effective Description of Neuronal Activity

[PDF] [Full Text] [Abstract] , October 1, 2007; 19 (10): 2604-2609. Neural Comput. R. Brette Exact Simulation of Integrate-and-Fire Models with Exponential Currents [PDF] [Full Text] [Abstract] , November 1, 2007; 19 (11): 2958-3010. Neural Comput. E. Muller, L. Buesing, J. Schemmel and K. Meier Theories Spike-Frequency Adapting Neural Ensembles: Beyond Mean Adaptation and Renewal [PDF] [Full Text] [Abstract] , December 1, 2007; 19 (12): 3226-3238. Neural Comput. A. Tonnelier, H. Belmabrouk and D. Martinez Event-Driven Simulations of Nonlinear Integrate-and-Fire Neurons. [PDF] [Full Text] [Abstract] , February 1, 2008; 99 (2): 656-666. J Neurophysiol L. Badel, S. Lefort, R. Brette, C. C. H. Petersen, W. Gerstner and M. J. E. Richardson Traces Dynamic I-V Curves Are Reliable Predictors of Naturalistic Pyramidal-Neuron Voltage [PDF] [Full Text] [Abstract] , September 1, 2008; 18 (9): 2086-2097. Cereb Cortex H. Kondgen, C. Geisler, S. Fusi, X. -J. Wang, H. -R. Luscher and M. Giugliano Noisy Inputs In Vitro The Dynamical Response Properties of Neocortical Neurons to Temporally Modulated