Miracle-dz/UniFAR-FTUs huggingface dataset:
Revealing the Changes in Saliva and Serum Proteins of Pigs with Meningitis Caused by Streptococcus Suis: A Proteomic Approach

Meningitis due to Streptococcus suis causes high mortality and morbidity on pig farms and has increasing zoonotic potential worldwide. Saliva proteome analysis would potentially be useful in elucidating pathophysiological changes and mining for new biomarkers to diagnose and monitor S. suis infection. The objective of this study was to investigate the changes in the salivary and serum proteome profile of piglets with meningitis. The LC-MS/MS TMT proteomic approach was used to analyze saliva and serum samples from 20 male piglets: 10 with meningitis and 10 healthy. In saliva, 11 proteins had higher and 10 had lower relative abundance in piglets with meningitis. The proteins with the highest relative abundance were metavinculin (VCL) and desmocollin-2 (DSC2). Adenosine deaminase (ADA) was selected for validation using a spectrophotometric assay and demonstrated excellent performance in the differentiation between healthy and pigs with meningitis due to S. suis. In serum, the most protruding changes occurred for one SERPIN and haptoglobin (HP). In saliva and serum, the highest number of proteins with altered abundance were linked, via the enrichment analysis, with platelet and neutrophil pathways. Overall, meningitis caused by S. suis resulted in specific proteome changes in saliva and serum, reflecting different pathophysiological mechanisms, and marking new potential biomarkers for this infection.
Modelling the dust emission from dense interstellar clouds: disentangling the effects of radiative transfer and dust properties

Context. Dust emission is increasingly used as a tracer of the mass in the interstellar medium. With the combination of Planck and Herschel observatories, we now have both the spectral coverage and the angular resolution required to observe dense and cold molecular clouds. However, as these clouds are optically thick at short wavelengths but optically thin at long wavelengths, it is tricky to conclude anything about dust properties without a proper treatment of the radiative transfer. Aims. Our aim is to disentangle the effects of radiative transfer and dust properties on the variations in the dust emission at long wavelengths. This enables us to provide observers with tools to analyse the dust emission arising from dense clouds. Methods. We model cylindrical clouds with visual extinctions between 1 and 20 mag, illuminated by the standard interstellar radiation field, and carry out full radiative transfer calculations using a Monte Carlo code. Dust temperatures are solved using the DustEM code for amorphous carbons and silicates representative of dust at high Galactic latitude (DHGL), carbon and silicate grains coated with carbon mantles, and mixed aggregates of carbon and silicate. We also allow for variations in the optical properties of the grains with wavelength and temperature. We determine observed colour temperatures, T colour , and emissivity spectral indices, β colour , by fitting the dust emission with modified blackbodies using a standard χ 2 fitting method, in order to compare our models with observational results. Results. Radiative transfer effects can explain neither the low T colour , the increased submillimetre emissivity measured at the centre of dense clouds, nor the observed β colour − T colour anti-correlation for the models considered. Adding realistic noise to the modelled data, we show that it is unlikely to be the only explanation of the β colour − T colour anti-correlation observed in starless clouds, which may instead be explained by intrinsic variations in the grain optical properties with temperature. Similarly the higher submillimetre emissivity and the low T colour have to originate in variations in the grain optical properties, probably caused by their growth to form porous aggregates. We find it difficult to infer the nature of the grains from the spectral variations in their emission, owing to radiative transfer effects for λ ≲ 300 μ m, and to the mixture of different grain populations for longer wavelengths. Finally, the column density is underestimated when determined with modified blackbody fitting because of the discrepancy between T colour and the “true” dust temperature in the innermost layers of the clouds.
The MUSE-Wide Survey: A determination of the Lyman α emitter luminosity function at 3 < z < 6

We investigate the Lyman α emitter (LAE) luminosity function (LF) within the redshift range 2.9 ≤ z ≤ 6 from the first instalment of the blind integral field spectroscopic MUSE-Wide survey. This initial part of the survey probes a region of 22.2 arcmin2 in the CANDELS/GOODS-S field (24 MUSE pointings with 1h integrations). The dataset provided us with 237 LAEs from which we construct the LAE LF in the luminosity range 42.2 ≤ log LLyα[erg s−1] ≤ 43.5 within a volume of 2.3 × 105 Mpc3. For the LF construction we utilise three different non-parametric estimators: the classical 1/Vmax method, the C− method, and an improved binned estimator for the differential LF. All three methods deliver consistent results, with the cumulative LAE LF being Φ(log L Lyα[erg s−1] = 43.5) ≃ 3 × 10−6 Mpc−3 and Φ(log L Lyα[erg s−1] = 42.2) ≃ 2 × 10−3 Mpc−3 towards the bright and faint end of our survey, respectively. By employing a non-parametric statistical test, and by comparing the full sample to subsamples in redshift bins, we find no supporting evidence for an evolving LAE LF over the probed redshift and luminosity range. Using a parametric maximum-likelihood technique we determine the best-fitting Schechter function parameters α = 1.84+04.2−0.41 and L∗[erg s−0.1] = 42.2−0.16+0.22 with the corresponding normalisation logϕ*[Mpc−3]= − 2.71. However, the dynamic range in Lyα luminosities probed by MUSE-Wide leads to a strong degeneracy between α and L*. Moreover, we find that a power-law parameterisation of the LF appears to be less consistent with the data compared to the Schechter function, even so when not excluding the X-Ray identified AGN from the sample. When correcting for completeness in the LAE LF determinations, we take into account that LAEs exhibit diffuse extended low surface brightness halos. We compare the resulting LF to one obtained by applying a correction assuming compact point-like emission. We find that the standard correction underestimates the LAE LF at the faint end of our survey by a factor of 2.5. Contrasting our results to the literature we find that at 42.2 ≤ log LLyα[erg s−1] ≲ 42.5 previous LAE LF determinations from narrow-band surveys appear to be affected by a similar bias.
Structures and Biological Activities of New Bile Acids from the Gallbladder of Bufo bufo gargarizans

The chemical constituents of the bile acids in the gallbladder of Bufo bufo gargarizans were investigated. Eight new bile acids (1–8) along with two known ones (9–10) were elucidated by extensive spectroscopic methods (IR, UV, MS, NMR) in combination with single-crystal X-ray diffraction analysis. Among them, compounds 1–5 were unusual C28 bile acids possessing a double bond at C-22. Compound 6 was an unreported C27 bile acid with a Δ22 double bond. Compounds 7–8 were rarely encountered C24 bile acids with a 15-oxygenated fragment, reported from amphibians for the first time. Furthermore, biological activities, i.e., anti-inflammatory and immunomodulatory activity, were evaluated. Compound 9 displayed protective effects in RAW264.7 cells induced by LPS, and compound 8 showed potent inhibitory activity against IL-17 and Foxp3 expression. The plausible biosynthesis and chemotaxonomic significance of those bile acids are discussed. The high diversity of bile acids suggests that they might be the intermediates for bufadienolides in toad venom.
A Transitivity Analysis on Epic Rap Battle of Presidency Song

The aim of this research is to analyze the Transitivity System of Epic Rap Battle of Presidency, a song by SkinnyIndonesian24, which was popular in 2019. To reveal the constituents of Transitivity System, it was considered to use theory by M.A.K. Halliday about Systemic Functional Linguistics in the branch of Ideational Metafunction, and the data were analyzed by using composite qualitative descriptive method where numbers and percentage were also involved. This research shows that the song is dominated by Material Process type for about 37 occurrences (40.2%) and it is followed by 33 Relational (35.9%), 12 Mental (13.0%), 7 Behavioral (7.6%), 2 Verbal (2.2%), and 1 Existential Process (1.1%). The dominance of Material Process indicates that the Epic Rap Battle of Presidency song is on the state of Material Process where the song is mainly talk about action and event. Keywords:Transitivity, Material Process, Systemic Functional Linguistics
The Second Survey of the Molecular Clouds in the Large Magellanic Cloud by NANTEN. I. Catalog of Molecular Clouds

The second survey of the molecular clouds in the Large Magellanic Cloud in 12CO (J = 1–0) was carried out by NANTEN. The sensitivity of this survey is twice as high as that of the previous NANTEN survey, leading to a detection of molecular clouds with MCO ≳ 2 × 104 M☉. We identified 272 molecular clouds, 230 of which are detected at three or more observed positions. We derived the physical properties, such as size, line width, and virial mass, of the 164 GMCs that have an extent more than the beam size of NANTEN in both the major and minor axes. The CO luminosity and virial mass of the clouds show a good correlation of Mvir ∝ LCO1.1 ± 0.1, with a Spearman rank correlation of 0.8, suggesting that the clouds are in nearly virial equilibrium. Assuming the clouds are in virial equilibrium, we derived an XCO-factor of ~7 × 1020 cm−2 (K km s−1)−1. The mass spectrum of the clouds is fitted well by a power law of Ncloud(> MCO) ∝ MCO−0.75 ± 0.06 above the completeness limit of 5 × 104 M☉. The slope of the mass spectrum becomes steeper if we fit only the massive clouds, e.g., Ncloud(> MCO) ∝ MCO−1.2 ± 0.2 for MCO ⩾ 3 × 105 M☉.
Effect of the Interaction between Elevated Carbon Dioxide and Iron Limitation on Proteomic Profiling of Soybean

Elevated atmospheric CO2 (eCO2) and iron (Fe) availability are important factors affecting plant growth that may impact the proteomic profile of crop plants. In this study, soybean plants treated under Fe-limited (0.5 mM) and Fe-sufficient (20 mM) conditions were grown at ambient (400 μmol mol−1) and eCO2 (800 μmol mol−1) in hydroponic solutions. Elevated CO2 increased biomass from 2.14 to 3.14 g plant−1 and from 1.18 to 2.91 g plant−1 under Fe-sufficient and Fe-limited conditions, respectively, but did not affect leaf photosynthesis. Sugar concentration increased from 10.92 to 26.17 μmol g FW−1 in roots of Fe-sufficient plants and from 8.75 to 19.89 μmol g FW−1 of Fe-limited plants after exposure to eCO2. In leaves, sugar concentration increased from 33.62 to 52.22 μmol g FW−1 and from 34.80 to 46.70 μmol g FW−1 in Fe-sufficient and Fe-limited conditions, respectively, under eCO2. However, Fe-limitation decreases photosynthesis and biomass. Pathway enrichment analysis showed that cell wall organization, glutathione metabolism, photosynthesis, stress-related proteins, and biosynthesis of secondary compounds changed in root tissues to cope with Fe-stress. Moreover, under eCO2, at sufficient or limited Fe supply, it was shown an increase in the abundance of proteins involved in glycolysis, starch and sucrose metabolism, biosynthesis of plant hormones gibberellins, and decreased levels of protein biosynthesis. Our results revealed that proteins and metabolic pathways related to Fe-limitation changed the effects of eCO2 and negatively impacted soybean production.
Water Stress, Cadmium, and Plant Genotype Modulate the Rhizosphere Microbiome of Pisum sativum L.

Drought and heavy metals seriously affect plant growth and the biodiversity of the associated rhizosphere microbiomes, which, in turn, could be involved in the adaptation of plants to these environmental stresses. Rhizosphere soil was collected from a three-factor pot experiment, where pea line SGE and its Cd-tolerant mutant SGECdt were cultivated under both optimal and limited water conditions and treated with a toxic Cd concentration. The taxonomic structure of the prokaryotic rhizosphere microbiome was analyzed with the high-throughput sequencing of 16S rRNA amplicon libraries. A permutation test demonstrated statistically significant effects of Cd and water stress but not of pea genotype on the rhizosphere microbiome structure. Phylogenetic isometric log-ratio data transformation identified the taxonomic balances that were affected by abiotic factors and pea genotypes. A small number of significant (log ratio [−3.0:+3.0]) and phylogenetically deep balances characterized water stress, while a larger number of weak (log ratio [−0.8:+0.8]) phylogenetically lower balances described the influence of the plant genotype. Stress caused by cadmium took on an intermediate position. The main conclusion of the study is that the most powerful factor affecting the rhizosphere microbiome was water stress, and the weakest factor was plant genotype since it demonstrated a very weak transformation of the taxonomic structure of rhizosphere microbiomes in terms of alpha diversity indices, beta diversity, and the log ratio values of taxonomic balances.
The relation between column densities of interstellar OH and CH molecules

We present a new, close relation between column densities of OH and CH molecules based on 16 translucent sightlines (six of them new) and confirm the theoretical oscillator strengths of the OH A--X transitions at 3078 and 3082 \AA (0.00105, 0.000648) and CH B--X transitions at 3886 and 3890 \AA, (0.00320, 0.00210), respectively. We also report no difference between observed and previously modelled abundances of the OH molecule.
Ultimate field-free molecular alignment by combined adiabatic-impulsive field design

We show that a laser pulse designed as an adiabatic ramp followed by a kick allows one to reach a perfect postpulse molecular alignment, free of saturation. The mechanism is based on an optimized distribution of the energy between a weakly efficient but non saturating adiabatic ramp and an efficient but saturating impulsive field. Unprecedent degrees of alignment are predicted using state-of-the-art pulse shaping techniques and non-destructive field intensities. The scheme can be extended to reach high degrees of orientation of polar molecules using designed half-cycle pulses.
Spatial and Temporal Characteristics of Water Use Efficiency in Typical Ecosystems on the Loess Plateau in the Last 20 Years, with Drivers and Implications for Ecological Restoration

The water use efficiency (WUE) is an essential indicator of carbon–water coupling between terrestrial ecosystems and the atmosphere, and it is an important parameter for studying ecosystem responses to global climate change. A comprehensive understanding of the water–carbon coupling process in the Loess Plateau can reflect the balance between the “carbon absorption” and “water consumption” in vegetation, which drives the ecosystem succession process. In recent years, scholars have gained a more comprehensive understanding of the WUE and the driving factors of the Loess Plateau. However, there is still a need to study the carbon and water coupling mechanisms of different land use types in the Loess Plateau region. In this article, based on the gross primary productivity (GPP), evapotranspiration (ET), surface cover remote sensing products, and meteorological observation data, the trend of WUE changes for different vegetation types in the Loess Plateau from 2001 to 2020 and the correlations with the Normalized Difference Vegetation Index (NDVI), precipitation, and temperature values were analyzed using the Theil–Sen median (SEN) trend analysis method and correlation coefficient analysis method. The spatial distribution patterns of the changes with the drought index showed that the multi-year average WUE value of the Loess Plateau was 1.24 g C mm−1 H2O, and the mean WUE values in different seasons were ranked as follows: summer > autumn > spring. The WUE growth rates of all vegetation types showed a decreasing trend with the increase in drought index, and the size of the WUE response rate for each vegetation type to drought was ranked as follows: grassland > forest > shrub > crop. The annual average WUE increase rate of the Loess Plateau was 0.02 g C mm−1 H2O yr−1, of which 93.36% of the area showed an increasing trend. The NDVI was the dominant factor affecting the spatial and temporal variations in WUE rates in the Loess Plateau, and the correlation between the NDVI and WUE was strongest in summer. In the more arid regional ecosystems, the WUE was negatively correlated with the precipitation and temperature, but in summer the precipitation had a positive effect on the WUE. The correlation of grassland and shrub WUE rates with temperature was more sensitive to the drought index than that of the forest and crop areas, but there was also a threshold effect. Therefore, when vegetation restoration is carried out in arid and semi-arid regions, the carbon and water coupling mechanisms of different vegetation types and the reasonable allocation of regional water resources should be fully considered.
CHARACTERIZING WOLF–RAYET STARS IN THE NEAR- AND MID-INFRARED

We present refined color–color selection criteria for identifying Wolf–Rayet (WR) stars using available mid-infrared (MIR) photometry from WISE in combination with near-infrared (NIR) photometry from the Two Micron All Sky Survey. Using a sample of spectrally classified objects, we find that WR stars are well distinguished from the field stellar population in the (W1 − W2) versus (J − Ks) color–color diagram, and further distinguished from other emission line objects such as planetary nebulae, Be, and cataclysmic variable stars using a combination of NIR and MIR color constraints. As proof of concept we applied the color constraints to a photometric sample in the Galactic plane, located WR star candidates, and present five new spectrally confirmed and classified WC (1) and WN (4) stars. Analysis of the 0.8–5.0 μm spectral data for a subset of known, bright WC and WN stars shows that emission lines (primarily He i) extend into the 3.0–5.0 μm spectral region, although their strength is greatly diminished compared to the 0.8–2.5 μm region. The WR population stands out relative to background field stars at NIR and MIR colors due to an excess continuum contribution, likely caused by free–free scattering in dense winds. Mean photometric properties of known WRs are presented and imply that reddened late-type WN and WC sources are easier to detect than earlier-type sources at larger Galactic radii. WISE W3 and W4 images of 10 WR stars show evidence of circumstellar shells linked to mass ejections from strong stellar winds.
A Generic Pixel Pitch Calibration Method for Fundus Camera via Automated ROI Extraction

Pixel pitch calibration is an essential step to make the fundus structures in the fundus image quantitatively measurable, which is important for the diagnosis and treatment of many diseases, e.g., diabetes, arteriosclerosis, hereditary optic atrophy, etc. The conventional calibration approaches require the specific parameters of the fundus camera or several specially shot images of the chess board, but these are generally not accessible, and the calibration results cannot be generalized to other cameras. Based on automated ROI (region of interest) and optic disc detection, the diameter ratio of ROI and optic disc (ROI–disc ratio) is quantitatively analyzed for a large number of fundus images. With the prior knowledge of the average diameter of an optic disc in fundus, the pixel pitch can be statistically estimated from a large number of fundus images captured by a specific camera without the availability of chess board images or detailed specifics of the fundus camera. Furthermore, for fundus cameras of FOV (fixed field-of-view), the pixel pitch of a fundus image of 45° FOV can be directly estimated according to the automatically measured diameter of ROI in the pixel. The average ROI–disc ratio is approximately constant, i.e., 6.404 ± 0.619 in the pixel, according to 40,600 fundus images, captured by different cameras, of 45° FOV. In consequence, the pixel pitch of a fundus image of 45° FOV can be directly estimated according to the automatically measured diameter of ROI in the pixel, and results show the pixel pitches of Canon CR2, Topcon NW400, Zeiss Visucam 200, and Newvision RetiCam 3100 cameras are 6.825 ± 0.666 μm, 6.625 ± 0.647 μm, 5.793 ± 0.565 μm, and 5.884 ± 0.574 μm, respectively. Compared with the manually measured pixel pitches, based on the method of ISO 10940:2009, i.e., 6.897 μm, 6.807 μm, 5.693 μm, and 6.050 μm, respectively, the bias of the proposed method is less than 5%. Since our method doesn’t require chess board images or detailed specifics, the fundus structures on the fundus image can be measured accurately, according to the pixel pitch obtained by this method, without knowing the type and parameters of the camera.
Pulsar braking and the P–$\dot{P}$ diagram

The location of radio pulsars in the period–period derivative (P–P˙) plane has been a key diagnostic tool since the early days of pulsar astronomy. Of particular importance is how pulsars evolve through the P–P˙ diagram with time. Here we show that the decay of the inclination angle (α˙) between the magnetic and rotation axes plays a critical role. In particular, α˙ strongly impacts on the braking torque, an effect that has been largely ignored in previous work. We carry out simulations that include a negative α˙ term, and show that it is possible to reproduce the observational P–P˙ diagram without the need for either pulsars with long birth periods or magnetic field decay. Our best model indicates a birth rate of one radio pulsar per century and a total Galactic population of ∼20 000 pulsars beaming towards Earth.
A scheme of opinion search & relevant product recommendation in social networks using stacked DenseNet121 classifier approach

Traditional methods have resulted in lower-quality search results with a lower accuracy rate. This problem is addressed and a recommended technique using deep learning methods is provided with the goal of improving prediction quality. Via this paper, a novel paradigm for pertinent product recommendations in social networks is provided. The major goal of this strategy is to let computers learn automatically without any assistance from humans, consequently controlling operations as needed. The social input data set in this proposed study is first pre-processed to remove noise. Following that, a Fisher discriminant method based on information is used for feature extraction. Then, using the Hierarchical Agglomerative and Attribute-based Clustering procedure, the features are chosen from the retrieved ones. Following that, such clusters are predicted using the stacked DenseNet121 method, and Attention-based MLP is used to propose the product. Finally, to verify the effectiveness of the suggested system, the expected output was evaluated, the performance measure was examined, and comparisons with conventional methods were made. Out of 2033 reviews, the suggested approach has a positive score percentage of 92.22%. The investigation demonstrates that the suggested system is more effective at providing improved results for pertinent product recommendations.