Miracle-dz/UniFAR-FTUs huggingface dataset:
MS2DeepScore - a novel deep learning similarity measure for mass fragmentation spectrum comparisons

Mass spectrometry data is one of the key sources of information in many workflows in medicine and across the life sciences. Mass fragmentation spectra are considered characteristic signatures of the chemical compound they originate from, yet the chemical structure itself usually cannot be easily deduced from the spectrum. Often, spectral similarity measures are used as a proxy for structural similarity but this approach is strongly limited by a generally poor correlation between both metrics. Here, we propose MS2DeepScore: a novel Siamese neural network to predict the structural similarity between two chemical structures solely based on their MS/MS fragmentation spectra. Using a cleaned dataset of >100,000 mass spectra of about 15,000 unique known compounds, MS2DeepScore learns to predict structural similarity scores for spectrum pairs with high accuracy. In addition, sampling different model varieties through Monte-Carlo Dropout is used to further improve the predictions and assess the model’s prediction uncertainty. On 3,600 spectra of 500 unseen compounds, MS2DeepScore is able to identify highly-reliable structural matches and predicts Tanimoto scores with a root mean squared error of about 0.15. The prediction uncertainty estimate can be used to select a subset of predictions with a root mean squared error of about 0.1. We demonstrate that MS2DeepScore outperforms classical spectral similarity measures in retrieving chemically related compound pairs from large mass spectral datasets, thereby illustrating its potential for spectral library matching. Finally, MS2DeepScore can also be used to create chemically meaningful mass spectral embeddings that could be used to cluster large numbers of spectra. Added to the recently introduced unsupervised Spec2Vec metric, we believe that machine learning-supported mass spectral similarity metrics have great potential for a range of metabolomics data processing pipelines.
Life history predicts global population responses to the weather in terrestrial mammals

With the looming threat of abrupt ecological disruption due to a changing climate, predicting which species are most vulnerable to environmental change is critical. The life-history of a species is an evolved response to its environmental context, and therefore a promising candidate for explaining differences in climate-change responses. However, we need broad empirical assessments from across the world's ecosystems to explore the link between life history and climate-change responses. Here, we use long-term abundance records from 157 species of terrestrial mammals and a two-step Bayesian meta-regression framework to investigate the link between annual weather anomalies, population growth rates, and species-level life history. Overall, we found no directional effect of temperature or precipitation anomalies or variance on annual population growth rates. Furthermore, population responses to weather anomalies were not predicted by phylogenetic covariance, and instead there was more variability in weather responses for populations within a species. Crucially, however, long-lived mammals with smaller litter sizes had smaller absolute population responses to weather anomalies compared with their shorter living counterparts with larger litters. These results highlight the role of species-level life history in driving responses to the environment.
Three bacterium-plasmid golden combinations facilitate the spread of ST11/CG258 carbapenemase-producing Klebsiella pneumoniae in China

Carbapenemase-producing Klebsiella pneumoniae (cpKP) poses serious threats to public health. Previous studies showed that only ST11/CG258-cpKP successfully disseminated in China, however, the underlying genetic bases are still unknown. We conducted a comprehensive genomic-epidemiology analysis on 420 cpKP isolates from 70 hospitals in 24 Chinese provinces during 2009-2017 based on short-/long-reads sequencing. Three ‘golden’ combinations of host––blaKPC-carrying plasmids (Clade 3.1+3.2—IncFIIpHN7A8, Clade 3.1+3.2—IncFIIpHN7A8:IncR, Clade 3.3—IncFIIpHN7A8:IncpA1763-KPC) endowed cpKP with advantages both in genotypes (strong-correlation/co-evolution) and phenotypes (resistance/growth/competition), thereby facilitating nationwide spread of ST11/CG258-cpKP. Intriguingly, Bayesian skyline illustrated that the three ‘golden’ combinations might directly lead to the strong population expansion during 2007-2008 and subsequent maintenance of the dissemination of ST11/CG258-cpKP after 2008. We tested drug-resistance profiles and proposed combination treatment regimens for CG258/non-CG258 cpKP. Our findings systematically revealed the molecular-epidemiology and genetic-basis for dissemination of Chinese ST11/CG258 cpKP and reminded us to monitor the ‘golden’ combinations of cpKP- plasmid closely.
The 3D construction of leaves is coordinated with water use efficiency in conifers

Conifers prevail in the canopies of many terrestrial biomes, holding a great ecological and economic importance globally. Current increases in temperature and aridity are imposing high transpirational demands and resulting in conifer mortality. Therefore, identifying leaf structural determinants of water use efficiency is essential in predicting physiological impacts due to environmental variation. Using synchrotron-generated microCT imaging, we extracted leaf volumetric anatomy and stomatal traits in 34 species across conifers with a special focus on Pinus, the richest conifer genus. We show that intrinsic water use efficiency (WUEi) is positively driven by leaf vein volume. Needle-like leaves of Pinus, as opposed to flat leaves or flattened needles of other genera, showed lower mesophyll porosity, decreasing the relative mesophyll volume. This led to increased ratios of stomatal pore number per mesophyll or intercellular airspace volume, which emerged as powerful explanatory variables, predicting both stomatal conductance and WUEi. Our results clarify how the three-dimensional organization of tissues within the leaf has a direct impact on plant water use and carbon uptake. By identifying a suit of structural traits that influence important physiological functions, our findings can help to understand how conifers may respond to the pressures exerted by climate change.
Effective Regulation in Collaborative Learning: An Attempt to Determine the Fit of Regulation Challenges and Strategies

University students often self-organize in groups for collaborative exam preparation. To learn effectively, they need to regulate emerging learning challenges through the choice of fitting strategies. So far, little is known about what strategies fit which challenges. We present a theoretical account for the definition of fit between regulation challenges and strategies in collaborative learning, thereby differentiating between direct and indirect strategies, and test its validity in an empirical study. We asked 163 university students in 90 groups to rate the challenges they encountered in their self-organized group meetings, and to report strategies by aid of which they regulated their biggest challenge. Answers were coded into 26 strategy types. We found that students mostly used strategy types that directly address their biggest challenges. Multilevel-modelling indicated that direct strategies are associated with higher satisfaction for coordinationand comprehension-related challenges only, but not for motivational challenges.
Membrane surfaces regulate assembly of a ribonucleoprotein condensate

Biomolecular condensates organize biochemistry in time and space, yet little is known about how cells control either the position or scale of these assemblies. In cells, condensates often appear as dispersed, relatively small assemblies that do not grow (coarsen) into a single droplet despite their propensity to coalesce. Here we report that ribonucleoprotein condensates of the Q-rich protein Whi3 interact with the endoplasmic reticulum, prompting us to hypothesize that membrane association controls the position and size of condensates. Reconstitution of Whi3 condensates on supported lipid bilayers reveals that association with a diffusive lipid surface promotes condensation at both physiological ionic strength and protein concentration. Notably, these assemblies rapidly arrest, matching size distributions seen in cells. The timing of the arrest is influenced by the ordering of protein-protein and protein-RNA interactions and controlled by the slow diffusion of complexes induced by the membrane. This slowed diffusion limits both transfer of small protein-RNA complexes between condensates and their coalescence, thus driving coarsening to arrest. Our experiments reveal a tradeoff between locally-enhanced protein concentration at membranes, which favors condensation, and an accompanying reduction in diffusion, which restricts coarsening. Thus, membranes can maintain a population of small condensates in the absence of active mechanisms. Given that many condensates are bound to endomembranes, we predict that the biophysical properties of lipid bilayers are key for controlling condensate sizes throughout the cell. One sentence summary Assembly on a membrane surface positions and scales biomolecular condensates by controlling relative diffusion rates of proteins and nucleic acids.
Understanding CSCL Through the Lens of Research Syntheses

: Computer-supported collaborative learning (CSCL) forms a diverse field with researchers from different backgrounds using a variety of learning theories and research methods to design and analyze CSCL learning environments. The dynamic and active features of the field can lead to confusion about its identity and conclusions that can be drawn from the outcomes of CSCL research. Syntheses of CSCL research can help to answer questions about the prevalent topics and outcomes in the field. There are a number of synthesis methods to choose depending on the methods used in the primary studies as well as goals of the synthesis. Meta-synthesis is also available to better integrate findings obtained using different research methods. This symposium showcases a spectrum of different synthesis methods used in CSCL. Benefits and disadvantages of the synthesis methods will be discussed along with the question of how different synthesis methods can be used
Systems for Checking and Testing the Quality of Knowledge Based on Fuzzy Inference

In this article the problems of systems for assessing the quality of knowledge based on test control. The approaches to the development of intelligent systems for testing the quality of knowledge are examined, the functioning of which is based on the apparatus of fuzzy inference. A knowledge assessment model for fuzzy testing systems based on a four-point assessment system is proposed. Also presented are fuzzy systems of testing. In particular, adaptive systems, the advantages of using the fuzzy logic apparatus in building intelligent testing systems designed to improve the accuracy of testing and identifying the quality of knowledge by students. The method of complex assessment of students knowledge based on the Type 2 Tagaki-Sugeno fuzzy model are proposed.
Machine Learning Algorithms for Predicting the Results of COVID-19 Coronavirus Infection

The paper analyzes data collected from around the world on patients with COVID-19 The patients studied were of different ages, with different chronic diseases and symptoms, men and women A binary classifier has been developed that considers data on a person's health, symptoms, patient's age, and other properties and determines the patient's disease outcome by assigning it to one of two categories: fatal or not The work's practical value is to help hospitals and health facilities decide who needs care in the first place when the system is overcrowded and to eliminate delays in providing the necessary care © 2020 Copyright for this paper by its authors Use permitted under Creative Commons License Attribution 4 0 International (CC BY 4 0)
Mathematical Models of Pseudorandom Processes Behavior for Nonlinear Dynamical Systems

This paper considers the processes in maps, which are examples of nonlinear dynamical systems. Analysing dynamical systems, it is necessary to take into account and analyze properties of iterative functions that determine the length of nonrepetitive iterative process. It is shown that not only properties of functions, but also properties of numbers from the considered functions domain influence the nonlinear maps behavior. Also this work consider nonlinear maps as a background in the analysis of financial data and complex dynamical systems, such as stock exchange and economics.
Collective Knowledge Advancement through Shared Epistemic Agency: Socio-Semantic Network Analyses

This study examined how high-school students engage in collective knowledge advancement through shared epistemic agency during jigsaw instruction, and how their collective knowledge advancement (through shared epistemic agency) relates to learning outcomes. To achieve this, we applied a double-layered socio-semantic network analysis (SSNA). In the first layer of the analysis, we conducted an SSNA to numerically represent collective knowledge advancement and to compare group performances between different levels of learning outcomes. In the second layer, we carried out an Epistemic Network Analysis to examine the relationship between students’ shared epistemic agency and learning outcomes. The results revealed that high learning-outcome groups were engaged in epistemic actions to generate new ideas; this led them to quick and sustainable knowledge advancement.
On the Robustness to Misspecification of α-Posteriors and Their Variational Approximations

$\alpha$-posteriors and their variational approximations distort standard posterior inference by downweighting the likelihood and introducing variational approximation errors. We show that such distortions, if tuned appropriately, reduce the Kullback-Leibler (KL) divergence from the true, but perhaps infeasible, posterior distribution when there is potential parametric model misspecification. To make this point, we derive a Bernstein-von Mises theorem showing convergence in total variation distance of $\alpha$-posteriors and their variational approximations to limiting Gaussian distributions. We use these distributions to evaluate the KL divergence between true and reported posteriors. We show this divergence is minimized by choosing $\alpha$ strictly smaller than one, assuming there is a vanishingly small probability of model misspecification. The optimized value becomes smaller as the the misspecification becomes more severe. The optimized KL divergence increases logarithmically in the degree of misspecification and not linearly as with the usual posterior.
On the Φ-Stability and Related Conjectures

Given a convex function $\Phi:[0,1]\to\mathbb{R}$ and the mean $\mathbb{E}f(\mathbf{X})=a\in[0,1]$, which Boolean function $f$ maximizes the $\Phi$-stability $\mathbb{E}[\Phi(T_{\rho}f(\mathbf{X}))]$ of $f$? Here $\mathbf{X}$ is a random vector uniformly distributed on the discrete cube $\{-1,1\}^{n}$ and $T_{\rho}$ is the Bonami-Beckner operator. Special cases of this problem include the (symmetric and asymmetric) $\alpha$-stability problems and the ``Most Informative Boolean Function'' problem. In this paper, we provide several upper bounds for the maximal $\Phi$-stability. When specializing $\Phi$ to some particular forms, by these upper bounds, we partially resolve Mossel and O'Donnell's conjecture on $\alpha$-stability with $\alpha>2$, Li and M\'edard's conjecture on $\alpha$-stability with $1<\alpha<2$, and Courtade and Kumar's conjecture on the ``Most Informative Boolean Function'' which corresponds to a conjecture on $\alpha$-stability with $\alpha=1$. Our proofs are based on discrete Fourier analysis, optimization theory, and improvements of the Friedgut--Kalai--Naor (FKN) theorem. Our improvements of the FKN theorem are sharp or asymptotically sharp for certain cases.
Structure refinements of beryl by single-crystal neutron and X-ray diffraction

The crystal structure of beryl has been refined from single crystal neutron and x-ray diffraction data obtained on two samples with different alkali and H 2 O contents (morganite and aquamarine) in order to elucidate the ambiguities affecting the assignment of atomic species to the channel sites. Neutron data for morganite were obtained at 295 and 30K; neutron data for aquamarine and x-ray data for both samples were obtained at room temperature. The expected Li substitutions in the Be tetrahedral site and of Fe in the Al octahedral site were clearly confirmed by neutron data refinements
Synthesis and Photocatalytic Activity of Bi2Fe4O9 Using KOH as Mineralizer via Hydrothermal Method

Bi2Fe4O9 nanoplatelets were successfully prepared via hydrothermal method using KOH as the mineralizer. The in uence of KOH concentration on the morphology of the products was investigated. It is found that the thickness and edge length of as-prepared Bi2Fe4O9 nanoplatelets can be tailored by adjusting the KOH concentration. With increase in the KOH concentration from 3 to 9 M, the thickness of nanoplatelets increases gradually, whereas their edge length exhibits a trend of decrease. A possible in uencing mechanism of the KOH concentration on the morphology of Bi2Fe4O9 nanoplatelets is proposed on the basis of experimental results. The photocatalytic activity of Bi2Fe4O9 nanoplatelets was investigated by the degradation of methylene blue under simulated sunlight irradiation, indicating that they possess an appreciable photocatalytic activity. Furthermore, the as-prepared Bi2Fe4O9 nanoplatelets present good photocatalytic reusability. Magnetic hysteresis loop measurement shows that the Bi2Fe4O9 nanoplatelets exhibit weak ferromagnetic behavior at room temperature. [doi:10.2320/matertrans.M2016043]
Consumers’ attitude and purchase intention towards organic personal care products. An application of the S-O-R model

Purpose of the paper: Guided by the Stimulus-Organism-Response (S-O-R) model, the study investigated whether and how six environmental stimuli related to the consumers’ experience with organic personal care products influenced their attitudinal responses (hedonic and utilitarian) which, in turn, affected their buying behaviour. Methodology: The empirical research builds on an online survey with a sample of 209 consumers. A structural equation model was performed to analyse the data. Findings: Results showed that knowledge about organic PCP and sensory appeal significantly improved the utilitarian and hedonic attitude towards these products. Contextually, natural content attributes and quality perception positively influence utilitarian attitude. Finally, both the affective and functional attitudinal dimensions significantly increased the purchase intention. Research limits: Further research is recommended in order to measure the actual purchase behaviour and to extend the investigation to a larger sample that is representative of the general population. Moreover, longitudinal studies are required to examine whether changes in consumer attitude, perception and buying with regard to organic PCP happen in time. Practical implications: Highlighting the determinants of consumers’ attitude and purchase intention, the paper provides valuable insight to manufacturers and retailers for the increase in organic PCP market share. Originality of the paper: The study showed that the S-O-R model is an adequate theoretical framework to investigate the decision-making process in the context of organic PCP. Furthermore, the proposed theoretical model sheds light on the role of new relevant variables which affect the consumers’ evaluation towards these products and that have been neglected in past research.
Visual Outcomes After Phacoemulsification in Sanjiwani Hospital Gianyar, Bali, Indonesia

The rate of blindness and visual impairment due to cataract is still high, especially in developing countries such as Indonesia. Phacoemulsification is one of the most advanced cataract surgery methods currently available. This study aims to evaluate the result of visual acuity in post-phacoemulsification cataract patients in Sanjiwani Hospital. This retrospective study used data obtained from medical records of patients who underwent phacoemulsification between 2019-2020. There were 45 eyes from a total of 35 patients. Most patients were male with an average age of 71± 9.58 years old. Around 71.1% of samples obtained good outcome (visual acuity of ≥ 6/18) 6 weeks after surgery. Meanwhile, 26.6% obtained a borderline outcome (visual acuity of 6/18-6/60) and one person had a poor outcome (visual acuity of <6/60). No intraoperative complication was recorded. There were 2 postoperative complications in the form of IOL dislocation. This result revealed a low complication rate. However, the percentage of good outcome has not reached WHO’s recommendation, which is 80%. Further studies with larger sample size and more complete data will be good to evaluate visual outcomes of phacoemulsification more optimally.
APPLICATION OF METHODOLOGIES OF DIAGNOSTICS FOR PATIENTS WITH DIZZINESS

1Candidate of medical Sciences assistant of otorhinolaryngology of the Samarkand medical Institute, Uzbekistan 2,3Doctor of medical Sciences Professor of the Department of ear, throat and nose diseases of Tashkent pediatric Institute, Uzbekistan ABSTRACT: Dizziness is frequent reason of address to the neurologist. The study of principal reasons of dizziness became a research aim for patients. 75 patients appealings to the neurologist and otorhinolaryngologist in connection with complaints about dizziness of system character are inspected. The stated below clinical inspections allow to educe the most widespread reasons of system dizziness and in good time to suspect the critical for life of patient damages of central departments of vestibular analyzer.
Structural changes of cellulosic polysaccharides in sesame hull during roasting at various temperatures

This article reports a study of the degradation of roasted sesame hulls cellulosic polysaccharides contribution to the Maillard and caramelization reaction. In the present study, cellulosic polysaccharides were extracted from sesame hulls before and after roasting at various temperatures (160, 180, 200, and 220 °C). The structural variations of the cellulosic polysaccharides were elucidated by using the techniques: scanning electron microscope (SEM), high-performance anion-exchange chromatography, Fourier transform (FT-IR) spectrometer, carbon-13 nuclear magnetic resonance (CP/MAS 13C-NMR), and thermal gravimetric analysis. The pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) characterized and verified the chemical composition obtained from the polysaccharide degradation during roasting. The sugar analysis results showed that galacturonic acid, xylose, and rhamnose were more easily degraded than arabinose, galactose, glucose, and mannose. The morphology of the cellulosic polysaccharides shows irregular dispersed globular fragments after roasting by SEM observation. FT-IR and CP/MAS 13C-NMR spectra indicated the crystalline structure and linkages of the cellulose did not break down in comparison to amorphous cellulose that partly degraded. Abundant acetic acid and 3-furaldehyde were among the polysaccharide degradation products identified by Py-GC/MS. These chemical compounds were likely the significant contributors to caramelization and the Maillard reaction in sesame seed roasting.