Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of ages and masses via carbon and nitrogen abundances for 556 007 giants from LAMOST

Estimating ages for a large number of giants is of great importance for studying Galactic evolution. In this work, we determine stellar ages and masses for 556 007 giants from LAMOST Data Release 5 (DR5) with empirical relations estimated from chemical [C/N] abundance ratios. Our sample reveals the two well-known sequences in the age–[α/M] relation. The high-α sequence is composed of stars older than 8 Gyr and low-α sequence is composed of stars with age ranging from 0 Gyr to 13.8 Gyr. Our sample also shows a flat age–[M/H] relation up until 12 Gyr. We compare these distributions with Galactic Chemical Evolution models for reference. When looking at the spatial distribution of stars in 2 Gyr age bins, we find that young stars are concentrated towards the Galactic plane and older stars extend to higher height above and below the disk. We find a smooth transition of median Galactic height for different age bins, which suggests a strong age-dependence on Galactic scale height.
Linear and nonlinear models for forecasting the realized volatility of cryptocurrencies

Cryptocurrencies are known for their high fluctuating prices. In order to minimize the risk for investors, many empirical researchers proposed the realized volatility, calculated with intradaily log returns, as an approximation for the true volatility on the market. In this empirical paper we aim to make possibly the best forecast for the daily realized volatility in the next period and to find a good financial application for our predicted values. For achieving of these goals, some linear and nonlinear models are considered. We make use of the popular linear heterogenous autoregressive model (HAR-RV) and various recurrent neural networks (SRN, LSTM and GRU). Additionally, a hybrid model between the simplest feedforward neural network and the heterogenous autoregressive model is proposed. The results demonstrate superiority of the nonlinear models, whereas this is more obvious for the recurrent neural networks in low volatility times with reduced training data set. The forecasted values are used for calculating the Value at Risk for a portfolio of cryptocurrencies. Unfortunately, the Unconditional coverage test and the Conditional coverage test reject the null hypotheses that the forecasts for future daily realized volatility are a suitable approximation for calculating Value at Risk. The noise and the jumps in the data are pointed as possible reasons for these results, therefore, as a starting point for further research, application of more complex models like HAR-RV-J, HAR-RV-CJ and deep recurrent neural networks is suggested.
Comparison of different predictive tests for difficult airways in pediatrics

Objective: There are few studies regarding the use of predictive tests for difficult airways in pediatrics. The aim of this study was to investigate the effectiveness of the modified Mallampati test (MMT), the upper lip bite test (ULBT) and anthropometric measurements of the head and neck in the prediction of difficult airways in children. Methods: Forty-eight pediatric patients who underwent elective surgery under general anesthesia with endotracheal intubation were recruited for the study. During the preanesthetic evaluation, airway status was evaluated using three methods: MMT, ULBT and anthropometric measurements of the head and neck. Laryngoscopy was performed with a single blade of a videolaryngoscope and airway status was evaluated using the Cormack-Lehane classification. All patients were then classified into two groups: difficult airway or easy airway. Results: Ten (20.8%) patients were classified as the difficult airway group. In this group, 80% of the patients had MMT grade 3-4 (p=0.001) while 50% of the patients were classified as ULBT 3 (p=0.000). Interincisor distance (ID), hyomental distance (HMD), distance from ear tragus to the corner of the mouth (DTM) and distance from frontal plane to chin (DFC) were significantly different between the groups (p<0.05). In ROC curve analysis, ULBT had the largest area under the curve (AUC=0.880). Conclusion: ULBT, MMT, HMD and ID were the most consistent predictors of difficult airway status. ULBT was superior to other tests because of its larger AUC and higher sensitivity and specificity rates. However, difficulty in applicability in young children seemed to be the most important limitation of both ULBT and MMT.
Preliminary Results of CitraVesTM Effects on Low Density Lipoprotein Cholesterol and Waist Circumference in Healthy Subjects after 12 Weeks: A Pilot Open-Label Study

Appropriate monitoring and control of modifiable risk factors, such as the level of lowdensity lipoprotein cholesterol (LDL-C) and other types of dyslipidemia, have an important role in the prevention of cardiovascular diseases (CVD). Recently, various nutraceuticals with lipid-lowering effects have gained attention. In addition to the plant-derived bioactive compounds, recent studies suggested that plant cells are able to release small lipoproteic structures named extracellular vesicles (EVs). The interaction between EVs and mammalian cells could lead to beneficial effects through anti-inflammatory and antioxidant activities. The present study aimed to assess the safety of the new patented plant-based product citraVesTM, containing extracellular vesicles (EVs) from Citrus limon (L.) Osbeck juice, and to investigate its ability to modulate different CV risk factors in healthy subjects. A cohort of 20 healthy volunteers was recruited in a prospective open-label study. All participants received the supplement in a spray-dried formulation at a stable dose of 1000 mg/day for 3 months. Anthropometric and hematobiochemical parameters were analyzed at the baseline and after the follow-up period of 1 and 3 months. We observed that the supplement has an effect on two key factors of cardiometabolic risk in healthy subjects. A significant change in waist circumference was found in women after 4 (85.4 [79.9, 91.0] cm, p < 0.005) and 12 (85.0 [80.0, 90.0] cm, p < 0.0005) weeks, when compared to the baseline value (87.6 [81.7, 93.6] cm). No difference was found in men (baseline: 100.3 [95.4, 105.2] cm; 4 weeks: 102.0 [95.7, 108.3] cm; 12 weeks: 100.0 [95.3, 104.7] cm). The level of LDL-C was significantly lower at 12 weeks versus 4 weeks (p = 0.0064). Our study evaluated, for the first time, the effects of a natural product containing plant-derived EVs on modifiable risk factors in healthy volunteers. The results support the use of EV extracts to manage cardiometabolic risk factors successfully. Metabolites 2021, 11, 276. https://doi.org/10.3390/metabo11050276 https://www.mdpi. com/journal/metabolites Metabolites 2021, 11, 276 2 of 14
A new variational approach and its application toheavy quarkonia

By combining the variational principle with Heisenberg uncertainty principle in an effective Hamiltonian for heavy flavored mesons, we in- troduce a framework to estimate masses and radii of these states from an analytical constraint. In a novel manner, a model for quark velocity and a model for quark momentum width are introduced. These kinemat- ical model parameters are obtained as analytical functions of inter quark separation in heavy quarkonia. The values of such quark parameters are then used in the calculation of S -wave annihilation decay rates of \bar{ c} c and\bar{ b} b . To test the accuracy of our technique we first calculate the spin av eraged masses, scalar radii and annihilation decay rates of charmonium and bottomonium without and with relativistic corrections by solving the Schrodinger wave equation with the appropriate parametrization of the Song-Lin potential. The Schrodinger wave equation is solved numerically with the matrix Numerov method and we observe a good agreement with the experimental measurements and other theoretical calculations and ex tract strong running coupling constant for \bar{ c} c and \bar{ b} b systems. In non rel- ativistic settings, heavy meson spectra have been obtained and extended to rather higher excited states within our framework by using bare masses of c and b quarks which we have extracted from analysis of experimental data
Diffusion and transport phenomena in a collisional magnetoplasma with temperature anisotropy

The theory of collisional cross field diffusion and transport of a fully ionised singly charged plasma particles is analysed theoretically al the onsel of an induced anisotropy (T ∥ ≠T ⊥ ) in plasma temperatures where T ∥ and T ⊥ represent the components of temperature along the magnetic field direction and the direction perpendicular to it, respectively. The modified diffusion transport coefficients like the electrical resisitivity (η ⊥ and thermal conductivity (K) are found to decrease significantly with increase in the thermal ratio (T ∥ /T ⊥ ) while both the E×B drift velocity and the thermoelectric coefficient (λ) remain independent of the thermal anisotropy. However, in the limiting approximation (T ∥ =T ⊥ ), the results agree with the early isotropic works of Rosenbluth and Kaufmann, Phys Rev, I (1958) 109. Goldstone and Rutherford [IOP Publishing 1995, Braginskil (1965)].
Development of an OF-CEAS laser spectrometer for water vapor isotope measurements at low water concentrations

The determination of the isotopic composition of water vapor is an important tool in atmospheric research. The isotopic composition of water in Antarctic or Arctic glacial ice can be used as a paleo-thermometer in the reconstruction of climate changes in the past. The isotope ratios of water vapor in the atmosphere provide information about the water cycle and are an important factor for atmospheric circulation models. This thesis describes the development of an innovative, highly sensitive infrared laser spectrometer, based on the method of Optical Feedback Cavity Enhanced Absorption Spectroscopy, for the quantitative determination of water isotopes in very dry air. Such measurements are not possible with conventional isotope ratio mass spectrometry, nor with commercially available laser instruments. We present a general characterization of the instrument, as well as a detailed discussion of the dependence of the isotopic measurement on the water concentration at which the measurements are performed. We also describe a novel calibration system based on nanoliter syringe pumps, designed to generate water vapor of known isotopic composition in a concentration range from 5 to 15 000 ppmv. This newly developed equipment is used in the context of this thesis for measurements of the atmospheric water isotopic composition at the Norwegian station Troll in Antarctica and as part of the international ISOCLOUD project to study (super) saturation effects during cloud formation in the AIDA simulation chamber of the Karlsruhe Institute of Technology. We conclude with a discussion of the optimal measurement strategy and give an outlook for the future.
Benefits of Cellular Telecommunication and Smart Card Data for Travel Behaviour Analysis

This paper proposes the estimation of trip origin-destination matrices using big data through two case studies. In the first, trip matrices are estimated from mobile network data and compared with household travel survey results. In the second, public transport trip matrices are derived from smart card data and compared with passenger survey data. The paper concludes that sample size and longitudinal data collection are big data’s main strengths, yet are limited by privacy protection constraints and by the need to control for biases in the sample.
Polymorphism study of Fec X gene in indigenous sheep of Assam

The present study was conducted to check the polymorphism of Fec X gene in the indigenous sheep breeds of Assam. A total of 50 unrelated sheep covering Barpeta, Bongaigaon, Goalpara, Hekera and Kamrup districts of Assam was taken into consideration for the research work. Blood samples were collected and genomic DNA was isolated. PCR amplification of the DNA samples produced 141 bp amplified product. The PCR-RFLP technique was employed using Hinf1 restriction enzyme which resulted into a single type of banding pattern with two fragments of 110 and 31 bp in all the samples studied. Fec X gene was found to be monomorphic in the studied population.
Comparison of Resistance to Sliding between Brackets and Archwires Utilizing Various Ligature Materials

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Wastewater-based epidemiology for novel Coronavirus detection in wastewater

The entire world is reeling under the worst pandemic of last 100 years. Over 128 million people have been infected with it and 2.8 million deaths have already taken place, till 30th March 2021. The identification of materials positive cases is the first step towards its containment and treatment. However, testing of individuals is an extensive, expensive and time-consuming exercise. In addition, societal taboos are also associated with infected individuals resulting in very few people volunteering for testing, esp. in the developing and under-developed world. An alternative approach that circumvents individual testing is the wastewater-based epidemiology. A state-of-the-art review of this method is provided in context of its utility for COVID-19 detection. This technique relies on collecting and testing samples from sewers and/or wastewater treatment plants for the presence of pathogens and then using that data to determine and predict the spread of the infection, thereby allowing the provision of appropriate containment and treatment steps. The study covers key aspects of wastewater-based epidemiology application for COVID-19 detection including its need, detailed process of detection and assessment, data analysis, economics and challenges to its application. Findings from a number of case studies are presented to elucidate the utility of this technique. It is clearly seen that WBE-based approach is a much better strategy as compared to individual testing and can be adopted to prevent further spread of Covid-19. The work is expected to further emphasize the application of this method for COVID (and other pandemic) detection and implementing containment strategies. This is clearly a much more economical and non-intrusive approach as compared to the individual testing. ==========================================================================================COPYRIGHTS©2021 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers. ==========================================================================================
INCORPORATION AND RELEASE KINETICS OF ALPHA-BISABOLOL FROM PCL AND CHITOSAN/GUAR GUM MEMBRANES

Abstract - Alpha-bisabolol, an anti-inflammatory and antioxidant compound extracted from candeia trees ( Eremanthus erythropappus ), was incorporated into hydrophobic polycaprolactone (PCL) and hydrophilic chitosan/guar gum (Ch-G) membranes aiming at the production of bioactive wound dressings. The incorporation efficiency achieved a maximum of ca . 18% (1 gram of alpha-bisabolol per gram of membrane) for Ch-G membranes. For PCL membranes, all of the active compound added was retained (0.2 gram of alpha-bisabolol per gram of membrane). Alpha-bisabolol release in phosphate-buffered saline was relatively slow in both cases, reaching around 6% and 24% after 120 hours respectively for PCL and Ch-G membranes presenting equivalent initial alpha-bisabolol/membrane mass ratios. Both formulations were capable of releasing alpha-bisabolol in the typically recommended topical dose range (from 1 to 10 grams of alpha-bisabolol per gram of vehicle). The extended release periods observed are advantageous, allowing less frequent dressing changes and contributing to turn the treatment more comfortable for the patient.
MASTERARBEIT / MASTER’S THESIS

3 Introduction . 4 Methods . 11 Results . 22 Discussion . 28 Acknowledgements . 38 References . 39 Appendices . 51 Zusammenfassung . 58 Curriculum Vitae . 59 Effects of Paced Respiration on Attentional Impulse Control Dominic Reichl
Fatigued Random Walks in Hypergraphs: A Neuronal Analogy to Improve Retrieval Performance

Hypergraphs are data structures capable of capturing supra-dyadic relations. We can use them to model binary relations, but also to model groups of entities, as well as the intersections between these groups or the contained subgroups. In previous work, we explored the usage of hypergraphs as an indexing data structure, in particular one that was capable of seamlessly integrating text, entities and their relations to support entity-oriented search tasks. As more information is added to the hypergraph, however, it not only increases in size, but it also becomes denser, making the task of efficiently ranking nodes or hyperedges more complex. Random walks can effectively capture network structure, without compromising performance, or at least providing a tunable balance between efficiency and effectiveness, within a nondeterministic universe. For a higher effectiveness, a higher number of random walks is usually required, which often results in lower efficiency. Inspired by von Neumann and the neuron in the brain, we propose and study the usage of node and hyperedge fatigue as a way to temporarily constrict random walks during keyword-based ad hoc retrieval. We found that we were able to improve search time by a factor of 32, but also worsen MAP by a factor of 8. Moreover, by distinguishing between fatigue in nodes and hyperedges, we are able to find that, for hyperedge ranking tasks, we consistently obtained lower MAP scores when increasing fatigue for nodes. On the other hand, the overall impact of hyperedge fatigue was slightly positive, although it also slightly worsened efficiency.
Effect of growth retardants on growth, flowering and bulb yield of Asiatic Lilium

The main focus in lily cultivation has been on cut flower production and other attributes like pot culture and garden display have not been addressed so seriously resulting in damage to the flowers during medium and high wind storms particularly to the cultivars which have long stems. The present investigation on effect of growth retardants on growth, flowering and bulb yield of Asiatic Lilium was carried out at the Experimental field of faculty of agriculture Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Wadura campus. The results obtained revealed that growth retardants (paclobutrazol and cycocel) had significant effects on growth, flowering and bulb characteristics of Asiatic lilium. The treatment combination paclobutrazol (60ppm) and cycocel (200ppm) took minimum days to bulb sprouting(17.66 days), produced shortest plant(45.18cm),less number of leaves (35.00),lesser number of days to colour break(48.00 days),minimum number of days to anthesis (52days),maximum number of bulbs plant (3.91) and diameter of bulb (6.33cm) with highest propagation coefficient (3.91) whereas maximum flower diamete r (15.27cm),weight of bulb (98.10 g) and maximum scale size (2.03)was obtained under T7 (cycocel@ 200ppm). On the other hand number of daughter bulbs produced bulb-was observed under T4 i.e., paclobutrazol @ 60ppm. However there were no significant effects of growth retardants on number of flowers plant.
The Potential use of Bacterial Diversity Analysis of Soft Rotted Potato Tubers and Their Geocaulospheres

Sanja Marković University of Belgrade Institute for Multidisciplinary Research: Univerzitet u Beogradu Institut za multidisciplinarna istrazivanja Tatjana Popović (  tanjaizbis@gmail.com ) Institut za zastitu Bilja I Zivotnu Sredinu https://orcid.org/0000-0003-0125-5905 Tanja Berić Univerzitet u Beogradu Bioloski Fakultet Ivica Dimkić Univerzitet u Beogradu Bioloski Fakultet Aleksandra Jelušić University of Belgrade Institute for Multidisciplinary Research: Univerzitet u Beogradu Institut za multidisciplinarna istrazivanja Renata Iličić Univerzitet u Novom Sadu Poljoprivredni fakultet Slaviša Stanković Univerzitet u Beogradu Bioloski Fakultet
Spoken Moments: Learning Joint Audio-Visual Representations from Video Descriptions

When people observe events, they are able to abstract key information and build concise summaries of what is happening. These summaries include contextual and semantic information describing the important high-level details (what, where, who and how) of the observed event and exclude background information that is deemed unimportant to the observer. With this in mind, the descriptions people generate for videos of different dynamic events can greatly improve our understanding of the key information of interest in each video. These descriptions can be captured in captions that provide expanded attributes for video labeling (e.g. actions/objects/scenes/sentiment/etc.) while allowing us to gain new insight into what people find important or necessary to summarize specific events. Existing caption datasets for video understanding are either small in scale or restricted to a specific domain. To address this, we present the Spoken Moments (S-MiT) dataset of 500k spoken captions each attributed to a unique short video depicting a broad range of different events. We collect our descriptions using audio recordings to ensure that they remain as natural and concise as possible while allowing us to scale the size of a large classification dataset. In order to utilize our proposed dataset, we present a novel Adaptive Mean Margin (AMM) approach to contrastive learning and evaluate our models on video/caption retrieval on multiple datasets. We show that our AMM approach consistently improves our results and that models trained on our Spoken Moments dataset generalize better than those trained on other video-caption datasets.http://moments.csail. mit.edu/spoken.html