Miracle-dz/UniFAR-FTUs huggingface dataset:
Algorithms for resource-constrained domain-specific knowledge management

A central problem in computational biology is how to extract information from evergrowing amounts of data. Not only is there a huge amount of laboratory data requiring processing, one also has to deal with millions of biomedical publications – especially in highly active areas of research. While currently available text mining technology facilitates large-scale exploration of textual data, no solution is currently available allowing one to analyze only a small corpus of scientific textual information without having to rely on complex frameworks that are hard to use without a dedicated cluster of servers. Therefore, these technologies are virtually inapplicable for field use or tasks where only a comparatively small domainspecific corpus needs to be queried, especially on devices with limited amounts of resources. Moreover, most available text mining packages are built for use cases which are either too general for specific biological tasks (e. g. Google) or use methods only being applicable for specific areas of research. This thesis presents algorithms and a proof-of-concept reference implementation named “Translatron” using a highly customizable and portable approach to text mining that is optimized for resource-constrained standalone devices running domain-specific algorithms with small to medium-sized datasets.
RATIONALITY OF SURVEY BASED INFLATION EXPECTATIONS OF EIGHTEEN

This study investigates rationality of inflation expectations of 18 emerging countries inflation rates using ten years (11/2001 – 5/2012) of inflation data. Given the nature of the data, we use the panel method to assess the relation between actual and the expected inflation rates. We perform various diagnostic tests to identify the appropriate panel test for the data. We use a recently developed panel regression method based on simple OLS techniques but derive standard errors corrected for serial correlation, panel heterogeneity and cross-sectional dependence. Results of the unbiasedness test and the efficiency test indicate that forecasts are rational for one month ahead forecast horizon. 1 Work-in-progress. Please do not cite. 2 Corresponding author. Tel: 478-301-5541; Email: rahman_ms@mercer.edu
A new “zero-strain” material for electrochemical lithium insertion

A new “zero-strain” system, spinel Li1+xRh2O4, is found as an insertion material for lithium ions. A very small volume change of ca. 0.5% is observed in the two-phase reaction process. The “zero-strain” behavior is likely induced by itinerant t2g electrons with a suppressed Jahn–Teller effect.
Emotional Intelligence and its Relationship with Conflict Management and Occupational Stress: A Meta-Analysis

The current study used meta-analysis to examine the relationship between Emotional Intelligence (EI) and Conflict Management (CM) and emotional intelligence and Occupational Stress (OS). A total of 14 studies examining the relationship between on EI and CM and 39 studies on EI and OS were considered. For Emotional Intelligence and Conflict Management, total sample size consisted of 5,371 participants, yielding 58 effect sizes and for EI and OS, total sample size consisted of 9,930 participants, yielding 53 effect sizes. The studies that had been published from 2002 to 2017 were selected. To identify relevant studies for meta-analysis, a computerized bibliographic keyword search using Elsevier, Science Direct, Emerald Insight, Sage Publications, Tailor & Francis, PubMed, Springer, EBSCOhost and Social Science Citation Index was conducted. Internet search was done using Google Scholar. The results of the present study supported the hypotheses that there is significant and positive relationship between EI and conflict management and significant and negative relationship between EI and occupational stress.
Eucalyptus globulus Kraft Pulp Residual Lignin. Part 2. Modification of Residual Lignin Structure in Oxygen Bleaching

Summary Residual lignins were isolated from unbleached and oxygen-bleached Eucalyptus kraft pulps by acid hydrolysis. The structural changes and degradation of residual lignin occurring during kraft pulping and oxygen bleaching were followed and identified by elemental analysis, residual carbohydrate analysis, molecular mass distribution, as well as qualitative and quantitative solution 13C NMR. The dissolved lignins in the kraft cooked and oxygen bleached liquors were also studied and compared with the corresponding residual lignins. Milled wood lignin treated under acid hydrolysis conditions served as a reference for the structural comparison. The results show that etherified syringyl structures were quite resistant towards degradation in the oxygen bleaching, causing little depolymerisation in residual lignin and a small increase in carboxylic acid content, but producing appreciable amounts of saturated aliphatic methylene groups.
Quantifying the Macroeconomic Effects of the COVID-19 Lockdown: Comparative Simulations of the Estimated Galí-Smets- Wouters Model

This paper considers 3 scenarios regarding the duration of the COVID-19 pandemic lockdown, staying for 1, 2 or 3 quarters, and 2 types of exceptionally rare and devastating disruptions in employment modeled as adverse labor supply shocks, a temporary one with negligible loss in the labor force due to deaths or a permanent one, with significant loss from deaths. The temporary labor supply shock simulations delimit a lower bound, designed to match about 1/4 of the labor force unable to work, and an upper bound, matching about 3/4 of the labor force made economically inactive, broadly consistent with estimates. The permanent labor supply shock is designed to match, in 3 scenarios again, up to 1% loss of the labor force due to mortality, twice milder than the Spanish flu 2% death rate. Estimated calibrations of the Galí-Smets-Wouters (2012) model with indivisible labor for 5 major and most affected by the COVID-19 pandemic economies are simulated: the US, France, Germany, Italy and Spain. The simulations suggest that even in the most optimistic scenario of a brief (lasting for 1 quarter) and mild (with 1/4 of the labor force unable to work) lockdown, the loss of per-capita consumption (6-7% in annualized terms down from the long-run trend in the impact quarter) and per-capita output (3-4% down) will be quite damaging, but recoverable relatively quickly, in 1-2 years. In the most pessimistic simulated scenario of temporary loss the effects will be 10-15 times more devastating, and the loss of output and consumption will persist beyond 10-15 years. Permanent loss of up to 1.5 percentage points of per-capita consumption and output characterizes the simulated permanent labor supply shock.
Optimized and efficient deblurring through constraint conditional modelling

Image deburring technique refers to restoring an image from the degraded version named blurred. Blurring can be caused due to various phenomena such as optical system, motion blur and other phenomena. Moreover, to deblur the image it is essential to know the blurring process characteristics and it is one of the difficult task. In past several deblurring algorithm have been proposed to approximate the kernel blur, however they lack the efficiency and expensive to be applied for the real world scenario. In this paper, we have proposed a CCM (constraint conditional model) to deblur the image; it learns the direct mapping from the degraded to the absolute clean image. Moreover, the main aim of CCM is to restore the image in its original form, the best advantage of CCM is that it provides handsome tradeoff between the image quality and efficiency. Moreover CCM is evaluated on the three different standard datasets by considering the different performance metrics and through the comparison analysis observation has made that CCM approach outperforms the other techniques.
Factors influencing COVID-19 vaccination uptake in an elderly sample in Poland

Backgrounds: This research represents an investigation into potential predictors for the uptake of the COVID-19 vaccination in Poland, following the instigation of policies to encourage the over-seventies to be vaccinated. Methods: Individuals participated in cross-sectional structured interviews. 1427 respondents were questioned for determining vaccination uptake, revealing attitudes regarding vaccination, where information was sourced from, health status and behavior, demographics and socio-economic profiles. Results: Selected predictors for acceptance of the vaccination were: being talked through the importance of the vaccination and potential side-effects by a medical professional; sharing living space with others; having a high ranking occupation; suffering from chronic illnesses; being able to access medical services by driving or walking rather than using public transport or relying on others. Those who opted not to be vaccinated most frequently justify their decision by saying that they were concerned about the efficacy of the vaccine or that they were worried about side-effects. Conclusions: It appears that the current nationwide campaign has successfully raised awareness regarding the vaccine, but this research indicates that a more information-based campaign, focusing on evidence of the vaccine's efficacy and the non-serious nature of all side-effects, could lead to improved uptake of the COVID-19 vaccine.
Computational approaches to study adsorption in MOFs with unsaturated metal sites

Metal-organic frameworks (MOFs) with coordinatively unsaturated sites (CUS) offer interesting possibilities for tuning the affinity of these materials towards certain adsorbates, potentially increasing their selectivity and storage capacity. From a modelling point of view, however, they pose a significant challenge due to the inability of conventional force-fields for dealing with these specific interactions. In this paper, we review recent developments in the application of quantum-mechanical (QM) methods and classical molecular simulations to understand and predict adsorption in MOFs with CUS. We find that hybrid approaches that incorporate QM-based information into classical models are able to provide dramatically improved adsorption predictions relative to conventional force-fields, while yielding a realistic description of the adsorption mechanism in these materials.
The beneficial effects of aged black garlic extract on obesity and hyperlipidemia in rats fed a high-fat diet

The present study was conducted to evaluate the effectiveness of aged black garlic (ABG) extract in alleviating obesity and hyperlipidemia, and regulating antioxidant properties in rats fed high-fat diet. Six-week old male Sprague-Dawley rats were separately fed for 5 weeks with two types of diets; a normal diet (ND) or high-fat diet (HD). Then rats fed HD were randomly assigned into 5 groups and fed with one of the followings: a carrier (control), ABG extract (100, 250 and 500 mg/kg body weight) or simvastatin (1 mg/kg body weight) for another 5 weeks. The body and fat-pad weight, lipid parameter, antioxidant enzyme activity and lipid peroxidation (LPO) in serum and hepatic was investigated. ABG extract significantly lowered body and adipose tissue weight relative to the control. ABG extract significantly improved lipid profile by decreasing serum triglyceride and hepatic total cholesterol compared with the control. ABG extract-treated groups were also observed significant increases glutathione (GSH):oxidized GSH ratio in serum and hepatic compared with the control and near to the level of the normal. Consumption of ABG extract significantly decreased serum LPO level relative to the control. Based on these results, we suggest that the administration of ABG extract improves the body weight gain and dyslipidemia through the suppression of body fat and alteration in lipid profiles and antioxidant defense system.
The crystal structure of p-nitroaniline, NO2.C6H4.NH2

p-Nitroaniline forms monoclinic crystals, space group C2h5–P21/n, with four asymmetric molecules in the unit cell. A quantitative X-ray investigation based on visual intensity measurements of about 250 reflections from the axial zones has led to a complete determination of the structure, and the results have been refined by the double Fourier series method, which gives projections of the structure along the three crystal axes. The co-ordinates of the atoms, the molecular dimensions, and the intermolecular distances are given. The nitro-group is symmetrical and lies in the plane of the benzene ring. In addition to rather weak hydrogen bridges connecting the oxygen atoms of the nitro-group to the amino-groups of adjoining molecules, there is a very close approach (2.7–3.0 A.) between one of the nitro-oxygen atoms and three of the aromatic carbon atoms of an adjoining molecule. This appears to be an intermolecular attraction of a new type, and it is suggested that a similar mechanism may be responsible for the formation of a large class of the molecular compounds that are formed between aromatic nitro-compounds and polycyclic hydrocarbons.
Effects of tribenuron-methyl treatment on glutathione S-transferase (GST) activities in some wheat and barley varieties

For efficient and profitable crop production, appropriate weed management is essential. Today, herbicides are an integral part of modern farming practice globally, as they assure the convenient method of weed control chemically. Glutathione S-transferases (GSTs, EC.2.5.1.18) are a superfamily of multifunctional enzymes that detoxify endo- and xeno-biotic compounds by conjugating glutathione (GSH) to a hydrophobic substrate. Plant GSTs have been a focus of attention because of their roles in herbicide detoxification and environmental safety. In this study, the application of herbicide called tribenuron-methyl to the cultivars of wheat (Triticum aestivum L. cv. Izgi-2001, Triticum aestivum L. cv. Alpu-2001) and barley plants (Hordeum vulgare L. cv. Bilgi-91, Hordeum vulgare L. cv. Kalayci-97) caused an increase in GST activities of both in roots and shoots. Total GSH and protein contents were also determined for all above-mentioned plants. As a conclusion, our results indicate that depending on the herbicide itself, treatment conditions and the origin of the plant, tribenuron-methyl had an effect on the parameters measured in this study, including the GST activities and synthesis of GSH. The maximum increase in enzyme activity was observed in herbicide-treated Triticum aestivum L. cv. Izgi-2001 roots: 192 % of control with a tribenuron-methyl concentration of 1.5 M. However, further investigations are needed to elucidate the presence of specific tribenuron-methyl GST isozymes in this plant.
Optimization Under Uncertainty Spring 2020 Lecture 10-11 : Chance-Constrained Programming ( CCPs )

This is a totally different kind of problem because the constraint is in a probabilistic form, rather than the deterministic form, i.e. g(x, ξ) ≤ 0, as we learned in stochastic optimization. Intuitively, the constraint here can be interpreted as a “reliability constraint” (or “risk constraint”). There are many applications that CCPs can fit in, for example, financial risk management, weather forecast [Gel12]. To facilitate the understanding of chance constraints, let’s consider the following toy example.
Mechanical Stratigraphy Controls Normal Fault Growth and Dimensions, Outer Kwanza Basin, Offshore Angola

Mechanical stratigraphy controls the growth patterns and dimensions of relatively small normal faults, yet how it influences the development of much larger structures remains unclear. Here, we use 3D seismic reflection data from the Outer Kwanza Basin, offshore Angola to constrain the geometry and kinematics of several normal faults formed in a deep‐water clastic succession. The faults are up to 6.3‐km long and 1.9‐km tall and have up to 44 m of throw. Aspect ratios and lower‐tip throw gradients are greater for faults that terminate downward at a c. 100 m thick, mass‐transport complex (MTC; up to 5.2 and 0.12) than for those that offset it (up to 2.7 and 0.01). Faults that offset the MTC invariably have >30 m of throw. Based on their geometric properties and throw patterns, we interpret that the faults nucleated above the MTC and propagated down toward it. Upon encountering this unit, which we infer behaved in a more ductile manner than encasing strata, tip propagation was halted until tip stresses were sufficiently high (corresponding to minimum throw of c. 30 m) to breach it. Faults with smaller throw were unable to breach the MTC. We argue that using only geometric criteria to determine fault growth patterns can mask the significant control mechanical stratigraphy has on fault kinematics. Mechanical stratigraphy is therefore a key control on the growth of large, seismic‐scale normal faults, in a similar way to that observed for far smaller structures.
Vertical Product Differentiation of Complementary Goods

The paper introduces a model of vertical product differentiation as an extension of Shaked and Sutton (1982) that allows for representation of the consumer demand for a bundle of several complementary goods sold in separate markets. Two key differences are identified in the equilibrium outcome. First, it is shown that the condition on market size derived by Shaked and Sutton (1982) for having duopoly at equilibrium in an independent market might not be sufficient to restrict down to two the equilibrium number of the possible bundles of several complementary goods. Therefore, to have further decreased number of the salable bundles, the mutual size of the markets must satisfy a more restrictive condition at which all the complementary markets except one have a monopoly structure at equilibrium. Second, the solution of the model implies that as long as one of the related markets has a monopoly structure and its size exceeds half of its upper bound, this market would not be covered at its pricing-stage equilibrium. Since the good sold in this market is a complement to the goods sold in other related markets, however, the latter would not be covered at equilibrium, either. The described result diverges from the one supported by Shaked and Sutton (1982) for a single independent market where at the same conditions exactly two goods would have sales, gain positive profits and cover the whole market at equilibrium.
Surface-Enhanced Raman Scattering from Uniform Gold and Silver Nanoparticle-Coated Substrates

Large-area gold and silver nanoparticles inside periodical silicon microhole arrays were prepared via simple electrodeposition. Such metal nanoparticles within Si microholes showed a strong surface-enhanced Raman scattering (SERS) effect, which enabled the detection of rhodamine at 10 ―8 M and 10 ―9 M on substrates of AuNPs and AgNPs, respectively. The SERS activity of the substrates depended on the metal particle morphology. Microfabrication combined with electrodeposition appears to be a viable approach for preparing reproducible SERS substrates for sensitive Raman detection.
The 800 pc long tidal tails of the Hyades star cluster

The tidal tails of stellar clusters provide an important tool for studying the birth conditions of the clusters and their evolution, coupling, and interaction with the Galactic potential. The Gaia satellite, with its high-quality astrometric data, opened this field of study, allowing us to observe large-scale tidal tails. Theoretical models of tidal-tail formation and evolution are available. However, the exact appearance of tidal features as seen in the Gaia catalogue has not yet been studied. Here we present the N-body evolution of a Hyades-like stellar cluster with backward-integrated initial conditions on a realistic 3D orbit in the Milky Way galaxy computed within the AMUSE framework. For the first time, we explore the effect of the initial cluster rotation and the presence of lumps in the Galactic potential on the formation and evolution of tidal tails. For all of our simulations we present Gaia observables and derived parameters in the convergent point (CP) diagram. We show that the tidal tails are not naturally clustered in any coordinate system and that they can span up to 40 km s−1 relative to the cluster centre in proper motions for a cluster age of 600–700 Myr. Models with initial rotation result in significant differences in the cluster mass loss and follow different angular momentum time evolution. Thus the orientation of the tidal tails relative to the motion vector of the cluster and the current cluster angular momentum constrain the initial rotation of the cluster. We highlight the use of the standard CP method in searches for co-moving groups and introduce a new compact CP (CCP) method that accounts for internal kinematics based on an assumed model. Using the CCP method, we are able to recover candidate members of the Hyades tidal tails in the Gaia Data Release 2 and early Data Release 3 (eDR3) reaching a total extent of almost 1 kpc. We confirm the previously noted asymmetry in the detected tidal tails. In the eDR3 data we recovered spatial overdensities in the leading and trailing tails that are kinematically consistent with being epicyclic overdensities and thus would present candidates for the first such detection in an open star cluster. We show that the epicyclic overdensities are able to provide constraints not only on the cluster properties, but also on the Galactic potential. Finally, based on N-body simulations, a close encounter with a massive Galactic lump can explain the observed asymmetry in the tidal tails of the Hyades.
Adaptive Illumination based Depth Sensing using Deep Learning

Dense depth map capture is challenging in existing active sparse illumination based depth acquisition techniques, such as LiDAR. Various techniques have been proposed to estimate a dense depth map based on fusion of the sparse depth map measurement with the RGB image. Recent advances in hardware enable adaptive depth measurements resulting in further improvement of the dense depth map estimation. In this paper, we study the topic of estimating dense depth from depth sampling. The adaptive sparse depth sampling network is jointly trained with a fusion network of an RGB image and sparse depth, to generate optimal adaptive sampling masks. We show that such adaptive sampling masks can generalize well to many RGB and sparse depth fusion algorithms under a variety of sampling rates (as low as 0 . 0625% ). The proposed adaptive sampling method is fully differentiable and ﬂexible to be trained end-to-end with upstream perception algorithms.