Miracle-dz/UniFAR-FTUs huggingface dataset:
Stalling of Globular Cluster Orbits in Dwarf Galaxies

We apply the Tremaine–Weinberg theory of dynamical friction to compute the orbital decay of a globular cluster (GC) on an initially circular orbit inside a cored spherical galaxy with isotropic stellar velocities. The retarding torque on the GC, , is a function of its orbital radius . The torque is exerted by stars whose orbits are resonant with the GC’s orbit and given as a sum over the infinitely many possible resonances by the Lynden-Bell–Kalnajs (LBK) formula. We calculate the LBK torque and determine for a GC of mass and an isochrone galaxy of core mass and core radius . (i) When , many strong resonances are active, and as expected, , the classical Chandrasekhar torque. (ii) For , comes mostly from stars nearly corotating with the GC, trailing or leading it slightly; trailing resonances exert stronger torques. (iii) As decreases, the number and strength of resonances drop, so also decreases, with at , a characteristic “filtering” radius. (iv) Many resonances cease to exist inside this includes all leading and low-order trailing ones. (v) The higher-order trailing resonances inside are very weak, with at . (vi) Inspiral times for to decay from to far exceed .
Determination of Swainsonine in Astragalus locoweed by internal standard gas chromatography

【Objective】 The study established a method for determination of Swainsonine. 【Method】 Swainsonine in Astragalus locoweed was determinated by mainternal standard gas chromatography with me-Gal as internal standard under the oven temperature 200 ℃,injection temperature 300 ℃,detector(FID) temperature 280 ℃ and flow rate of carrier gas 200 kPa. 【Result】 The analysis results of single-calibration-ratio was 1.067 8 and good linear relationship was obtained in the range of 0.047 to 6 mg/mL.The recovery percentage was 107.33%. The SW contents of A.variabilis and A.strictus were (39.2±0.16) mg/kg and(43.6±0.13) mg/kg respectively. 【Conclusion】 The internal standard method had high accuracy and good repertability and could be a determination method of Swainsinine.
STRATEGIES TO DEAL WITH EPIDEMICS USING A SYSTEM DYNAMICS MODEL: A COVID-19 STUDY CASE

This paper presents a System Dynamics Model to verify well-known strategies to deal with the COVID-19 outbreak, based on the classical epidemiological SIR model. Three main strategies were tested, considering the idealized main goal of public policies, to save lives. In addition, the authorities' reaction time on implementing actions to control the pandemic is analyzed. From the tested strategies, between quarantine extension, vertical quarantine, and identification of infected persons, the most promising is to identify infected persons and the least suitable is vertical quarantine. Also, the simulations indicated that tightening quarantine at any time tends to save lives, but late action by authorities can bring overpressure on a country's health care system, which has also direct impact on the lethality of the epidemic.
Biotransformation screen of ursolic acid and determination of consumption rate

Objective To study 25 species of fungi on the conversion of ursolic acid and determine the substrate consumption rate of activated fungi by RP-HPLC method combined with thin layer chromatography.Methods The optimum HPLC conditions were as follows:column was SHIMADZU VP-ODS(250 mm×4.6 mm,5 μm),mobile phase was acetonitrile and water(V∶V=85∶15),flow rate is 1.0 mL·min-1 and the detection wavelength was set at 204 nm;TLC conditions:developping agent was cyclohexane-ethyl acetate(V∶V=5∶5),chromogenic agent was 10% sulfuric acid ethanol solution.Results The calibration curve was A=1.250×104ρ+3.855×104(r=0.999 9)with the linear in the range of 4.0-16.0 μg for ursolic acid.Detected by HPLC combined with TLC method,the results showed that ursolic acid was biotransformed by three kinds of fungi and the consumption rate were 42.04%,51.73%,69.36% when ursolic acid concentration in medium was 0.3 mg·L-1.Conclusions The detective method,which using RP-HPLC method combined with the rechecking by TLC,is stable and accurate for qualitative and quantitative analysis of the biotransformation products of ursolic acid.
Evaluating the Landslides Characterization and Deformation Using Multi-Temporal Uav Imageries in Northern Pakistan

The Un Manned Aerial Vehicles (UAVs) have emerged as an effective tool for mapping and evaluating the landslides dynamics. This study aims to evaluate the dynamics of the landslide using the UAV derived aerial photos and Digital Surface Model (DSM). The selected landslides are the Nara and Nokot landslides in the rough terrain of Balakot, north Pakistan. The UAV survey was carried in April and August 2019 for Nara and Nokot landslides in Balakot. The images were processed in the Pix4D mapper to compute the orthomosaic and DSMs. The Ground Control Points (GCPs) collected in the geodetic survey with the Global Navigation Satellite System (GNSS) using Post Processing Kinematic (PPK) were used to accurately co-register and orthorectify the UAV imageries. The derived DSMs were analyzed to evaluate the dynamics in the landslide’s topography and volumetric changes. The shaded relief single band was used to correlate the temporal images for the Nara and Nokot landslide using the COSI-Corr algorithm. The statistical and frequent correlator was used for landslide displacement. The result shows that the Nara landside has a surface movement ranging from 1 to 29 m in the NE scarp and lateral areas. The Nokot landslide has active NS, NE and NW scarps with a surface movement ranging from 1 to 25.5 m. The accuracy assessment reveals the RMSE calculated for the Nara landslide as 4.58 m and 4.24 m for the Nokot landslide. This study reflected the potential application of UAVs for monitoring the landslides dynamics to mitigate the hazard.
Emissions of nitrous oxide, dinitrogen and carbon dioxide from three soils amended with carbon substrates under varying soil matric potentials

Carbon (C) substrates are critical for regulating denitrification, a process that results in nitrous oxide (N2O) and dinitrogen (N2) emissions from soil. However, the impacts of C substrates on concomitant soil emissions of carbon dioxide (CO2) and N2O under varying soil types and soil water contents are not well studied. Three repacked Pallic grassland soils, varying in texture and phosphorus (P) status, containing NO3−‐15N were held at three levels of matric potential (ψ, −3, −5 and −7 kPa), while receiving daily substrate additions (acetate, glucose and water control) for 14 days. The CO2 and N2O emissions were measured daily. Additionally, the N2O:(N2 + N2O) ratios were determined using 15N on days 3 and 14. Results showed that N2O emissions increased exponentially as soil gas diffusivity declined, and N2O peak emissions were higher with glucose than with acetate addition, with a range (± standard deviation) of 0.1 ± 0.0 to 42.7 ± 2.1 mg N m−2 h−1. The highest cumulative N2O emission (2.5 ± 0.2 g N m−2) was measured following glucose addition with a soil ψ of −3 kPa. In comparison with added glucose, acetate resulted in a twofold increase in N2 emissions in soils with relatively low gas diffusivities. The N2O:(N2O + N2) emissions ratios varied with substrate (glucose, 0.91; acetate, 0.81) on day 3, and had declined by day 14 under substrate addition (≤0.10). Cumulative CO2 emissions were enhanced with increasing soil gas diffusivity and were higher for soils amended with glucose (ranging from 22.5 ± 1.3 to 36.6 ± 1.8, g C m−2) than for those amended with acetate. Collectively, the results demonstrate that the increase of N2O, N2 and CO2 emissions and changes in the N2O:(N2 + N2O) ratio vary over time in response to C substrate type and soil gas diffusivity.
False Data Detection in Smart Grid using Artificial Intelligence

In order to increase the utilization of artificial intelligence in smart grids, it is necessary to have an accurate state estimation. This criterion is an essential aspect, along with other functionalities for successful control and monitoring. As the internet and utility network form an increasing interconnectivity, it leaves the state estimators in a state of vulnerability to various attacks like bad data detection and false data injection. Though there are many research-works done on detectors for false data detection, depending on the contingencies, the counter measure will also vary. A sudden change physically will have a high impact on the available data, resulting in incorrect classification of the future instances. As a means of addressing this issue, we have analyzed the differences between data manipulation change and physical grid change for better understanding. Focusing on distribution change, we used outage and have introduced analysis of historical data. The goal is to determine the important aspects thereby identifying the scope. We have also used statistical hypothesis and dimensionality reduction for testing purpose. We have used IEEE 14 bus system for evaluation based on the scenario of attack: under concept drift and without concept drift. The result shows a more accurate output when compared with the other previously existing methodologies using concept drift.
Critical Barriers to Implementation of Reverse Logistics in the Manufacturing Industry: A Case Study of a Developing Country

Globalization policies are encouraging manufacturing companies to produce environment-friendly products that offer a sustainable competitive advantage. Currently, product recovery and zero-waste supply chains have caught the attention of manufacturers and professionals. Reverse logistics (RL) is considered as the most significant part of supply chain management in developed countries; unfortunately, its implementation in developing countries is in the initial stages due to certain barriers. This study aims to identify and verify the barriers to implementation of reverse logistics using a two-stage methodology: the Delphi Method and Structural Equation Modeling. A comprehensive literature review was considered to identify a primary set of barriers. Using the Delphi Method, a team of experts screened out barriers after performing three iterations. A survey-based questionnaire was then sent out to supply chain and logistics employees in the manufacturing industry and relevant government authorities. Five hundred and forty-seven useful responses were analyzed in the Statistical Package for the Social Science (SPSS) & AMOS 21 softwares using Structural Equation Modeling to verify barriers, and ranked according to their severity. The most critical barriers with respect to each category are: high cost of reverse logistics adoption (finance and economics), lack of skilled professionals (knowledge and experience), lack of government supportive policies (law and regulation), poor organizational culture (management), lack of human resources (infrastructure and technology), lack of environmental law awareness (environment), lack of community pressure (market) and company policies (reverse logistics in policy). Overall, the top five barriers found in this study include lack of initial capital, lack of skilled professional in RL, companies’ policies against RL, lack of new technologies and information systems, and lack of community pressure. Knowledge about barriers to reverse logistics allows manufacturing companies to prepare a priority list of actions for better implementation of the reverse logistics system.
SENSORY OPTIMISATION IN NEW FOOD PRODUCT DEVELOPMENT: A CASE STUDY OF POLISH APPLE JUICE

A large variety of juices representing a wide range of sensory profiles can be found on the market. Nevertheless, their manufacturers may not fully recognise the needs and demands of consumers. The aim of the study was to verify a new strategy for consumer product testing using apple juice as an example. The material comprised of 14 apple juices. The sensory analysis was carried out by a team of 130 assessors. The impact of individual physicochemical parameters on the results of the juice sensory assessment was tested with the use of generalised additive models (GAM). The results of the research indicate that the most preferred apple juice is characterised by a balanced sweet and sour taste, low density as well as the colour described by a compromise between the high value of L* and low values of a* and b* parameters and a relatively low price. After the analysis of the map of preferences and its comparison with the results of the sensory assessment, it can be concluded that the products tested do not fully meet the consumer expectations. The research adds new insight into knowledge on new food product development. It shows that by examining the sensory desirability of products available on the market and by employing the GAM analysis the characteristics of the most appreciated product can be determined.
Framing sustainable exports in theory and practice

Increasingly exporters need to take into consideration sustainable exports. This paper is an academic exercise that seeks to develop an analytical framework to demonstrate sustainable exports as a market embedded inter-organisational function. Influences of this investigation include institutional economics and sociology. The developed framework guides investigation of three published cases of exporting behaviour. Here we re-tell the narratives following this alternative framework. New insight on each case includes considerations of sustainability as well as exporting as an emergent exchange process. This framework also gives guidance for a new research agenda on the topic of sustainable export.
Test-Retest Reliability of Sole Morphology Measurements Using a Novel Single-Image-Based Pin-Array Impression Reconstruction Method

Background: Assessment of the sole morphology provides a clinically useful measure of the foot condition, but existing methods are mostly limited to two-dimensional or non-weight-bearing conditions. The current study aimed to assess the reliability of a novel method called Single-Image-Based Pin-Array Impression Reconstruction Method (SIBPAIR) implemented on a commercial foot assessment system, and the intra-rater, inter-rater and inter-session reliability of the SIBPAIR-based protocol for three-dimensional sole morphological measurements. Methods: The reliability of the SIBPAIR method, and the intra-rater, inter-rater, and inter-session reliability of the SIBPAIR-based protocol in measuring morphological parameters of the sole were assessed by repeated measurements of fifteen young healthy adults by two male physical therapists, in terms of intra-class correlation coefficients (ICC) and standard error of measurement (SEM). Results and Conclusions: The SIBPAIR method was found to have very high reliability with very small SEM values, and the SIBPAIR-based protocol also showed very high intra-rater, inter-rater, and inter-session reliability with small SEM. These results indicate that accurate and reliable measurements could be obtained by following the protocol regardless of the rater’s experience or time of measurement. This will be useful for foot assessment and subsequent applications, such as design and manufacture of customized orthoses or shoes.
Duraflo ? II heparin treated extracorporeal circulation circuits ( 2 nd version ) the European working group on heparin coated extracorporeal circulation circuits

Objectives: To evaluate whether the application of heparin treated circuits for elective coronary artery surgery improves postoperative recovery, a European multicenter randomised clinical trial was carried out. Methods: In 11 European heart centers, 805 low-risk patients underwent cardiopulmonary bypass (CPB) with either an untreated circuit (n=407) or an identical but heparin treated circuit (n=398, DurafloII). Results: Significant differences were found among participating centers with respect to patient characteristics, blood handling procedures and postoperative care. The use of heparin treated circuits revealed no overall changes in blood loss, blood use, time on ventilator, occurrence of adverse events, morbidity, mortality, and intensive care stay. These results did not change after adjustment for centers and (other) prognostic factors as analysed with logistic regression. In both groups no clinical or technical (patient or device related) side effects were reported. Because female gender and aortic * Corresponding author. The European Working Group on heparin coated extracorporeal circulation circuits, P.O. Box 169, 5400 AD Uden, Netherlands. Tel. : +31 413 286621; fax +31 413 250085. 1010-7940/97/$17.00 © 1997 Elsevier Science B.V. All rights reserved. PII S 1 0 10 -7940 (96 )01122 -0 C.R. H. Wilde6uur et al. / European Journal of Cardio-thoracic Surgery 11 (1997) 616–623 617 cross clamp time appeared as prognostic factors in the logistic regression analysis, a subgroup analysis with these variables was performed. In a subpopulation of females (n=99), those receiving heparin treated circuits needed less blood products, had a lower incidence of rhythm disturbances and were extubated earlier than controls. In another subgroup of patients with aortic cross clamp time exceeding 60 min (n=197), the amount of patients requiring prolonged intensive care treatment (\24 h) was significantly lower when they received heparin treated circuits versus controls. Conclusion: These findings suggest that improved recovery can be expected with heparin treated circuits in specific higher risk patient populations (e.g. females) and when prolonged aortic cross clamp time is anticipated. Further investigations are recommended to analyse the clinical benefit of heparin treated circuits in studies with patients in different well defined risk categories and under better standardised circumstances. © 1997 Elsevier Science B.V.
A Bayesian Nonparametric Approach to Factor Analysis

This paper introduces a new approach for the inference of non-Gaussian factor models based on Bayesian nonparametric methods. It relaxes the usual normality assumption on the latent factors, widely used in practice, which is too restrictive in many settings. Our approach, on the contrary, does not impose any particular assumptions on the shape of the distribution of the factors, but still secures the basic requirements for the identification of the model. We design a new sampling scheme based on marginal data augmentation for the inference of mixtures of normals with location and scale restrictions. This approach is augmented by the use of a retrospective sampler, to allow for the inference of a constrained Dirichlet process mixture model for the distribution of the latent factors. We carry out a simulation study to illustrate the methodology and demonstrate its benefits. Our sampler is very efficient in recovering the distribution of the factors, and only generates models that fulfill the identification requirements. A real data example illustrates the applicability of the approach. JEL Classification: C11; C38; C63.
Root morphology and ammonium uptake kinetics in two traditional rice varieties submitted to different doses of ammonium nutrition

Abstract Rice (Oryza sativa L.) is one of the most produced cereals in the world. Among the essential nutrients required by this crop, nitrogen (N) is of paramount importance to achieve optimum yields. In paddy fields, ammonium (NH4+) represents the main source of N. This work aimed to evaluate the root morphology, ammonium uptake kinetics and N accumulation in two upland rice varieties, Piauí and Manteiga from Maranhão – Brazil. The varieties were cultivated in hydroponic conditions and submitted to three different doses of ammonium: 1 – constant treatment with 0.2 mM NH4+, 2 – constant treatment with 1 mM NH4+ and 3 – constant treatment with 1 mM NH4+, followed by N starvation during 72 h and resupply with 1 mM NH4+. The varieties present contrasting behaviors when submitted to different doses of NH4+. Piauí showed higher biomass and root length under the treatment with 0.2 mM NH4+. The favorable kinetics parameters observed contributed to a higher N accumulation by Piauí in low dose of NH4+. Under 1 mM NH4+, a higher root biomass and favorable kinetics parameters was recorded by Manteiga. This variety presented a better performance with higher doses of N. Under the treatment of N resupply, Piauí variety showed to be more adapted, due to the greater root plasticity observed. For one hand, the results suggest that Piauí variety presents greater growth in environments with low dose or seasonal flux of NH4+. On the other hand, Manteiga variety presents better growth when submitted to higher levels of NH4+.
Conceptualising ‘Disaster Education’

‘Disaster education’ has been studied in various disciplines such as disaster risk management and environmental studies. However, disaster education is a relatively ‘new enquiry’ in the field of education. Particularly, the literature that conceptualises ‘disaster education’ in education is minimal. This paper aims to fill this gap by synthesising existing disaster education literature linking them with educational concepts. The paper suggests three possible conceptualisations for disaster education. The first is based on a temporal distinction between education undertaken in usual times or unusual times. The second conceptualisation applies modes of learning and teaching: formal, non-formal and informal. Thirdly, establishing disaster education as a sub-discipline in the field of education is proposed: one sub-discipline is lifelong learning and the other is public pedagogy. Critiquing each method of conceptualisation, the paper argues for the suitability and usefulness of locating ‘disaster education’ within public pedagogy.
Optimal Policy for Dynamic Assortment Planning Under Multinomial Logit Models

We study the dynamic assortment planning problem, where for each arriving customer, the seller offers an assortment of substitutable products and the customer makes the purchase among offered products according to an uncapacitated multinomial logit (MNL) model. Because all the utility parameters of the MNL model are unknown, the seller needs to simultaneously learn customers’ choice behavior and make dynamic decisions on assortments based on the current knowledge. The goal of the seller is to maximize the expected revenue, or, equivalently, to minimize the expected regret. Although dynamic assortment planning problem has received an increasing attention in revenue management, most existing policies require the estimation of mean utility for each product and the final regret usually involves the number of products [Formula: see text]. The optimal regret of the dynamic assortment planning problem under the most basic and popular choice model—the MNL model—is still open. By carefully analyzing a revenue potential function, we develop a trisection-based policy combined with adaptive confidence bound construction, which achieves an item-independent regret bound of [Formula: see text], where [Formula: see text] is the length of selling horizon. We further establish the matching lower bound result to show the optimality of our policy. There are two major advantages of the proposed policy. First, the regret of all our policies has no dependence on [Formula: see text]. Second, our policies are almost assumption-free: there is no assumption on mean utility nor any “separability” condition on the expected revenues for different assortments. We also extend our trisection search algorithm to capacitated MNL models and obtain the optimal regret [Formula: see text] (up to logrithmic factors) without any assumption on the mean utility parameters of items.
Voluntary Liquidations: An Empirical Study

A number of studies have analyzed the effect of voluntary corporate liquidations on shareholder wealth. Others have examined some specific aspects, such as procedural and tax differences, of voluntary liquidating firms. In this paper we perform a preliminary study of the characteristics of firms that voluntary liquidate using a logit mo- del. The paper avoids some of the methodological flaws of commonly used binary state prediction models with diffe- rent sample and population distributions.