Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical Modelling of Melting Processes and Induced Diapirism In the Lower Crust

SUMMARY The processes of partial melting and magmatic diapirism within the lower crust are evaluated using a numerical underplating model. Fully molten basalt (T= 1200°C) is emplaced at the Moho beneath a solid granite (T= 750OC) in order that a melt front grows into the granite. If diapirism does not occur, this melt front in the granite reaches a minimal depth in the crust before (like in the molten basalt) crystallization takes place. The density contrast between the partially molten granite layer and the overlying solid granite can lead to a Rayleigh-Taylor instability (RTI) which results in diapiric rise of the partially molten granite. Assuming a binary eutectic system for both the granite and the underplating basalt and a temperature- and stress-dependent rheology for the granite, we numerically solve the governing equations and find (a) that diapirism occurs only within a certain but possibly realistic range of parameters, and (b) that if diapirs occur, they do not rise to levels shallower than 15 or perhaps 12km. The growth rate depends on the degree of melting and the thickness of the partially molten layer, as well as the viscosity of the solid and the partially molten granite. From a comparison of the growth rate with the velocity of a Stefan front it is possible to predict whether a melt front will become unstable and result in diapiric ascent or whether a partially molten layer is created, which remains at depth. We carry out such a comparison using our thermodynamically and thermomechanically consistent model of melting and diapirism.
Further Evidence on the Performance of Funds of Funds: The Case of Real Estate Mutual Funds

Funds of funds (FOFs) are created when investment companies invest in other investment companies. Although the additional layer of fees incurred by FOFs has a negative effect on returns, there is empirical evidence that real estate FOFs generate superior performance net of fees and risk adjustments. The evidence is inconsistent with a growing consensus that most actively managed mutual funds do not, on average, generate excess returns after adjusting for fees and risk. This study explains this apparent contradiction and finds that most real estate FOFs do not outperform their benchmarks under alternative risk adjustment specifications.
Controlled aspect ratios of gold nanorods in reduction-limited conditions

Aspect ratios of gold nanorods have been finely modified in reduction-limited conditions via two electrochemical ways: by changing the amount of a growth solution containing small gold clusters in the presence of already prepared gold nanorods as seeds or by changing electrolysis time in the presence or absence of a silver plate. While the atomic molar ratio of gold in the growth solution to gold in the seed solution is critical in the former method, the relative molar ratio of gold ions to silver ions in the electrolytic solution is important in the latter way for the control of the aspect ratios of gold nanorods. The aspect ratios of gold nanorods decrease with an increase of electrolysis time in the absence of a silver plate, but they increase with an increase of electrolysis time in the presence of a silver plate.
Scaling of health information systems in India: Challenges and approaches

This article addresses the issue of scaling of information systems (IS) in both theoretical and empirical terms. Scaling is an important issue in IS, especially in the contemporary context of globalization, as attempts are ongoing to expand IS in the same context as well as take it into other contexts. Theoretically, an information-infrastructure (II) perspective is drawn on to analyze the challenge of scaling, viewing it not merely as a technical problem, but as a socio-technical one involving a heterogeneous network constituted of technology, people, processes, and the institutional context. Empirically, scaling is analyzed based on experiences from an ongoing project to implement health information systems within the primary health care sector in India. The theoretically informed empirical analysis leads to some preliminary insights relating to the questions of what is being scaled and how it is being scaled. Some conclusions are drawn on theoretical and practical challenges related to scaling, and on implications for human-resource capacity development. © 2006 Wiley Periodicals, Inc.
Comparative Study of Breeding Systems of Sympatric Subterranean Termites (Reticulitermes flavipes and R. hageni) in Central North Carolina Using Two Classes of Molecular Genetic Markers

Abstract We used microsatellite and mtDNA markers to compare colony and population genetics of two sympatric species of subterranean termites, Reticulitermes flavipes (Kollar) (n = 25 colonies) and R. hageni Banks (n = 16 colonies), in two sites located 27 km apart in the Piedmont of central North Carolina. Colony breeding structure was inferred by examination of microsatellite genotypes of workers within colonies and by estimates of nestmate relatedness and hierarchical F-statistics. Similar to previous results on this species, nearly one-half of the R. flavipes colonies were simple families mainly headed by outbred primary (alate-derived) reproductives, about one-half were comprised of extended (inbred) families inferred to be headed by low numbers of neotenics (non alate-derived secondary reproductives) descended from the original primary pair, and two colonies contained the offspring of multiple reproductives. About two-thirds of the R. hageni colonies were comprised of simple families largely headed by related reproductives, and about one-third consisted of extended families headed by low numbers of neotenics. R. hageni differed from R. flavipes in having significant isolation by distance at one site as well as significant differentiation between sites at both the microsatellite and mtDNA markers. We conclude that dispersal in R. hageni is more limited resulting in higher levels of inbreeding within colonies and greater degrees of population genetic structure at small and large spatial scales than in sympatric populations of R. flavipes. These results indicate that closely related species of subterranean termites occurring in the same habitat can differ in their breeding systems with important consequences for higher level genetic structure.
Steelmaking Study on the Effect of Various Modifying Agent on the Blast Furnace Slag

Blast furnace slag has modification with different modifying agents, such as iron ore waste rock, fly ash, and the mixture (each 50%). The modifying effect is evaluated from five aspects: acidity coefficient Mk, viscosity coefficient Mη, hydrogen ion index pH of slag, molten slag viscosity, and slag mineral composition. The study shows that modification slag can be used as raw material and meets the requirements for the preparation of slag wool, but they exhibit different modifying effects to different modifying agents. By means of burden calculation, slag parameter calculation and parameter linear regression analysis, the effects of modifying agent were compared as follows, iron ore waste rock is the best modifying agent, mixture is the next and fly ash is the worst.
Non-Preferred Limb Performance Following Prolonged Training periods: Performance and Retention of Skills

The purpose of the current study was to examine if a long-term training program could improve non-preferred limb performance on a battery of standard tasks (Annett Pegboard, Grooved Pegboard Place and Remove Phase) and non-standard tasks (Scroll Task and Line-crossing Task). Upon completion of the training sessions, two new tasks were introduced, Finger Tapping and Fitt's Law Task, to examine if any performance improvements could be transferred. A second purpose of the study was to learn if a training program could increase the perceived comfort in using the non-preferred hand on the same testing tasks. Participants were assigned to a 1-week training group (3 sessions over 7 days, N = 21), 3-week training group (9 sessions over 21 days, N = 15) or no training control group (N = 20). Training sessions were derived based on the suggestions of the Ackland and Hendrie (2005) study and consisted of 20-30 minute sessions with a focus of non-preferred limb training on multiple tasks. Post-training testing found that though the non-preferred hand never does reach an on par performance with the preferred hand at the same point in time, the Grooved Pegboard Place phase and Scroll tasks, both had significant improvements in non-preferred hand performance over the course of the study. The training was task dependent, as no transfer of training was found on the two transfer tasks. Perceived comfort also improves with repeated exposure to a task, though training and hand improvements were not determining factors, as there were no group differences between tests. The results suggested that a training period of 2to 3-weeks was all that was required to see improvements in the non-preferred hand, but the learning does appear to be task specific.
Bmad Model of COSY, Status and Progress

The COSY1 in Jülich is a versatile machine with a long history of polarized proton acceleration. A new model of COSY based on the Bmad library was developed to simulate beam and spin dynamics. Original methods of lattice design, notably multi-objective lattice optimization, were explored. This contribution presents the status and development steps of the Bmad model of COSY. Some of the latest simulations will also be discussed.
Extremal Information Structures in the First Price Auction

We study how the outcomes of a private-value first price auction can vary with bidders' information, for a fixed distribution of private values. In a two bidder, two value, setting, we characterize all combinations of bidder surplus and revenue that can arise, and identify the information structure that minimizes revenue. The extremal information structure that minimizes revenue entails each bidder observing a noisy and correlated signal about the other bidder's value. In the general environment with many bidders and many values, we characterize the minimum bidder surplus of each bidder and maximum revenue across all information structures. The extremal information structure that simultaneously attains these bounds entails an efficient allocation, bidders knowing whether they will win or lose, losers bidding their true value and winners being induced to bid high by partial information about the highest losing bid. Our analysis uses a linear algebraic characterization of equilibria across all information structures, and we report simulations of properties of the set of all equilibria.
AUTOMATED PREDICTION OF THE WRITTEN ERRORS OF TERTIARY LEVEL ESL AND EFL LEARNERS

This paper summarizes a two-year project at the Chinese University of Hong Kong (CUHK) from 2006 to 2008. IELTS Online Writing Assistant (IOWA) is a computer-based teaching system designed for students in support of their preparation for the writing module of the International English Language Testing System (IELTS). Situated in Error Analysis (EA) (Corder, 1981; Mitchell, 2004; Lightbown, 1998) and Computer-Assisted Instruction (CAI), the system is designed to address both students' local (i.e., word and sentence) and global (i.e., discourse) errors. It attempts to predict which types of error tertiary level ESL and EFL learners in Hong Kong are most likely to make by assessing their ability to find errors in a prepared script. There are two major research questions: How effective is the system in predicting students' predispositions to committing writing errors and to creating discourse problems? How can teachers better use such a diagnostic tool to complement their teaching practice to address different issues of error categories? The study concludes that: (1) its predictive performance varies greatly depending on the types of error; (2) testing alone—with limited feedback—is effective at reducing the incidence of certain types of error, especially low-frequency and structural errors, in students’ productive writing; (3) certain types of error, which are most difficult for IOWA to predict, could be better instructed by teachers in an ordinary classroom context. Overall, the study has laid important foundations for enhancing our students’ IELTS writing test preparation. Keywords: Computer-Assisted Instruction (CAI), International English Language Testing System ( IELTS), Error Analysis (EA)
Improving Neural Program Synthesis with Inferred Execution Traces

The task of program synthesis, or automatically generating programs that are consistent with a provided specification, remains a challenging task in artificial intelligence. As in other fields of AI, deep learning-based end-to-end approaches have made great advances in program synthesis. However, more so than other fields such as computer vision, program synthesis provides greater opportunities to explicitly exploit structured information such as execution traces, which contain a superset of the information input/output pairs. While they are highly useful for program synthesis, as execution traces are more difficult to obtain than input/output pairs, we use the insight that we can split the process into two parts: infer the trace from the input/output example, then infer the program from the trace. This simple modification leads to state-of-the-art results in program synthesis in the Karel domain, improving accuracy to 81.3% from the 77.12% of prior work.
ossible mechanisms of antinociception of methanol extract of elastoma malabathricum leaves

Melastoma malabathricum L. , Melastomaceae, has been traditionally used to relieve diverse pain-related ailments. The objectives of the present study were to determine the antinociceptive activity of methanol extract of M. malabathricum leaves and to elucidate the possible mechanisms of antinociception involved using various rats’ models. The extract (100, 250, and 500 mg/kg) was administered orally 60 min prior to subjection to the respective test. The in vivo acetic acid-induced abdominal constriction, formalininduced paw licking, and hot plate tests were used as the models of nociception to evaluate the extract antinociceptive activity. Further studies were carried out to determine the role of opioid and vanilloid receptors, glutamate system and nitric oxide/cyclic guanosine phosphate (NO/cGMP) pathway in modulating the extract antinociceptive activity. From the results obtained, M. malabathricum exhibited significant (p < 0.05) antinociceptive activity in all the chemicaland thermal-induced nociception models. Naloxone (5 mg/kg), a non-selective opioid antagonist, failed to significantly affect the antinociceptive activity of MEMM when assessed using the abdominal constriction-, hot plateand formalin-induced paw licking-test. M. malabathricum also significantly (p < 0.05) reversed the nociceptive response in capsaicinand glutamate-induced paw licking test. Furthermore, only l-arginine (a nitric oxide precursor) alone, but not, NG-nitro-l-arginine methyl esters (l-NAME; an inhibitor of NO synthase), methylene blue (MB; an inhibitor of cGMP), or their combination thereof, significantly (p < 0.05) block the antinociceptive activity of M. malabathricum. In conclusion, M. malabathricum exerted a non-opioid antinociceptive activity at the central and peripheral levels partly via the inhibition of vanilloid receptors and glutamatergic system, and activation of the NO-mediated/cGMP-independent pathway. rasil he CC © 2016 Sociedade B access article under t
The Quality of Risk Disclosure: Evidence from Infrastructure Industry in Indonesia

The objective of this study was to analyze the quality of mandatory and voluntary risk disclosure in Indonesia during the period of 2011 and 2012. The risk disclosure quality is defined as the quality of risk information that are disclosed by firms in term of relative quantity (adjusted by type of sub-industry and firm size), depthness (the potential impact of risk disclosed on firm’s future performance), the coverage within every type of risk, and the outlook profile of firm’s risk management. This study used samples of 48 firm-years of infrastructure companies that were listed in Indonesia Stock Exchange. Infrastructure industry was chosen due to the strategic role of this industry to support the acceleration and expansion of Indonesia's economic development. By using a descriptive qualitative method, the result showed that firms were still emphasizing on relative quantity dimension compared to the other three dimensions: coverage, depth, and outlook profile of firm risk management. In addition, the quality of mandatory risk disclosure was better than voluntary risk disclosure either for depth, coverage, or an outlook profile of firm risk management dimension. In other words, financial risk items (mandatory risk disclosure items) have better quality rather than non-financial risk items (voluntary risk disclosure items).
Prediction Factory: automated development and collaborative evaluation of predictive models

In this paper, we present a data science automation system called Prediction Factory. The system uses several key automation algorithms to enable data scientists to rapidly develop predictive models and share them with domain experts. To assess the system's impact, we implemented 3 different interfaces for creating predictive modeling projects: baseline automation, full automation, and optional automation. With a dataset of online grocery shopper behaviors, we divided data scientists among the interfaces to specify prediction problems, learn and evaluate models, and write a report for domain experts to judge whether or not to fund to continue working on. In total, 22 data scientists created 94 reports that were judged 296 times by 26 experts. In a head-to-head trial, reports generated utilizing full data science automation interface reports were funded 57.5% of the time, while the ones that used baseline automation were only funded 42.5% of the time. An intermediate interface which supports optional automation generated reports were funded 58.6% more often compared to the baseline. Full automation and optional automation reports were funded about equally when put head-to-head. These results demonstrate that Prediction Factory has implemented a critical amount of automation to augment the role of data scientists and improve business outcomes.
Optimal lossy compression for differentially private data release by Jonas Köhler 11400358 November 26 , 2018

Differential privacy (DP) is the mathematical guarantee that the output of an algorithm operating on a data set has only a small dependency on any single individual in that set. A particular application of DP is the task of releasing privatized representations of data sets which should not be leaked to the public in their original form. Finding the right transformation of a data set, such that it is provably privatized but still preserves utility for the analysis task at hand, is a difficult task in theory and also practically unsolved for many applications. During this thesis we present an information theoretic approach to design DP data set release mechanisms, by reducing the problem to optimally compressing the data with respect to a measure of utility. As the optimal compression problem is inherently difficult to solve by itself, we analyze this approach for two linear instances of optimal compression for which an analytic solution exists and thus the analysis and sampling of privatized data sets is tractable. We further show in experiments that both methods cannot yield privacy/utility trade-offs that allow them to be used in practical tasks. We finish this research by proposing more complex approaches following this framework that are based on approximations and sampling methods and discuss their strengths and weaknesses.
Study of the Hygric Behaviour and Moisture Buffering Performance of a Hemp–Starch Composite Panel for Buildings

This paper presents the results of a laboratory investigation into the hygric properties and moisture buffering performance of hemp-starch composite panels designed for building applications. Composite panels were produced by bonding hemp shiv with wheat starch as a binder. Two types of hemp shiv were tested: chemically processed shiv with enhanced adhesion between fibers and starch matrix, and non-treated shiv. The panels were then characterised in terms of their hygroscopic properties (sorption curve and vapour diffusion resistance factor) and their moisture buffering performance (moisture buffering value, MBV). The determination of theoretical MBV was based on the effusivity of the material, which is obtained from its basic hygroscopic characterisation. The results show that both panels are excellent hydric regulators that can be used to improve indoor hygrothermal comfort by buffering indoor relative humidity variations.
Designing ex-situ conservation strategies for seeds storage of Piper aduncum and P. hispidinervum through cryopreservation and low-temperature techniques

ABSTRACT Piper aduncum and Piper hispidinervum are species found primarily in the Amazon region, and have been highlighted by the fact that they contain, in their essential oils, significant amounts of dillapiol and safrole. The aim of this work was to assess the seed behavior of P. aduncum and P. hispidinervum and to develop strategies for medium—to long-term storage of the species at sub-zero and cryogenic temperatures. In the first experiment, seeds were desiccated and their water content was determined. Then, the seeds were kept at −20°C for up to 90 days. In the second experiment, seeds were stored for up to 24 h in liquid nitrogen (LN; −196°C), with and without the use of cryoprotectants. Finally, for assessing the efficiency of these techniques, seeds were stored at −20°C and in LN for up to 360 days. The germination rate was more than 90% for both species when stored at −20°C or LN, without compromising their viability and development. The results suggest that P. aduncum and P. hispidinervum have seeds with orthodox behavior, which can be stored for the medium to long term at sub-zero and cryogenic temperatures without the need for use of cryoprotectants.
Inexact trust-region algorithms on Riemannian manifolds

We consider an inexact variant of the popular Riemannian trust-region algorithm for structured big-data minimization problems. The proposed algorithm approximates the gradient and the Hessian in addition to the solution of a trust-region sub-problem. Addressing large-scale finite-sum problems, we specifically propose sub-sampled algorithms with a fixed bound on sub-sampled Hessian and gradient sizes, where the gradient and Hessian are computed by a random sampling technique. Numerical evaluations demonstrate that the proposed algorithms outperform state-of-the-art Riemannian deterministic and stochastic gradient algorithms across different applications.
A new experimental hybrid of cabbage suitable for early production

The paper analyzes experimental hybrids of early cabbage developed at the Institute of Field and Vegetable Crops in the previous period. The hybrids were tested together for two years and then one (H17) was chosen and submitted to the Variety Commission of the Republic of Serbia. In 2011, the experimental hybrid H17 was officially released as an early cabbage hybrid and registered under the name of NS Mendo F1. The hybrid had been developed by crossing two early lines, one of which was sterile. It is characterized by a short growing season - 65 days from transplanting to harvest. The head weight ranges from 2.5 to 3.5 kg depending on the cultural practice applied. The head is light green in color, sweet-tasting, and suitable for fresh consumption. The hybrid’s traits that contributed significantly to the formation of the first principal component were in fact those that the breeders attach most importance to in their breeding programs. These are the traits that directly influence the market value of a new hybrid and make a given hybrid recognizable on the market. Most notable among such traits are head weight and the weight of the useful part of the head. [Projekat Ministarstva nauke Republike Srbije, br. TR 31030]