Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving reliability of heat and fluid flow calculation during conduction mode laser spot welding by multivariable optimisation

Several uncertain parameters affect the reliability of heat transfer and fluid flow calculations during conduction mode laser spot welding because their values cannot be prescribed from fundamental principles. These parameters include absorptivity of the laser beam, effective thermal conductivity and effective viscosity of liquid metal in the weld pool. Values of these parameters are usually adjusted by trial and error so that the computed results agree with the corresponding experimental values. Here it is shown that by integrating multivariable constrained optimisation with convective heat transfer and fluid flow calculations, the values of the uncertain parameters can be obtained from a limited volume of experimental data. The optimisation technique requires numerically calculated sensitivity values of weld dimensions with respect to absorptivity, effective thermal conductivity and effective viscosity and minimises the discrepancy between the predicted and the measured weld dimensions. The numerical heat transfer and fluid flow model embodying the optimised values of the uncertain parameters could accurately compute values of weld dimensions for new welding conditions. Reliability of heat transfer and fluid flow calculations can be significantly enhanced by determining the values of uncertain parameters from a limited volume of experimental data using a multivariable optimisation technique with a numerical heat transfer and fluid flow model.
Finite‐size corrections at the hard edge for the Laguerre β ensemble

A fundamental question in random matrix theory is to quantify the optimal rate of convergence to universal laws. We take up this problem for the Laguerre β ensemble, characterized by the Dyson parameter β, and the Laguerre weight xae−βx/2 , x>0 in the hard edge limit. The latter relates to the eigenvalues in the vicinity of the origin in the scaled variable x↦x/4N . Previous work has established the corresponding functional form of various statistical quantities—for example, the distribution of the smallest eigenvalue, provided that a∈Z≥0 . We show, using the theory of multidimensional hypergeometric functions based on Jack polynomials, that with the modified hard edge scaling x↦x/4(N+a/β) , the rate of convergence to the limiting distribution is O(1/N2) , which is optimal. In the case β=2 , general a>−1 the explicit functional form of the distribution of the smallest eigenvalue at this order can be computed, as it can for a=1 and general β>0 . An iterative scheme is presented to numerically approximate the functional form for general a∈Z≥2 .
Microscopic spinon-chargon theory of magnetic polarons in the 
t−J
 model

The interplay of spin and charge degrees of freedom, introduced by doping mobile holes into a Mott insulator with strong antiferromagnetic (AFM) correlations, is at the heart of strongly correlated matter such as high-${T}_{c}$ cuprate superconductors. Here, we capture this interplay in the strong coupling regime and propose a trial wave function of mobile holes in an AFM. Our method provides a microscopic justification for a class of theories which describe doped holes moving in an AFM environment as mesonlike bound states of spinons and chargons. We discuss a model of such bound states from the perspective of geometric strings, which describe a fluctuating lattice geometry introduced by the fast motion of the chargon, relative to the spinon. This is demonstrated to give rise to short-range hidden string order, signatures of which have recently been revealed by ultracold atom experiments at elevated temperatures. We present evidence for such short-range hidden string correlations also at zero temperature by performing numerical density-matrix renormalization-group simulations. To test our microscopic approach, we calculate the ground-state energy and dispersion relation of a hole in an AFM, as well as the magnetic polaron radius, and obtain good quantitative agreement with advanced numerical simulations at strong coupling. We discuss extensions of our analysis to systems without long-range AFM order to systems with short-range magnetic correlations.
Risk Factors of Non-Syndromic Orofacial Clefts in Sudan during 2016-2017

Background: Orofacial clefts are among the most common anomalies in the head and neck region and both genetic and environmental etiologies can be implicated. Aims: To evaluate the association of certain environmental risk factors with non-syndromic orofacial clefts (NSOFCs) and to determine the most common type of clefts associated with these factors. Methodology: 288 participants were included in this cross-sectional study; 144 in case group (mothers of children with NSOFC) and equal number of control group (mothers of healthy children). Details about gender of child, type of cleft, maternal gestational age and health, level of education, socioeconomic status, folic acid intake, consanguineous marriage, family history of clefts, radiation exposure, chemotherapy, gestational smoking, alcohol and drug intake were recorded. Results: Low education level (p. v=0.001), lack of folic acid supplementation (p. v=0.003, OR=0.20, 95% CI: -0.6_1.0) family history of clefts (p. v=0.014, OR=6, 95% CI: 4.68_7.26) and low socioeconomic status (p. v=0.042) were significantly associated with NSOFCs. Using multivariate analysis, maternal education was the most significant factor followed by folic acid supplementation. Conclusion: low education level, lack of gestational folic acid intake, family history of clefts, low socioeconomic status and consanguineous marriage all should be considered as potential risk factors for NSOFCs. Among these, maternal education and gestational folic acid supplementation were the most significant ones. Isolated cleft lip was the commonest type associated with these factors.
Evaluation of Historical and Future Cool Season Precipitation over the Eastern United States and Western Atlantic Storm Track Using CMIP5 Models

AbstractThis study analyzed the contribution of cyclones to projected changes in cool season (1 November–31 March) precipitation over the eastern United States and western North Atlantic Ocean. First, global climate model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were compared to Global Precipitation Climatology Project (GPCP) and Climate Prediction Center (CPC) precipitation analyses for the period 1979–2004. The CMIP5 ensemble mean realistically reproduced the historical distribution of regional precipitation with no discernable effect because of model spatial resolution. Subsequently, the projected changes in precipitation on cyclone and noncyclone days under the representative concentration pathway 8.5 (RCP8.5) scenario were quantified. While precipitation on both types of days was projected to increase, the increase on noncyclone days (23%) was greater than the increase on cyclone days (12%). The increase in precipitation on cyclone days occurred despite a decrease.
Lexical reading in Spanish: Two cases of phonological dyslexia

The way spoken language is represented by orthographic structure is thought to influence the cognitive reading mechanism for a language, and therefore language breakdown patterns should reflect this. The present article focuses on two patients, both monolingual native Spanish speakers, who were able to read words but showed great difficulty in reading nonwords. This finding could be attributed to the fact that these patients were reading globally using a lexical route. This pattern of reading behavior is known as phonological dyslexia. It has been argued that lexical reading is not an option for Spanish readers since its orthography is highly regular. Our findings contradict this hypothesis and support the view that cognitive reading mechanisms are universal.
A replicated two-level total factorial analysis: deformation in aluminum alloy skins caused by riveting processes

The objective of this work was to demonstrate the following: the deformation effect in aluminum alloy skins when a riveting process is applied; to determine which factors, such as hole diameter, depth of countersunk etc. affect the skin deformation, and the degree of this influence. In order to identify the candidate factors relating to the deformation effect, a survey was carried out with riveting process and material science specialists. The survey results were analyzed and detailed further. Then, an experimental approach was conducted based on the Taguchi Robust Design, which used the factors previously elected, as well as a set of samplings. Finally, a variance analysis, which was based on a multifactor variance method, was performed. Results showed the expansion of the panels after the riveting process, the identification of factors of influence on this expansion, and the suggestion of possible actions to reduce this deformation.
The Process of Chinese Manufacturing Upgrading: Transitioning from Unilateral to Recursive Mutual Learning Relations

This article argues that upgrading in China has been a historical success, that upgrading must be seen as a learning process, and that current Chinese upgrading involves a transformation in industrial learning dynamics. During China's initial export-oriented industrialization strategy, indigenous producers successfully upgraded by apprenticing themselves to their foreign customers, and they learned through integration in transnational communities of practice. The success of those initial unilateral learning relations enhanced the sophistication of the Chinese market, both as a community of producers and as a market for manufactured goods. This has generated a new phase of learning-driven upgrading in which Chinese producers and MNC manufacturers both seek to make their Chinese operations more sophisticated. In this new context, apprenticeship disappears and Chinese and foreign players learn from one another. A core claim about the new mutual learning is that it is facilitated by the globalization of formal learning systems, such as corporate production systems (CPSs).
Indigenous cultural heritage and Fairtrade: voluntary certification standards in the light of WIPO and WTO law and policymaking

Private initiatives for voluntary certification standards appear to be an attractive alternative to top-down approaches in the field of indigenous cultural heritage and development. Over the last 50 years, many different indigenous communities have attempted to use certification trademarks to promote their authentic cultural products. These schemes have had varying success, but arguably none has been as visually unsuccessful as the government-funded Australian system, which collapsed within two years of its inception. On the other side of the scale, the Fairtrade label is considered to be an international triumphant success. This paper assesses why the Australian authenticity label system failed, while the Fairtrade label succeeded, and how these conclusions can be used for existing and future endeavours. It further discusses whether such a voluntary certification system would be compliant with World Intellectual Property Organisation and World Trade Organisation law and policy. It concludes by looking towards the future and the possibility of the Fairtrade label being extended to meet the interests of indigenous communities.
How Does Organizational Citizenship Behavior (OCB) Affect the performance of megaprojects? Insights from a System Dynamic Simulation

As one of the emerging research fields of sustainability management, Organizational Citizenship Behavior (OCB), especially its influence on project performance, has been drawing increased attention both in the academic and industrial areas. Nevertheless, existing studies mainly examine the static relationship between OCB and project performance but fail to explore the dynamic characteristic of the relationship as a project may evolve and proceed over the time. Therefore, this paper aims to evaluate the dynamic impacts of OCB on the performance of megaprojects with the assistance of a system dynamic model. Four causal feedback loops and a stock-flow diagram were developed to illustrate the dynamic influencing mechanism, and three distinct policies quantitatively simulated the possible impacts arising from the changes of OCB on the whole system and, specifically, on the performance megaproject. The results show that an increase in the AIRPP (actual increasing rate of potential promotion) exerts significant influence on the improvement in OCB and the performance of megaprojects. The higher the AIRPP in the multi-policy scenario, the higher the OCB and the performance. One major contribution is that this study is one of the first studies to explore the potential use of system dynamics to model megaproject organizational behavior and its performance with implications in both the practical and cultural promotion of OCB.
Problems and issues in laser-arc hybrid welding

Hybrid welding, using the combination of a laser and an electrical arc, is designed to overcome problems commonly encountered during either laser or arc welding such as cracking, brittle phase formation and porosity. When placed in close contact with each other, the two heat sources interact in such a way as to produce a single high intensity energy source. This synergistic interaction of the two heat sources has been shown to alleviate problems commonly encountered in each individual welding process. Hybrid welding allows increased gap tolerances, as compared to laser welding, while retaining the high weld speed and penetration necessary for the efficient welding of thicker workpieces. A number of simultaneously occurring physical processes have been identified as contributing to these unique properties obtained during hybrid welding. However, the physical understanding of these interactions is still evolving. This review critically analyses the recent advances in the fundamental understanding of hybrid welding processes with emphases on the physical interaction between the arc and laser and the effect of the combined arc/laser heat source on the welding process. Important areas for further research are also identified.
G-quadruplex binders cause DNA damage by inducing R-loops in human cancer cells

G-Quadruplexes (G4s) and R-loops are non-B DNA structures that can regulate transcription and replication. G4s are formed from four guanine residues that are held together in the same plane by Hoogsteen hydrogen bonds and further stabilized by the presence of monovalent cations. R-loops are triple-strand structures that contain an RNA-DNA hybrid and displaced single-stranded DNA. One of the most important features that influence these DNA structures is the GC content. Indeed, R-loop structures can be favoured by a high guanine density in the non-template DNA strand and this is specifically due to the higher thermodynamic stability of RNA-DNA hybrid. R-loops and G4s are generally regarded as highly deleterious, indeed the structures can block both transcription and DNA replication, creating replicative stress and potentially causing DNA damage. Here, we used immunofluorescence analysis in order to identify the increase of G4s and R-loops in cancer cells treated with specific G4 binders at long and very short time. At long time, the increase of these two non-B DNA structures triggers genomic DNA damage as established by the formation of γH2AX foci and other markers of cellular DNA damage response. Interestingly, stable and transient overexpression of RNaseH, an enzyme that specifically removes R-loop structures, induce a rescue of G4 binder-induced DNA damage and genome instability. Our study provides the first direct evidence of a mechanistic link between G4s and R-loops in human cancer cells.
An Audit of Political Behavior Research

What are the most important concepts in the political behavior literature? Have experiments supplanted surveys as the dominant method in political behavior research? What role does the American National Election Studies (ANES) play in this literature? We utilize a content analysis of over 1,100 quantitative articles on American mass political behavior published between 1980 and 2009 to address these questions. We then supplement this with a second sample of articles published between 2010 and 2018. Four key takeaways are apparent. First, the agenda of this literature is heavily skewed toward understanding voting to a relative lack of attention to specific policy attitudes and other topics. Second, experiments are ascendant, but are far from displacing surveys, and particularly the ANES. Third, while important changes to this agenda have occurred over time, it remains much the same in 2018 as it was in 1980. Fourth, the centrality of the ANES seems to stem from its time-series component. In the end, we conclude that the ANES is a critical investment for the scientific community and a main driver of political behavior research.
The Effect of Exogenous Information on Voluntary Disclosure and Market Quality

Abstract We analyze a model in which information may be voluntarily disclosed by a firm and/or by a third party, e.g., financial analysts. Due to its strategic nature, corporate voluntary disclosure is qualitatively different from third-party disclosure. Greater analyst coverage crowds out (crowds in) corporate voluntary disclosure when analysts mostly discover information that is available (unavailable) to the firm. Nevertheless, greater analyst coverage always improves the overall quality of public information. We base this claim on two market quality measures: price efficiency, which is statistical in nature, and liquidity, which is derived in a trading stage that follows the disclosure stage.
The Glittering Prizes: Career Incentives and Bureaucrat Performance

Bureaucracies are configured differently to private sector and political organizations. Across a wide range of civil services entry is competitive, promotion is constrained by seniority, jobs are for life, and retirement occurs at a fixed age. This implies that older entering officers, who are less likely to attain the glittering prize of reaching the top of the bureaucracy before they retire, may be less motivated to exert effort. Using a nationwide stakeholder survey and rich administrative data on elite civil servants in India, we provide evidence that: (i) officers who cannot reach the senior-most positions before they retire are perceived to be less effective and are more likely to be suspended and (ii) this effect is weakened by a reform that extends the retirement age. Together, these results suggest that the career incentive of reaching the top of a public organization is a powerful determinant of bureaucrat performance.
Fostering Green Investments and Tackling Climate-Related Financial Risks: Which Role for Macroprudential Policies?

Abstract While there is a growing debate among researchers and practitioners on the possible role of central banks and financial regulators in supporting a smooth transition to a low-carbon economy, the information on which macroprudential instruments could be used for reaching the “green structural change” is still quite limited. Moreover, the achievement of climate goals is still affected by the so-called “green finance gap”. This paper addresses these issues by proposing a critical review of existing and novel prudential approaches to incentivizing the decarbonization of banks' balance sheets and aligning finance with sustainable growth and development objectives. The analysis carried out in the paper allows understanding of under which conditions macroprudential policy could tackle climate change and promote green lending, while also containing climate-related financial risks.
Implementation and analysis of deep competitive neural networks

Deep learning techniques have made great progress in classifications of complex datasets [3]. This project aimed to determine whether further improvements could be made by the addition of unsupervised competitive layers to deep neural networks, with the reasoning that they could perform noise reduction on complex inputs. In order to do this, competitive neural networks of varying sizes, structures, and behaviours were constructed and fed into a feedforward neural network, and their performance evaluated. Testing on the MNIST database of handwritten digits [4] showed that whilst fully connected competitive layers did not improve the classification accuracy, more complex structures such as subdivisions and competitive convolutions were able to produce moderate improvements in the network’s performance.
Electron densities near Io from Galileo plasma wave observations

This paper presents an overview of electron densities obtained near Io from the Galileo plasma wave instrument during the first four flybys of Io. These flybys were 10, which was a downstream wake pass that occurred on December 7, 1995; I24, which was an upstream pass that occurred on October 11, 1999; I25, which was a south polar pass that occurred on November 26, 1999; and I27, which was an upstream pass that occurred on February 22, 2000. Two methods were used to measure the electron density. The first was based on the frequency of upper hybrid resonance emissions, and the second was based on the low-frequency cutoff of electromagnetic radiation at the electron plasma frequency. For three of the flybys, 10, I25, and I27, large density enhancements were observed near the closest approach to Io. The peak electron densities ranged from 2.1 to 6.8 × 104 cm−3. These densities are consistent with previous radio occultation measurements of Io's ionosphere. No density enhancement was observed during the I24 flyby, most likely because the spacecraft trajectory passed too far upstream to penetrate Io's ionosphere. During two of the flybys, I25 and I27, abrupt step-like changes were observed at the outer boundaries of the region of enhanced electron density. Comparisons with magnetic field models and energetic particle measurements show that the abrupt density steps occur as the spacecraft penetrated the boundary of the Io flux tube, with the region of high plasma density on the inside of the flux tube. Most likely the enhanced electron density within the Io flux tube is associated with magnetic field lines that are frozen to Io by the high conductivity of Io's atmosphere, thereby enhancing the escape of plasma along the magnetic field lines that pass through Io's ionosphere.
Title Discriminative deep metric learning for face verification inthe wild

This paper presents a new discriminative deep metric learning (DDML) method for face verification in the wild. Different from existing metric learning-based face verification methods which aim to learn a Mahalanobis distance metric to maximize the inter-class variations and minimize the intra-class variations, simultaneously, the proposed DDML trains a deep neural network which learns a set of hierarchical nonlinear transformations to project face pairs into the same feature subspace, under which the distance of each positive face pair is less than a smaller threshold and that of each negative pair is higher than a larger threshold, respectively, so that discriminative information can be exploited in the deep network. Our method achieves very competitive face verification performance on the widely used LFW and YouTube Faces (YTF) datasets.