Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural Basis for Activation of Class Ib Ribonucleotide Reductase

Two Ways to Nucleotide Reduction Ribonucleotide reductases (RNRs) are essential for DNA synthesis and repair in all organisms, initiating nucleotide reduction through a free-radical mechanism. The class Ib RNRs are the primary aerobic RNRs for many human pathogens. NrdF, the class Ib RNR of Escherichia coli, can initiate nucleotide reduction through either a FeIII2-Y• or a MnIII2-Y• cofactor. Whereas the Fe-based cofactor can self-assemble, assembly of the Mn-based free radical requires a reduced flavoprotein, NrdI. Boal et al. (p. 1526, published online 5 August; see the Perspective by Sjöberg) have gained insight into the mechanism of cofactor activation by determining structures of MnII2-NrdF, FeII2-NrdF, and MnII2-NrdF in complex with reduced and oxidized NrdI. The structures show how a single protein, NrdF, can use two different oxidants to activate two different metallocofactors using distinct chemistries. A single protein activates two different metallofactors by distinct chemistries. The class Ib ribonucleotide reductase of Escherichia coli can initiate reduction of nucleotides to deoxynucleotides with either a MnIII2-tyrosyl radical (Y•) or a FeIII2-Y• cofactor in the NrdF subunit. Whereas FeIII2-Y• can self-assemble from FeII2-NrdF and O2, activation of MnII2-NrdF requires a reduced flavoprotein, NrdI, proposed to form the oxidant for cofactor assembly by reduction of O2. The crystal structures reported here of E. coli MnII2-NrdF and FeII2-NrdF reveal different coordination environments, suggesting distinct initial binding sites for the oxidants during cofactor activation. In the structures of MnII2-NrdF in complex with reduced and oxidized NrdI, a continuous channel connects the NrdI flavin cofactor to the NrdF MnII2 active site. Crystallographic detection of a putative peroxide in this channel supports the proposed mechanism of MnIII2-Y• cofactor assembly.
Determinants of information retweeting in microblogging

Purpose – The purpose of this paper is to propose a conceptual model to investigate the determinants of information retweeting in microblogging based on Heuristic‐Systematic Model.Design/methodology/approach – Microblogging data about emergency events from Sina microblogging (http://weibo.com) are collected and analyzed with text mining technology. The proposed hypotheses are tested with logistic and multiple linear regressions.Findings – The results show that source trustworthiness, source expertise, source attractiveness, and the number of multimedia have significant effects on the information retweeting. In addition, source expertise moderates the effects of user trustworthiness and content objectivity on the information retweeting in microblogging.Practical implications – This study provides an in‐depth understanding of what makes information about emergency events in microblogging diffuse so rapidly. Based on these findings the emergency management organizations in China can apply the microblogging t.
The Political Economy of Social

Portions of this paper are based on joint work with co-authors. Section 2 draws heavily on Lucio Baccaro and Marco Simoni, “Policy Concertation in Europe: Explaining Government Choice” (unpublished ms., 2006); the parts on Korea in Section 3 draw heavily on Lucio Baccaro and SangHoon Lim, “Social Pacts as Coalitions of the Weak and Moderate: Ireland, Italy, and South Korea in Comparative Perspective” (forthcoming in the European Journal of Industrial Relations); Section 5 draws heavily on Lucio Baccaro and Diego Rei, “Institutional Determinants of Unemployment in OECD Countries: Does the Deregulatory View Hold Water? ” (forthcoming in International Organization). I am profoundly grateful to Diego, Marco, and Sang-Hoon for their invaluable contributions.
Biophysical Tools and Concepts Enable Understanding of Asexual Blood Stage Malaria

Forces and mechanical properties of cells and tissues set constraints on biological functions, and are key determinants of human physiology. Changes in cell mechanics may arise from disease, or directly contribute to pathogenesis. Malaria gives many striking examples. Plasmodium parasites, the causative agents of malaria, are single-celled organisms that cannot survive outside their hosts; thus, thost-pathogen interactions are fundamental for parasite’s biological success and to the host response to infection. These interactions are often combinations of biochemical and mechanical factors, but most research focuses on the molecular side. However, Plasmodium infection of human red blood cells leads to changes in their mechanical properties, which has a crucial impact on disease pathogenesis because of the interaction of infected red blood cells with other human tissues through various adhesion mechanisms, which can be probed and modelled with biophysical techniques. Recently, natural polymorphisms affecting red blood cell biomechanics have also been shown to protect human populations, highlighting the potential of understanding biomechanical factors to inform future vaccines and drug development. Here we review biophysical techniques that have revealed new aspects of Plasmodium falciparum invasion of red blood cells and cytoadhesion of infected cells to the host vasculature. These mechanisms occur differently across Plasmodium species and are linked to malaria pathogenesis. We highlight promising techniques from the fields of bioengineering, immunomechanics, and soft matter physics that could be beneficial for studying malaria. Some approaches might also be applied to other phases of the malaria lifecycle and to apicomplexan infections with complex host-pathogen interactions.
Phoneme Recognition on the TIMIT Database

In the information age, computer applications have become part of modern life and this has in turn encouraged the expectations of friendly interaction with them. Speech, as “the” communication mode, has seen the successful development of quite a number of applications using automatic speech recognition (ASR), including command and control, dictation, dialog systems for people with impairments, translation, etc. But the actual challenge goes beyond the use of speech in control applications or to access information. The goal is to use speech as an information source, competing, for example, with text online. Since the technology supporting computer applications is highly dependent on the performance of the ASR system, research into ASR is still an active topic, as is shown by the range of research directions suggested in (Baker et al., 2009a, 2009b). Automatic speech recognition – the recognition of the information embedded in a speech signal and its transcription in terms of a set of characters, (Junqua & Haton, 1996) – has been object of intensive research for more than four decades, achieving notable results. It is only to be expected that speech recognition advances make spoken language as convenient and accessible as online text when the recognizers reach error rates near zero. But while digit recognition has already reached a rate of 99.6%, (Li, 2008), the same cannot be said of phone recognition, for which the best rates are still under 80% 1,(Mohamed et al., 2011; Siniscalchi et al., 2007). Speech recognition based on phones is very attractive since it is inherently free from vocabulary limitations. Large Vocabulary ASR (LVASR) systems’ performance depends on the quality of the phone recognizer. That is why research teams continue developing phone recognizers, in order to enhance their performance as much as possible. Phone recognition is, in fact, a recurrent problem for the speech recognition community. Phone recognition can be found in a wide range of applications. In addition to typical LVASR systems like (Morris & Fosler-Lussier, 2008; Scanlon et al., 2007; Schwarz, 2008), it can be found in applications related to keyword detection, (Schwarz, 2008), language recognition, (Matejka, 2009; Schwarz, 2008), speaker identification, (Furui, 2005) and applications for music identification and translation, (Fujihara & Goto, 2008; Gruhne et al., 2007). The challenge of building robust acoustic models involves applying good training algorithms to a suitable set of data. The database defines the units that can be trained and
The Role of Tip Leakage Flow in Spike-Type Rotating Stall Inception

This paper describes the role of tip leakage flow in creating the leading edge separation necessary for the onset of spike-type compressor rotating stall. A series of unsteady multipassage simulations, supported by experimental data, are used to define and illustrate the two competing mechanisms that cause the high incidence responsible for this separation: blockage from a casing-suction-surface corner separation and forward spillage of the tip leakage jet. The axial momentum flux in the tip leakage flow determines which mechanism dominates. At zero tip clearance, corner separation blockage dominates. As clearance is increased, the leakage flow reduces blockage, moving the stall flow coefficient to lower flow, i.e., giving a larger unstalled flow range. Increased clearance, however, means increased leakage jet momentum and contribution to leakage jet spillage. There is thus a clearance above which jet spillage dominates in creating incidence, so the stall flow coefficient increases and flow range decreases with clearance. As a consequence, there is a clearance for maximum flow range; for the two rotors in this study, the value was approximately 0.5% chord. The chordwise distribution of the leakage axial momentum is also important in determining stall onset. Shifting the distribution toward the trailing edge increases flow range for a leakage jet dominated geometry and reduces flow range for a corner separation dominated geometry. Guidelines are developed for flow range enhancement through control of tip leakage flow axial momentum magnitude and distribution. An example is given of how this might be achieved.
Coordinating Aerial Robots and Unattended Ground Sensors for Intelligent Surveillance Systems

Sensor networks are being used to implement different types of sophisticated emerging applications, such as those aimed at supporting ambient intelligence and surveillance systems. This usage is enhanced by employing sensors with different characteristics in terms of sensing, computing and mobility capabilities, working cooperatively in the network. However, the design and deployment of these heterogeneous systems present several issues that have to be handled in order to meet the user expectations. The main problems are related to the nodes' interoperability and the overall resource allocation, both inter and intra nodes. The first problem requires a common platform that abstracts the nodes' heterogeneity and provides a smooth communication, while the second is handled by cooperation mechanisms supported by the platform. Moreover, as the nodes are supposed to be heterogeneous, a customizable platform is required to support both resource rich and poorer nodes. This paper analyses surveillance systems based on a heterogeneous sensor network, which is composed by lowend ground sensor nodes and autonomous aerial robots, i.e. Unmanned Aerial Vehicles (UAVs), carrying different kinds of sensors. The approach proposed in this work tackles the two above mentioned problems by using a customizable hardware platform and a middleware to support interoperability. Experimental results are also provided.
PredGly: predicting lysine glycation sites for Homo sapiens based on XGboost feature optimization

Motivation Protein glycation is a familiar post-translational modification (PTM) which is a two-step non-enzymatic reaction. Glycation not only impairs the function but also changes the characteristics of the proteins so that it is related to many human diseases. It is still much more difficult to systematically detect glycation sites due to the glycated residues without crucial patterns. Computational approaches, which can filter supposed sites prior to experimental verification, can extremely increase the efficiency of experiment work. However, the previous lysine glycation prediction method uses a small number of training datasets. Hence, the model is not generalized or pervasive. Results By searching from a new database, we collected a large dataset in Homo sapiens. PredGly, a novel software, can predict lysine glycation sites for Homo sapiens, which was developed by combining multiple features. In addition, XGboost was adopted to optimize feature vectors and to improve the model performance. Through comparing various classifiers, support vector machine achieved an optimal performance. On the basis of a new independent test set, PredGly outperformed other glycation tools. It suggests that PredGly can provide more instructive guidance for further experimental research of lysine glycation. Availability https://github.com/yujialinncu/PredGly. Supplementary information Supplementary data are available at Bioinformatics online.
Macro-Economic Level Corporate Governance and FDI in Emerging Markets: Is There a Close Relationship?

Many experts believe that Foreign Direct Investment (FDI) can provide substantial benefits to emerging market countries and help to speed up the economic development process. National accounts data also shows FDI to be the single largest component of capital inflows to the vast majority of emerging market countries. Thus, it is crucial to determine the drivers and determinants of inwards FDI flows to such markets. There have been several studies on some FDI determinants such as market size and human capital factors, however the role of corporate governance at a national level has been largely neglected. This has mainly been due to the lack of good quality data on corporate governance measures and indicators. The creation of the World Bank Governance Indicators by Kaufmann et al (1999) makes rigorous studies of corporate governance and FDI possible. This study uses the World Bank Governance Indicators to empirically test the relationship between macroeconomic level corporate governance and inwards FDI flows into emerging market countries, using a panel data set of 33 countries between 1997 and 2002. The key finding is that macroeconomic corporate governance has a positive and significant effect on inwards FDI flows, suggesting host country governments and authorities should shape policy in this area to maximize inwards FDI flows.
Polycystic Ovary Syndrome: Pathophysiology, Presentation, and Treatment With Emphasis on Adolescent Girls

Abstract Polycystic ovary syndrome (PCOS) is a heterogeneous disorder characterized by hyperandrogenism and chronic anovulation. Depending on diagnostic criteria, 6% to 20% of reproductive aged women are affected. Symptoms of PCOS arise during the early pubertal years. Both normal female pubertal development and PCOS are characterized by irregular menstrual cycles, anovulation, and acne. Owing to the complicated interwoven pathophysiology, discerning the inciting causes is challenging. Most available clinical data communicate findings and outcomes in adult women. Whereas the Rotterdam criteria are accepted for adult women, different diagnostic criteria for PCOS in adolescent girls have been delineated. Diagnostic features for adolescent girls are menstrual irregularity, clinical hyperandrogenism, and/or hyperandrogenemia. Pelvic ultrasound findings are not needed for the diagnosis of PCOS in adolescent girls. Even before definitive diagnosis of PCOS, adolescents with clinical signs of androgen excess and oligomenorrhea/amenorrhea, features of PCOS, can be regarded as being “at risk for PCOS. ” Management of both those at risk for PCOS and those with a confirmed PCOS diagnosis includes education, healthy lifestyle interventions, and therapeutic interventions targeting their symptoms. Interventions can include metformin, combined oral contraceptive pills, spironolactone, and local treatments for hirsutism and acne. In addition to ascertaining for associated comorbidities, management should also include regular follow-up visits and planned transition to adult care providers. Comprehensive knowledge regarding the pathogenesis of PCOS will enable earlier identification of girls with high propensity to develop PCOS. Timely implementation of individualized therapeutic interventions will improve overall management of PCOS during adolescence, prevent associated comorbidities, and improve quality of life.
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images

Training an agent to solve control tasks directly from high-dimensional images with model-free reinforcement learning (RL) has proven difficult. A promising approach is to learn a latent representation together with the control policy. However, fitting a high-capacity encoder using a scarce reward signal is sample inefficient and leads to poor performance. Prior work has shown that auxiliary losses, such as image reconstruction, can aid efficient representation learning. However, incorporating reconstruction loss into an off-policy learning algorithm often leads to training instability. We explore the underlying reasons and identify variational autoencoders, used by previous investigations, as the cause of the divergence. Following these findings, we propose effective techniques to improve training stability. This results in a simple approach capable of matching state-of-the-art model-free and model-based algorithms on MuJoCo control tasks. Furthermore, our approach demonstrates robustness to observational noise, surpassing existing approaches in this setting. Code, results, and videos are anonymously available at https://sites.google. com/view/sac-ae/home.
Pentacam® Corneal Tomography for Screening of Refractive Surgery Candidates: A Review of the Literature, Part I

Corneal tomography and Scheimpflug imaging are frequently used to analyze the corneal surface, especially in the field of cataract and refractive surgery. The Pentacam system is one of the most commonly used commercially available systems for this purpose. Through a rotating Scheimpflug camera, the system is capable of creating a three-dimensional map of the cornea. These advances in tomography have simultaneously enhanced the ability of clinicians to screen surgical candidates and detect subtle corneal changes in diseases such as keratoconus. However, there remains a need to enhance diagnosis in order to recognize mild and early forms of corneal ectasia. As iatrogenic ectasia and keratoconus are dreaded complications of refractive surgery, it is imperative to screen patients appropriately prior to surgery. The Pentacam is one of many systems utilized in the screening process, but the literature has not identified specific protocol nor parameters that are capable of carrying out this process appropriately. Post-operative keratoconus continues to occur despite the advances in technology seen in corneal imaging. Therefore, clear indices for screening are required in order to diagnose early forms of keratoconus and other corneal diseases that may exclude the seemingly asymptomatic patient from undergoing refractive surgery. This article aims to summarize the indices available on the Pentacam system and to identify the most accurate parameters for screening of the refractive surgery candidate.
Nobeyama 45 m mapping observations toward Orion A. I. Molecular outflows

We conducted an exploration of ${}^{12}$CO molecular outflows in the Orion A giant molecular cloud to investigate outflow feedback using ${}^{12}$CO ($J = 1\! -\! 0$) and ${}^{13}$CO ($J = 1\! -\! 0$) data obtained by the Nobeyama 45 m telescope. In the region excluding the center of OMC 1, we identified 44 ${}^{12}$CO (including 17 newly detected) outflows based on the unbiased and systematic procedure of automatically determining the velocity range of the outflows and separating the cloud and outflow components. The optical depth of the ${}^{12}$CO emission in the detected outflows is estimated to be approximately 5. The total momentum and energy of the outflows, corrected for optical depth, are estimated to be $1.6 \times 10^{2}\, M_{\odot }\:$km$\:$s$^{-1}$ and $1.5\times 10^{46}\:$erg, respectively. The momentum and energy ejection rate of the outflows are estimated to be 36% and 235% of the momentum and energy dissipation rates of the cloud turbulence, respectively. Furthermore, the ejection rates of the outflows are comparable to those of the expanding molecular shells estimated by Feddersen et al. (2018, ApJ, 862, 121). Cloud turbulence cannot be sustained by the outflows and shells unless the energy conversion efficiency is as high as 20%.
How vines deal with salt

Water used for irrigation generally contains some level of dissolved salt. There are a number of ways to measure the salt concentration of irrigation water, ranging from the standard weight per volume measure (mg/litre or parts per million, ppm) to units of electrical conductivity (EC). Salinity of River Murray water, for example, is generally given as ‘EC’ units (μS/cm). The unit most often used by scientists is dS/m. An electrical conductivity of 1 dS/m is equivalent to 1000 ‘EC’ units (1000 μS/cm), which in turn is equivalent to 640 mg/litre (ppm) of soluble salts or the older term of 45 grains per gallon. Various salts can be present in irrigation water. River Murray Water, for example, contains chloride, sodium, sulphate, bicarbonate, calcium and magnesium with sodium and chloride the predominant ions (Gutteridge, Haskins and Davey, 1970). When plants transpire by taking-up water from the soil solution there is some filtering-out of ions as the water enters and moves through the roots. Some plants can also partition chloride and sodium ions to trunk, petiole and other tissues to minimise the accumulation of these ions in the laminae (leaf blade) and fruit (Greenway and Munns, 1980). This ability to limit uptake and movement of ions to the shoot varies amongst species and varieties and is generally referred to as ‘salt exclusion’. Plants with low abilities to exclude salt are often the most sensitive. The question of how vines deal with salt is also influenced by the type of irrigation method used. Overhead irrigation wets the leaves with water containing salt resulting in direct absorption of salt through the leaf surface. Such foliar absorption of salt can be minimised by irrigating during the evening (Ehlig and Bernstein, 1959). Undervine irrigation methods confine the delivery of dissolved salts to the rootzone. Rootstocks vary in their ability for salt exclusion and are therefore important in order to avoid excessive accumulation of chloride and/or sodium in leaves and berries and to ensure that levels in grape juice and wine do not exceed acceptable limits. This paper will focus on the response of grapevines to undervine irrigation with saline water.
A Step Towards the Optimal Estimation of Image Orientation

Generally speaking, the orientation of an image can easily be recognized by human beings. On the other hand, recognizing the orientation of an image is one of the challenges facing digital image processing. Several attempts have been made in this research area. However, the optimal solution still needs to be determined. For such a solution, the main issue is to obtain the precise angle for possible rotation. Numerous attempts have been made to address this issue; some of them mainly focus on coarse angles, whereas others have applied fuzzy logic in order to determine more precise angles. In this paper, a two-stage method is introduced in which a coarse angle estimation is achieved through the use of the Convolutional Neural Network (CNN) approach, and a more precise angle is acquired via fuzzy logic. An extensive evaluation of the proposed method is carried out on different public datasets. The results indicate an outstanding level of performance in terms of optimizing image orientation.