Miracle-dz/UniFAR-FTUs huggingface dataset:
IMAGING THE BLACK HOLE SILHOUETTE OF M87: IMPLICATIONS FOR JET FORMATION AND BLACK HOLE SPIN

The silhouette cast by the horizon of the supermassive black hole in M87 can now be resolved with the emerging millimeter very long baseline interferometry (VLBI) capability. Despite being ∼2 × 103 times farther away than Sagittarius A* (Sgr A*; the supermassive black hole at the center of the Milky Way and the primary target for horizon-scale imaging), M87's much larger black hole mass results in a horizon angular scale roughly half that of Sgr A*'s, providing another practical target for direct imaging. However, unlike Sgr A*, M87 exhibits a powerful radio jet, providing an opportunity to study jet-formation physics on horizon scales. We employ a simple, qualitatively correct force-free jet model to explore the expected high-resolution images of M87 at wavelengths of 1.3 mm and 0.87 mm (230 GHz and 345 GHz), for a variety of jet parameters. We show that future VLBI data will be able to constrain the size of the jet footprint, the jet collimation rate, and the black hole spin. Polarization will further probe the structure of the jet's magnetic field and its effect on the emitting gas. Horizon-scale imaging of M87 and Sgr A* will enable for the first time the empirical exploration of the relationship between the mass and spin of a black hole and the characteristics of the gas inflow/outflow around it.
Grade and Subtype Classification for Glioma Tumors using Clinical and Molecular Mutations

Gliomas are insidious brain tumors with varying attributes, and their traditional methods of prognosis suffer from notable limitations. In addressing these challenges, we conduct a study on the classification of tumor grades and subtypes, utilizing The Cancer Genome Atlas (TCGA) dataset consisting of 862 data instances. We leverage six feature selection techniques, and several machine learning models, which are scrutinized using metrics like accuracy, F1 score and others. Our experimental results highlight Mutual Information, Chi-Square and Lasso as the best feature selection techniques. We achieve a validation accuracy of 90.70% for grade classification using Mutual Information with an ensemble model of Logistic Regression, KNN and SVM, as well as using two other feature selection-classifier combinations. We further achieve a validation accuracy of 84.88% for subtype classification, using the Bagging classifier with Mutual Information Feature selection. Our framework obtains a higher performance in terms of validation accuracy as compared to the performance of other state of the art classifiers.
RSD: A Safety Decision-Making Algorithm Under Cyber Attacks for Natural Disaster Monitoring

As global temperatures increase, forest fires have increased in frequency and size. The multi-robot system can monitor the fire spread trend in real-time and provide effective information for the global decision-making center. Furthermore, attackers may prevent some robots from making optimal decisions. Therefore, this paper studies the multi-robot cooperative forest fire monitoring problem under cyber attacks, where each robot has the ability to make autonomous decisions. First, the forest fire monitoring problem is considered as a maximum area coverage problem, and the single-step actions of each robot are selected based on the principle of maximizing the submodular function. Based on this, this paper proposes a robust decision-making algorithm that can minimize the attacker's influence on the decision, even in the worst case. Finally, the simulation results verify that the proposed algorithm can achieve maximum forest fire monitoring.
Structural insights into the molecular mechanism of the m6A writer complex

Methylation of adenosines at the N6 position (m6A) is a dynamic and abundant epitranscriptomic mark that regulates critical aspects of eukaryotic RNA metabolism in numerous biological processes. The RNA methyltransferases METTL3 and METTL14 are components of a multisubunit m6A writer complex whose enzymatic activity is substantially higher than the activities of METTL3 or METTL14 alone. The molecular mechanism underpinning this synergistic effect is poorly understood. Here we report the crystal structure of the catalytic core of the human m6A writer complex comprising METTL3 and METTL14. The structure reveals the heterodimeric architecture of the complex and donor substrate binding by METTL3. Structure-guided mutagenesis indicates that METTL3 is the catalytic subunit of the complex, whereas METTL14 has a degenerate active site and plays non-catalytic roles in maintaining complex integrity and substrate RNA binding. These studies illuminate the molecular mechanism and evolutionary history of eukaryotic m6A modification in post-transcriptional genome regulation. DOI: http://dx.doi. org/10.7554/eLife.18434. 001
Voltage-Gated Potassium Channel Kv1.3 Is Highly Expressed in Human Osteosarcoma and Promotes Osteosarcoma Growth

Deregulation of voltage-gated potassium channel subunit Kv1.3 has been reported in many tumors. Kv1.3 promotes tumorigenesis by enhancing cell proliferation while suppressing apoptosis. However, the expression and function of Kv1.3 in osteosarcoma are unknown. In the present study, we detected the expression of Kv1.3 in human osteosarcoma cells and tissues by RT-PCR, Western blot and immunohistochemistry. We further examined cell proliferation and apoptosis in osteosarcoma MG-63 cells and xenografts following knockdown of Kv1.3 by short hairpin RNA (shRNA). We found that Kv1.3 was upregulated in human osteosarcoma. Knockdown of Kv1.3 significantly suppressed cell proliferation and increased apoptosis as demonstrated by enhanced cleavage of poly (ADP-ribose) polymerase (PARP) and the activation of Caspase-3/7. Furthermore, adenovirus delivered shRNA targeting Kv1.3 significantly inhibited the growth of MG-63 xenografts. Taken together, our results suggest that Kv1.3 is a novel molecular target for osterosarcoma therapy.
Highly Efficient Simulation and Visualization of Acoustic Wave Fields

The Functional Transformation Method is an established method for digital sound synthesis via physical modeling. It starts from a physical description of the sounding object in form of a partial differential equation and solves it by suitable integral transformation in the frequency domain. After discretization, the resulting algorithms are fast enough to be implemented in full audio sample-rate. In this paper new results are presented, that extend the evaluation of the model into an efficient visualization of all physical processes with constant coefficients over regions with separable boundary conditions. In particular the simulation of wave fields is shown. A simulation program is presented, that creates animations of two-dimensional wave propagation in real-time. Furthermore, an application to the analysis of a new multi-channel sound reproduction method is shown.
Stochastic Models of User-Contributory Web Sites

We describe a general stochastic processes-based approach to modeling user-contributory web sites, where users create, rate and share content. These models describe aggregate measures of activity and how they arise from simple models of individual users. This approach provides a tractable method to understand user activity on the web site and how this activity depends on web site design choices, especially the choice of what information about other users' behaviors is shown to each user. We illustrate this modeling approach in the context of user-created content on the news rating site Digg.
Energy efficient runtime approximate computing on data flow graphs

Approximate computing is an emerging computation paradigm that utilizes many applications' intrinsic error resilience to improve power and energy efficiency. Several approaches have been proposed to identify the non-critical computations by analyzing the output sensitivity to the accuracy of the results, and then perform approximate computing on these computations. However, these static approaches only use the prior knowledge (e.g. input ranges) for analysis and fail to consider the runtime information, which limits the energy saving and incurs large computation error. In this paper, we propose a runtime approximate computing framework to solve this problem. The basic idea is to use a low cost method to estimate the impact of each immediate input value to the accuracy of computation at every node in the data flow graph, and then decide whether we should simply use the estimated value or perform an accurate computation. Our novel runtime estimation method is based on converting data to the logarithmic representation. We propose two algorithms to make the decision at certain nodes whether an accurate computation will be needed to balance energy saving and computation error. Experimental results show that this tradeoff ranges from 40% energy saving with 4.85% error on average to 8% energy saving with 0.18% error. Compared to the static DFG node cutting approach, our approach's estimation accuracy is 32x better to achieve the same amount of energy saving.
Mining Medical Records for Computer Aided Diagnosis

Over the last five years, a new generation of medical data mining tools have dramatically impacted the health care industry by improving the diagnosis of medical diseases and by reducing the time pressure on physicians and nurses. Our demonstration highlights three products for the the health care industry, showcasing the potential of novel data mining technologies to save lives on a large scale. During the demonstration, our products will use real-life (de-identified) patient data, in an effort to convey the practical and theoretical challenges unique to data from the medical domain.
Convex and linear models of NP-problems

Reducing the NP-problems to the convex/linear analysis on the Birkhoff polytope. Introduction Since the classical works of J. Edmonds [2, and others], linear modeling became a common technique in combinatorial optimization [8, 9, 13, 14, 15, 16, and others]. Often, the linear models are expressed with some constrains on the incidence vector. The major benefit of this approach is the symmetry of the resulting model: the resulting equations are an invariant under relabeling. The major disadvantage of the approach is difficulty to express the constrains explicitly due to their size and structural complexity [8, 9, 13, and others]. In this work, the Subgraph Isomorphism Problem [3, 4, 7, 11] is taken as a basic NP-problem. The adjacency and incidence matrices are used to express the linear and convex models explicitly. In such asymmetric models, the unknown is a relabeling. The relabeling is presented with an unknown permutation matrix. That reduces the NP-problems to the linear/convex analysis on the Birkhoff polytope [1]. 1. Adjacency matrix models Let’s take the Subgraph Isomorphism Problem [3, 4, 7]: whether a given multi digraph g contains a subgraph which is isomorphic with another given multi digraph s. That is a NP-complete problem. Let n and m be powers of vertex-sets of g and s, appropriately. Based on a node labeling/enumeration, let’s construct adjacency matrices of these digraphs matrices G and S, appropriately. In terms of these matrices, the problem is a compatibility problem for the following quadratic system where the unknown is permutation matrix X = (xij)n×n: (1.1) PmnX T GXP T mn ≥ S Here, matrix Pmn is a truncation: Pmn = (Um 0)m×n, where matrix Um is the union matrix of size m × m. Permutation matrix X presents all n! possible ways to label vertices of (multi) digraph g. Compatibility of system 1.1 means that there is such a vertex labeling of digraph g that the appropriate adjacency matrix of that digraph will “cover” the adjacency matrix of (multi) digraph s. Such a labeling of g would make the positive solution for instance (g, s) the self evident. Obviously, if the system is 2000 Mathematics Subject Classification. Primary 68Q15, 68R10, 90C57.
Describing the Web in less than 140 Characters

Links curation, that is, finding relevant information within the World-Wide-Web and its ever-growing amount of content is a crucial problem for information access. Hyperlinks recommendation has been for a long time a common way to share references between web users, be it by e-mail exchanges, instant messages or forums. We explore in this paper how Social Media extend this recommendation practice by focusing on the citation of hyperlinks on Twitter. We investigate how people deal with the strong limitation of 140 characters per message, showing that this constraint encourages people to perform a good synthesis of the content they are linking to. We take advantage of this practice to efficiently cluster the actual content of the linked pages with an algorithm based on lexical proximities between messages. Our method yields topical clusters that are consistent with the dynamics of user interests with no need to extract text from the pages themselves.
On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank One Perturbations of Gaussian Tensors

We consider the following detection problem: given a realization of a symmetric matrix X of dimension <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>, distinguish between the hypothesis that all upper triangular variables are independent and identically distributed (i.i.d). Gaussians variables with mean 0 and variance 1 and the hypothesis, where X is the sum of such matrix and an independent rank-one perturbation. This setup applies to the situation, where under the alternative, there is a planted principal submatrix B of size <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> for which all upper triangular variables are i.i. d. Gaussians with mean 1 and variance 1, whereas all other upper triangular elements of X not in B are i.i. d. Gaussians variables with mean 0 and variance 1. We refer to this as the “Gaussian hidden clique problem. ” When <inline-formula> <tex-math notation="LaTeX">$L=(1+\epsilon )\sqrt {n}$ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$\epsilon >0$ </tex-math></inline-formula>), it is possible to solve this detection problem with probability <inline-formula> <tex-math notation="LaTeX">$1-o_{n}(1)$ </tex-math></inline-formula> by computing the spectrum of X and considering the largest eigenvalue of X. We prove that this condition is tight in the following sense: when <inline-formula> <tex-math notation="LaTeX">$L<(1-\epsilon )\sqrt {n}$ </tex-math></inline-formula> no algorithm that examines only the eigenvalues of X can detect the existence of a hidden Gaussian clique, with error probability vanishing as <inline-formula> <tex-math notation="LaTeX">$n\to \infty $ </tex-math></inline-formula>. We prove this result as an immediate consequence of a more general result on rank-one perturbations of <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-dimensional Gaussian tensors. In this context, we establish a lower bound on the critical signal-to-noise ratio below which a rank-one signal cannot be detected.
Myoglobin oxygen affinity in aquatic and terrestrial birds and mammals

ABSTRACT Myoglobin (Mb) is an oxygen binding protein found in vertebrate skeletal muscle, where it facilitates intracellular transport and storage of oxygen. This protein has evolved to suit unique physiological needs in the muscle of diving vertebrates that express Mb at much greater concentrations than their terrestrial counterparts. In this study, we characterized Mb oxygen affinity (P50) from 25 species of aquatic and terrestrial birds and mammals. Among diving species, we tested for correlations between Mb P50 and routine dive duration. Across all species examined, Mb P50 ranged from 2.40 to 4.85 mmHg. The mean P50 of Mb from terrestrial ungulates was 3.72±0.15 mmHg (range 3.70–3.74 mmHg). The P50 of cetaceans was similar to terrestrial ungulates ranging from 3.54 to 3.82 mmHg, with the exception of the melon-headed whale, which had a significantly higher P50 of 4.85 mmHg. Among pinnipeds, the P50 ranged from 3.23 to 3.81 mmHg and showed a trend for higher oxygen affinity in species with longer dive durations. Among diving birds, the P50 ranged from 2.40 to 3.36 mmHg and also showed a trend of higher affinities in species with longer dive durations. In pinnipeds and birds, low Mb P50 was associated with species whose muscles are metabolically active under hypoxic conditions associated with aerobic dives. Given the broad range of potential globin oxygen affinities, Mb P50 from diverse vertebrate species appears constrained within a relatively narrow range. High Mb oxygen affinity within this range may be adaptive for some vertebrates that make prolonged dives. Summary: Myoglobin oxygen affinity varies among terrestrial and aquatic birds and mammals, with long-duration diving species having greater myoglobin oxygen affinity.
High accuracy visual odometry using multi-camera systems

This work proposed an improvement for the visual odometry based on a new hardware design concept. Generally, a visual odometry system relies on one stereo camera to detect the 3D features which are used as input for the ego motion estimation process. However, such design usually faced with the motion ambiguity problem resulting in poor estimation of the ego motion. The proposed multi-camera system solves this problem using an intuitive hardware design that enables a simple yet effective way to eliminate the motion ambiguity problems. Experiment results show that the proposed system yields better ego motion estimation compared to the conventional single camera system.
On the limits of DTN monitoring

Compared to wired networks, Delay/Disruption Tolerant Networks (DTN) are challenging to monitor due to their lack of infrastructure and the absence of end-to-end paths. This work studies the feasibility, limits and convergence of monitoring such DTNs. More specifically, we focus on the efficient monitoring of intercontact time distribution (ICT) between DTN participants. Our contribution is two-fold. First we propose two schemes to sample data using monitors deployed within the DTN. In particular, we sample and estimate the ICT distribution. Second, we evaluate this scheme over both simulated DTN networks and real DTN traces. Our initial results show that (i) there is a high correlation between the quality of sampling and the sampled mobility type, and (ii) the number and placement of monitors impact the estimation of the ICT distribution of the whole DTN.
Health Beliefs, Stages of Change and Smoking Behaviour in Portuguese College Students

The aim of this cross-sectional study is to explore, in a sample of 380 college students, if there are any differences between regular, occasional and ex-smokers regarding health value, perceived health competence and self-efficacy to refrain from smoking. Stages of change are also assessed according to the transtheoretical model. There were no significant differences between groups regarding the health value. However, perceived health competence and self-efficacy (to refrain from smoking) were significantly different for the different smoking status and several stages of change. These findings provide new insights into how college student's health-related perceptions relate to smoking behaviour, which may help in the elaboration of smoking cessation interventions for this population.
Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes.
Violence and mental disorder: Developments in risk assessment.

Preface List of Contributors 1: Toward a Rejuvenation of Risk Assessment Research John Monahan, Henry J. Steadman. 2: Anger as a Risk Factor for Violence among the Mentally Disordered Raymond W. Novaco 3: Impulsiveness and Aggression Ernest S. Barratt 4: Psychopathy as a Risk Marker for Violence: Development and Validation of a Screening Version of the Revised Psychopathy Checklist Stephen D. Hart, Robert D. Hare, Adelle E. Forth. 5: Mental Disorder, Substance Abuse, and Community Violence: An Epidemiological Approach Jeffrey W. Swanson 6: Psychotic Symptoms and the Violent/Illegal Behavior of Mental Patients Compared to Community Controls Bruce G. Link, Ann Stueve. 7: Delusions and Violence Pamela J. Taylor, Philippa Garety, Alec Buchanan, Alison Reed, Simon Wessely, Katarzyna Ray, Graham Dunn, Don Grubin. 8: Hallucinations and Violence Dale E. McNiel 9: Personality Disorders and Violence Thomas A. Widiger, Timothy J. Trull. 10: Demographic and Case History Variables in Risk Assessment Deidre Klassen, William A. O'connor. 11: Social Networks, Social Support, and Violence among Persons with Severe, Persistent Mental Illness Sue E. Estroff, Catherine Zimmer. Designing a New Generation of Risk Assessment Research Henry J. Steadman, John Monahan, Paul S. Appelbaum, Thomas Grisso, Edward P. Mulvey, Loren H. Roth, Pamela Clark Robbins, Deidre Klassen. Index
A simple method for isolation of genomic DNA from fresh and dry leaves of Terminalia arjuna ( Roxb . ) Wight and Argot

*Corresponding author Current protocols for isolation of genomic DNA from Terminalia Arjuna have their own limitations due to the presence of high content of gummy polysaccharides and polyphenols. DNA isolated by these protocols is contaminated with a yellowish, sticky and viscous matrix. In our modified DNA isolation method polysaccharides and polyphenols are removed prior to the precipitation of the DNA. Then the genomic DNA was precipitated using isopropanol. This protocol yielded a high molecular weight DNA isolated from fresh as well as dry leaves of T. Arjuna, which was free from contamination and colour. Isolated DNA can be used for restriction digestion and PCR amplification. The main objective of the present protocol is to provide a simple method of isolation of DNA, using in house prepared reagents.
Signal-dependent turnover of the bacterial flagellar switch protein FliM

Most biological processes are performed by multiprotein complexes. Traditionally described as static entities, evidence is now emerging that their components can be highly dynamic, exchanging constantly with cellular pools. The bacterial flagellar motor contains ∼13 different proteins and provides an ideal system to study functional molecular complexes. It is powered by transmembrane ion flux through a ring of stator complexes that push on a central rotor. The Escherichia coli motor switches direction stochastically in response to binding of the response regulator CheY to the rotor switch component FliM. Much is known of the static motor structure, but we are just beginning to understand the dynamics of its individual components. Here we measure the stoichiometry and turnover of FliM in functioning flagellar motors, by using high-resolution fluorescence microscopy of E. coli expressing genomically encoded YPet derivatives of FliM at physiological levels. We show that the ∼30 FliM molecules per motor exist in two discrete populations, one tightly associated with the motor and the other undergoing stochastic turnover. This turnover of FliM molecules depends on the presence of active CheY, suggesting a potential role in the process of motor switching. In many ways the bacterial flagellar motor is as an archetype macromolecular assembly, and our results may have further implications for the functional relevance of protein turnover in other large molecular complexes.