Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison between anterior cervical discectomy with fusion and anterior cervical corpectomy with fusion for the treatment of cervical spondylotic myelopathy: a meta-analysis

Background Whether anterior cervical discectomy with fusion (ACDF) or anterior cervical corpectomy with fusion (ACCF) is superior in the treatment of cervical spondylotic myelopathy remains controversial. Therefore, we conducted a meta-analysis to quantitatively compare the efficacy and safety of ACDF and ACCF in the treatment of cervical spondylotic myelopathy. Methods PubMed, Embase, Web of Science, SinoMed (Chinese BioMedical Literature Service System, People’s Republic of China), and CNKI (China National Knowledge Infrastructure, People’s Republic of China) were systematically searched to identify all available studies comparing efficacy and safety between patients receiving ACDF and ACCF. The weighted mean difference (WMD) was pooled to compare the Japanese Orthopaedic Association scores, visual analog scale scores, hospital stay, operation time, and blood loss. The risk ratio was pooled to compare the incidence of complications and fusion rate. Pooled estimates were calculated by using a fixed-effects model or a random-effects model according to the heterogeneity among studies. Results Eighteen studies (17 observational studies and one randomized controlled trial) were included in this meta-analysis. Our results suggest that hospital stay (WMD =−1.33, 95% confidence interval [CI]: −2.29, −0.27; P=0.014), operation time (WMD =−26.9, 95% CI: −46.13, −7.67; P=0.006), blood loss (WMD =−119.36, 95% CI: −166.94, −71.77; P=0.000), and incidence of complications (risk ratio =0.51, 95% CI: 0.33, 0.80; P=0.003) in the ACDF group were significantly less than that in the ACCF group. However, other clinical outcomes, including post-Japanese Orthopaedic Association score (WMD =−0.27, 95% CI: −0.57, 0.03; P=0.075), visual analog scale score (WMD =0.03, 95% CI: −1.44, 1.50; P=0.970), and fusion rate (risk ratio =1.04, 95% CI: 0.99, 1.09; P=0.158), between the two groups were not significantly different. Conclusion Evidence from the meta-analysis of 18 studies demonstrated that surgical options of cervical spondylotic myelopathy using ACDF or ACCF seemed to have similar clinical outcomes. However, ACDF was found to be superior to ACCF in terms of hospital stay, operation time, blood loss, and incidence of complications.
Web Based Distributed Network Analyzer Using SES Over Service Oriented Architecture

As the network uses, and especially the number of internet users, increases rapidly, an efficient system for managing large network traffic datasets becomes an important issue. Although there are several network traffic analysis tools such as tcpdump, Ethereal, and other applications, these tools have weaknesses: limited size of files, command line execution, large memory and huge computational power requirement, and complications. In addition to these scalability limitations, both tcpdump and Ethereal have a security issue. Files captured by these tools keep all the packet information such as IP addresses, port numbers, and packet sizes. As well as basic network traffic information, captured files contain secure information: user identification numbers (IDs) and passwords. Therefore, captured files should not allow to be leaked out. However, network analyses need to be performed outside target networks in some cases. The paper presents an approach to efficiently and quickly analyze large amount of network behaviors. This is achieved by applying System Entity Structure SES) theory. To speed up evaluation time, a webbased distributed simulation approach over Service Oriented Architecture (SOA) is applied. Discrete Event System Specification/Service Oriented Architecture (DEVS/SOA) is used to deploy workloads into multi-servers, increasing overall system performance. A web-based distributed simulation contains two fundamental processes: distributing and analyzing among loosely coupled models through message-passing methods. The distributed simulation— allocating distributing models inside networks and assigning analyzing models outside networks—also allows analysis of network behaviors out of networks while keeping important information secured.
Modeling the wind circulation around mills with a Lagrangian stochastic approach

This work aims at introducing model methodology and numerical studies related to a Lagrangian stochastic approach applied to the computation of the wind circulation around mills. We adapt the Lagrangian stochastic downscaling method that we have introduced in [3] and [4] to the atmospheric boundary layer and we introduce here a Lagrangian version of the actuator disc methods to take account of the mills. We present our numerical method and numerical experiments in the case of non rotating and rotating actuator disc models. We also present some features of our numerical method, in particular the computation of the probability distribution of the wind in the wake zone, as a byproduct of the fluid particle model and the associated PDF method.
Infrastructures for Patient-centeredness: connecting Novel and Existing Components to Serve Strategic Agendas for Change

Web-based access to health services, health information and personal health records are increasingly offered to patients for enabling a new, more active patient role. However, incorporating such solutions into national health infrastructures poses challenges. In an information infrastructure perspective, the design of such technologies requires two main intertwined activities: designing ‘the new’ and dealing with ‘the old’ (i.e. the already established infrastructural arrangement). In this paper, we study such activities through the concept of institutional work to investigate how actors go about creating, maintaining and disrupting what was established in provider-centric healthcare. This is investigated in the context of an ongoing national initiative to design and develop a web-based, platform that will support shifting healthcare towards patient-centeredness. Analysing actors’ efforts for “patient authentication”, “availability” and “comprehensiveness”, we identify the pivotal role of activities that are about rearranging seemingly separate technological and institutional components.
Neuronal death in Alzheimer’s disease and therapeutic opportunities

• Introduction • Origin of the disease and mechanisms for neuronal death in AD – Inflammatory reaction – Aβ‐induced neurotoxicity – Complement‐mediated neurodegeneration – Oxidative and nitrosylative damage – Proteasome inhibitor‐induced neurotoxicity – Cholesterol‐induced neurotoxicity – Viral infections – Interrelationship between different aetiopathogenic theories of AD • Treatment approaches – Drugs which modify AD symptoms – Cholinergic treatment – Antiglutamic treatment – β‐ and γ‐secretase inhibitors – Drugs which potentially prevent and modify AD symptoms – Vitamins and antioxidants – Non‐steroidal anti‐inflammatory drugs – Oestrogen replacement therapy – Inhibitors of complement‐mediated degeneration – Cobra venom factor (CVF) – Heparin and other polyionic agents – Other small molecule inhibitors – Recombinant protein inhibitors – Anti‐amyloid therapy (‘vaccination’) – Targeting proteasome inhibition – Neuropeptide mixture (Cerebrolysin) • Conclusions
Attribution of Precipitation Changes on a Regional Scale by Neural Network Modeling: A Case Study

On a regional scale, climate variability masks any direct link between external forcings and precipitation values. Thus, the problem of attribution of precipitation changes splits into two distinct steps: understanding how forcings influence circulation patterns and finding relationships between these patterns and the behavior of precipitation. Here, we deal with this second step, by analyzing data about eight circulation indices and their influence on precipitation anomalies in an extended Italian Alpine region. The methods used are bivariate nonlinear analysis and neural network modeling. We identify the most influential circulation patterns in each season and work out neural network models that are able to substantially describe the climate variability of precipitation at this regional scale.
Topology and existence of 3D anisotropic ﬁlamentary kinematic dynamos

Curvature and helicity topological bounds for the magnetic energy of the streamlines magnetic structures of a kinematic dynamo ﬂow are computed. The existence of the ﬁlament dynamos are determined by solving the magnetohydrodynamic equations for 3D ﬂows and the solution is used to determine these bounds. It is shown that in the limit of zero resistivity ﬁlamentary dynamos always exists in the isotropic case, however when one takes into account that the Frenet frame does not depend only of the ﬁlament length parameter s, (anisotropic case) the existence of the ﬁlamentary dynamo structure depends on the curvature in the case of screwed dynamos. Frenet curvature is associated with forld and torsion to twist which allows us to have a sretch, twist, and fold method to build fast ﬁlament dynamos. Arnold theorem for the helicity bounds of energy of a divergence-free vector ﬁeld is satisﬁed for these streamlines and the constant which depends on the size of the compact domain MCR 2 , where the vector ﬁeld is deﬁned is determined in terms of the dimensions of the constant cross-section ﬁlament. It is shown that when the Arnold theorem is violated by the ﬁlament ampliﬁcation of the magnetic ﬁeld structure appears, the magnetic ﬁeld decays in space. numbers: 02.40. Hw:Riemannian geometries
Porting and evaluation of automatic summarization

The ScandSum research network (ScandSum 2003) has helped coordinate Nordic research on summarization, especially for the Scandinavian languages. Such a research effort was badly needed, since at present there is a lack of usable tools for summarization targeted at those languages. In today’s information society, the overflow of textual information, especially on the Internet and increasingly delivered through mobile devices, makes summarization useful and sometimes indispensable. The current state of the art is primarily based on extraction techniques which attempt to identify and retain the most relevant sentences in a text. The resulting extract should ideally contain enough information to satisfy the user’s needs and at the same time it should not contain any redundant or superfluous information. The user s needs can roughly be described as either indicative (topic of the text) or informative (central information in the text). Spotting keywords and named entities in a text are useful for attaining these goals. A further requirement for a summary is that it should ideally be a fluent text without any gaps that could be misleading to the reader. In particular, missing antecedents of anaphors may cause problems. Therefore, anaphor resolution techniques may help to increase the quality of summaries. It is difficult to formulate what makes an ideal summary. Therefore any effort at automatic summarization must carefully assess user s needs. Research will clearly benefit from an analysis of human summarization and a comparative evaluation of machine generated summaries. Further reading about the research field can be found in (Mani & Maybury 1999)
The Lack of Broad-Line Regions in Low Accretion Rate Active Galactic Nuclei as Evidence of Their Origin in the Accretion Disk

In this Letter, we present evidence suggesting that the absence or presence of hidden broad-line regions (HBLRs) in Seyfert 2 galaxies is regulated by the rate at which matter accretes onto a central supermassive black hole, in units of the Eddington rate. Evidence is based on data from a subsample of type 2 active galactic nuclei extracted from the Tran spectropolarimetric sample and made up of all those sources that also have good-quality X-ray spectra available and for which a bulge luminosity can be estimated. We use the intrinsic (i.e., unabsorbed) X-ray luminosities of these sources and their black hole masses (estimated by using the well-known relationship between nuclear mass and bulge luminosity in galaxies) to derive the nuclear accretion rate in Eddington units. We find that virtually all HBLR sources have accretion rates larger than a threshold value of thres ≃ 10-3 (in Eddington units), while non-HBLR sources lie at ≲ thres. These data nicely fit predictions from a model proposed by Nicastro in which the broad-line regions (BLRs) are formed by accretion disk instabilities occurring in proximity of the critical radius at which the disk changes from gas pressure dominated to radiation pressure dominated. This radius diminishes with decreasing ; for low enough accretion rates (and therefore luminosities), the critical radius becomes smaller than the innermost stable orbit and BLRs cannot form.
The Computational Complexity Column

Although the ﬁeld of “parameterized complexity” has been around for several years and has generated a large and varied literature, the ﬁeld is still unknown to a large segment of the theory community, and it is misunder-stood by many who have only a vague notion of the ﬁeld. The article below is not only entertaining and highly readable, but it also explains how the ﬁeld of parameterized complexity complements other eﬀorts in theoretical computer science, in combining practical approaches and theoretical tools to attack the fundamental problems in complexity and algorithm design.
Expanding Thinking Through a Kaleidoscopic Look Into the Future

The field of mixed methods research abounds with opportunities for creative development in terms of methodological advances and potential to contribute to important and complex societal problems. Inspired by issues that arose in the Mixed Methods International Research Association task force report on the future of mixed methods, this article contemplates its implications for challenges and opportunities for the mixed methods community for advancement in philosophy and methodology, innovative designs, technological advancements and big data, preparation of mixed methods researchers, and responsiveness to complex societal problems. We invite the mixed methods research community to participate in the conversation about these important, as yet unanswered, questions relevant for the future of mixed methods research and the world.
Observing Republican and Democrat Behavior through

The increasing personalization of the web, particularly social media, has placed users in a “filter bubble”. Within this bubble users only see political content that reinforces their existing biases, while content that presents alternative views is filtered out. This proposal outlines a strategy for popping the filter bubble. This project builds upon previous social network and Natural Language Processing (NLP) research to devise methods to cluster and classify not just users, but also the news articles shared through social networks, which is a task not yet explored in academic research. Ultimately, we were able to create an automated system which determines the topics about which Republicans and Democrats are sharing articles and the degree to which the topics are being talked about by either group, among other data. The final result is web application which automatically generates a visualization of the topics being discussed by both groups, the keywords associated with those topics, and the domains shared most frequently by either group. Furthermore, our system is completely automated and generalizable to any two groups. Hence it could be used to detect tweeting differences between any two arbitrary groups.
Multi-Robot Task Allocation Based on Swarm Intelligence

The task allocation was studied based on the swarm inteeligence for the large-scale multi-robot system with loose-and tight-coupled tasks adopting the hierarchial architecture. In the high level,the ant colony algorithm was employed to find the optimal allocation of the loose-coupled tasks,namely,based on the reverse distribution idea,taking each ant to form a task,an undertaker was chosen for every task. In the low level,the coalition formation algorithms based on the ant colony optimization(ACO) ,the particle swarm and ant colomy optimization(PSACO) ,or the quantum-inspised ant colony optimization(QACO) was proposed respectively for performin a tight-coupled task.Simulations were performed and results showed that PSACO provides the best solution,but its running time is the largest;QACO is a little inferior in solution quality to PSACO,however,it needs only a half time of the 2 other methods. Therefore,QACO appears more suitable for the task allocation of the large-scale multi-robot system.
Information Aggregation and Efficiency in Agency Contracts with Endogenous Externality

In this paper we investigate the principal-multi agent relationship with moral hazard where a risk neutral principal contracts with multiple risk averse agents whose actions are unobservable to the principal. We show that the well--known trade--off between incentive and risk sharing can be asymptotically resolved as the number of agents becomes sufficiently large, when an arbitrary fraction of agents can obtain unverifiable perfect signals about the actions of other agents. In particular the contract to attain the asymptotic efficiency has the following features: (i) The wage schemes to some agents are contingent on the task performances of other agents as well as their own performances even though all of them are technologically and statistically independent each other. (ii) The wage scheme specifies only two payment levels for each agent. (iii) The principal does not need to observe all the performances of agents. (iv) The almost first best is uniquely implemented.
Mapping with an Autonomous Car

In this paper, we present an approach towards mapping and safe navigation in real, large-scale environments with an autonomous car. The goal is to enable the car to autonomously navigate on roads while avoiding obstacles and while simultaneously learning an accurate three-dimensional model of the environment. To achieve these goals, we apply probabilistic state estimation techniques, network-based pose optimization, and a sensor-based traversability analysis approach. In order to achieve fast map learning, our system compresses the sensor data using multi-level surface maps. The overall systems runs on a modified Smart car equipped with different types of sensors. We present several results obtained from extensive experiments which illustrate the capabilities of our vehicle.
Leadership in Prisoner ’ s Dilemma with Inequity Aversive Preferences ∗

We develop a new economic theory of leadership in which a leader-follower relationship endogenously emerges in consequences of players’ heterogeneous inequity aversions. We study a prisoner’s dilemma in which players are endowed with Fehr and Schmidt preferences with inequity aversions as their private information and then choose cooperation or defection once at one of two timings that they prefer. We provide a sufficient condition for the existence of leadership equilibrium. Who takes the leadership depends on game parameters. We provide a characterization of the equilibrium leadership patterns. We present an application to organizational design. JEL Classification: C72, D03, D82
The Voronoi Diagram of Convex Objects in the Plane

This paper presents a dynamic algorithm for the construction of the Euclidean Voronoi diagram of a set of convex objects in the plane. We consider first the Voronoi diagram of smooth convex objects forming pseudo-circles set. A pseudo-circles set is a set of bounded objects such that the boundaries of any two objects intersect at most twice. Our algorithm is a randomized dynamic algorithm. It does not use a conflict graph or any sophisticated data structure to perform conflict detection. This feature allows us to handle deletions in a relatively easy way. In the case where objects do not intersect, the randomized complexity of an insertion or deletion can be shown to be respectively O(^2 n) and O(^3 n). Our algorithm can easily be adapted to the case of pseudo-circles sets formed by piecewise smooth convex objects. Finally, given any set of convex objects in the plane, we show how to compute the restriction of the Voronoi diagram in the complement of the objects' union.
Keyword-Labeled Classification with Auxiliary Unlabeled Documents

To reduce the human effort in labeling the training set for document classification, some learning algorithms ask users to give the representative keywords for each class rather than any labeled documents. The key challenge in such \emph {keyword-labeled classification} is how to learn the high quality classifier with very small number of keywords. In this paper, we propose a novel co-clustering based classification algorithm for keyword-labeled classification (CCKC) by utilizing auxiliary unlabeled documents. The experimental results show our algorithm greatly improves the classification performance over existing approaches.
A Fast Solution to the Surface Reconstruction

Surface reconstruction from range data acquired using a vareity of sources has been a very active area of research in computational vision over the past decade. Generalized splines have emerged as the single most popular approximation tool to this end. In this paper we present a new and fast algorithm for solving the surface reconstruction problem using the membrane spline which yields a C 0 surface. Our algorithm for dense data constraints takes O(N) computational time, where N is the number of nodes in the discretization. For sparse data constraints, the algorithm requires O(log N== 2) iterations with each iteration taking O(N) time. The number of iterations in this case depends on a prespeciied error tolerance. We demonstrate the algorithm performance on synthesized sparse range data.
Selective partial access to a database

A system to support a multi-function, shared-access database requires the capability of defining for each user an arbitrary subset of the fields of a logical record to which access is allowed. The feasibility of such a capability has already been demonstrated by several operational systems. This paper is concerned with the possibility of granting something less than complete access to a specified field of a record. The purpose would be to allow a user to perform various summary and statistical tasks over controlled fields without allowing identification of the exact value of a field in a particular record. Three different strategies are examined: 1. An arbitrary partition of values is defined for each restricted field. A user granted this type of access can determine only which class of the partition contains the field value. 2. The actual field value is distorted by a random perturbation. 3. Access to actual field values is allowed—but values are dissociated from the actual record in which they occur. The third strategy—dissociation—appears to be the most interesting, potentially useful, but potentially vulnerable. In each case, the utility of incomplete access is examined and various implementation alternatives are explored. The degree of protection against persistent assault is determined.