Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of CT screening on smoking habits at 1-year follow-up in the Danish Lung Cancer Screening Trial (DLCST)

Background: The effect of low-dose CT screening for lung cancer on smoking habits has not been reported in large randomised controlled trials. Methods: This study evaluated the effect on smoking habits of screening with low-dose CT at 1-year follow up in the Danish Lung Cancer Screening Trial (DLCST), a 5-year randomised controlled trial comprising 4104 subjects; 2052 subjects received annual low-dose CT scan (CT group) and 2052 received no intervention (control group). Participants were healthy current and former smokers (>4 weeks since smoking cessation) with a tobacco consumption of >20 pack years. Smoking habits were determined at baseline and at annual screening. Smoking status was verified using exhaled carbon monoxide levels. Lung function tests, nicotine dependency and motivation to quit smoking were assessed. Quit rates and relapse rates were determined at 1-year follow-up for all subjects. Results: At 1 year the quit rates among smokers were 11.9% in the CT group and 11.8% in the control group (p = 0.95). Relapse rates for former smokers were 10.0% and 10.5% in the CT and control groups, respectively (p = 0.81). Significant predictors (p<0.05) for smoking cessation were: high motivation to quit, low dependency, low ratio of forced expiratory volume in 1 s to forced vital capacity, low pack years, higher age, longer period of abstinence and CT findings necessitating 3-month repeat CT scans. Conclusions: Overall, quit rates were similar in the CT and control group at 1-year follow-up, with a net quit rate of 6.0%. Quit rates were higher and relapse rate lower among subjects with initial CT findings that necessitated a repeat scan 3 months later.
Journal of Theoretical and Applied Information Technology Efficient Resource Utilization of Web Using Data Clustering and Association Rule Mining

Data mining is a dominant technology which extorts the hidden information from the huge databases. Data mining techniques envisage future progressions and trends, acquiesce businesses to make practical, knowledge-actuate arbitration. Data clustering and association rule mining has attracted a lot of research interest in field of computational statistics and data mining. Web usage mining is an important application of data mining techniques and it is used to determine user navigation pattern from web log data. In this paper, the clustering technique is applied for grouping the users based on the ip address and association rule mining is used for finding the associations between the clustered groups. A hybrid Leaders complete linkage algorithm is used for clustering the users into groups and the Apriori algorithm is used for finding associations between the users. This approach reveals the individual access pattern of users.
The PDZ-binding Chloride Channel ClC-3B Localizes to the Golgi and Associates with Cystic Fibrosis Transmembrane Conductance Regulator-interacting PDZ Proteins*

ClC chloride channels are widely distributed in organisms across the evolutionary spectrum, and members of the mammalian family play crucial roles in cellular function and are mutated in several human diseases (Jentsch, T. J., Stein, V., Weinreich, F., and Zdebik, A. A. (2002) Physiol. Rev.82, 503–568). Within the ClC-3, -4, -5 branch of the family that are intracellular channels, two alternatively spliced ClC-3 isoforms were recognized recently (Ogura, T., Furukawa, T., Toyozaki, T., Yamada, K., Zheng, Y. J., Katayama, Y., Nakaya, H., and Inagaki, N. (2002)FASEB J. 16, 863–865). ClC-3A resides in late endosomes where it serves as an anion shunt during acidification. We show here that the ClC-3B PDZ-binding isoform resides in the Golgi where it co-localizes with a small amount of the other known PDZ-binding chloride channel, CFTR (cystic fibrosis transmembrane conductance regulator). Both channel proteins bind the Golgi PDZ protein, GOPC (Golgi-associated PDZ and coiled-coil motif-containing protein). Interestingly, however, when overexpressed, GOPC, which is thought to influence traffic in the endocytic/secretory pathway, causes a large reduction in the amounts of both channels, probably by leading them to the degradative end of this pathway. ClC-3B as well as CFTR also binds EBP50 (ERM-binding phosphoprotein 50) and PDZK1, which are concentrated at the plasma membrane. However, only PDZK1 was found to promote interaction between the two channels, perhaps because they were able to bind to two different PDZ domains in PDZK1. Thus while small portions of the populations of ClC-3B and CFTR may associate and co-localize, the bulk of the two populations reside in different organelles of cells where they are expressed heterologously or endogenously, and therefore their cellular functions are likely to be distinct and not primarily related.
Choroidal Neovascularization Due to Pathologic Myopia

H igh myopia, normally defined as myopia with refractive error less than-6.00 D, is common in Asian countries, with an incidence of 5% to 10%. In comparison, countries with a predominantly white population have a lower incidence. Complications such as macular hole with retinal detachment, myopic foveoschisis, and chorioretinal atrophy often develop with high myopia. Choroidal neovascularization (CNV) due to pathologic myopia (mCNV) is a major condition that threatens the vision of people with myopia. Its incidence is not well investigated ; however, a hospital-based study reported that the condition existed in 5% to 10% of highly myopic patients. 1 Myopia is the second most common cause of secondary CNV, accounting for 62% of CNV in patients less than 50 years of age. 2 mCNV often stabilizes without treatment; however, chorioretinal atrophy initiated from the CNV margin and gradually expanding during the chronic stage is a main cause of poor visual outcome over the long term. Chorioretinal atrophy is augmented by the loss of photoreceptors and by the obstruction of the choroidal vasculature and its replacement with fibrous tissue. 3 Yoshida et al reported that more than 80% of eyes with mCNV had a visual acuity better than 20/200 at the onset, but vision was preserved in less than 10% of eyes after 5 to10 years. 4 CLINICAL M ANIFE STA SIONS mCNV is normally small and grayish at the macula or adjacent to the crescent of the optic nerve head (Figure 1). This circular lesion, called Foerster-Fuchs spot, is often pigmented. According to the Verteporfin in Photodynamic Therapy study group, more than 70% of these lesions are of the classic type, and 65% of them are subfoveally located. The pathogenesis of this condition is unknown, but anti-VEGF treatment has shown promising therapeutic results. Figure 1. Typical fundus photograph (A), fluorescein angiography (B), and OCT appearance (C) of mCNV. This case presents juxtafoveal classic mCNV superotemporal to the fovea. Small subretinal hemorrhage and retinal detachment over CNV complex is observed on OCT. BCVA at this visit was 20/40.
The effect of fin ray flexural rigidity on the propulsive forces generated by a biorobotic fish pectoral fin

SUMMARY A biorobotic pectoral fin was developed and used to study how the flexural rigidities of fin rays within a highly deformable fish fin affect the fin's propulsive forces. The design of the biorobotic fin was based on a detailed analysis of the pectoral fin of the bluegill sunfish (Lepomis macrochirus). The biorobotic fin was made to execute the kinematics used by the biological fin during steady swimming, and to have structural properties that modeled those of the biological fin. This resulted in an engineered fin that had a similar interaction with the water as the biological fin and that created close approximations of the three-dimensional motions, flows, and forces produced by the sunfish during low speed, steady swimming. Experimental trials were conducted during which biorobotic fins of seven different stiffness configurations were flapped at frequencies from 0.5 to 2.0 Hz in flows with velocities that ranged from 0 to 270 mm s–1. During these trials, thrust and lift forces were measured, kinematics were recorded in three dimensions, and digital particle image velocimetry was used to evaluate flow hydrodynamics. The results of the trials revealed that slight changes to the fin's mechanical properties or to the operating conditions can have significant impact on the direction, magnitude and time course of the propulsive forces. In general, the magnitude of the 2-D (thrust and lift) propulsive force scaled with fin ray stiffness, and increased as the fin's flapping speed increased or as the velocity of the flow decreased.
Design and Evaluation of Serious Games for Cognitive Diagnosis and Stimulation with Older Adults : A Preliminary Study

The aging process is often influenced by brain diseases affecting cognitive and physical abilities. From a clinical perspective, methods for neuropsychological assessment and cognitive stimulation adapted for an older population are crucial to quantify the cognitive and functional decline. Ideally, these methods should include relaxed, non-tiring and engaging tasks in order to motivate the elderly. Serious Games that adapt the current neuropsychological tests in order to assess performance of the players can enable useful data collection for medical evaluation. Here were port on initial steps for a methodology concerning the development of serious games for cognitive assessment, involving usability tests on two proposed prototypes. We present and discuss the behavior of the players during usability tests: the responses of players to the interview. An analysis of relevant points from the study concerning the challenges of working with an older population has revealed that the main challenge of working with a senior population is to awaken in them an interest to use the games, fundamental to overcome an initial resistance; and that there is need to develop strategies to design simple, yet useful, motivating games, allowing the collection of relevant results for health professionals working with this target group.
Regularization parameter selection for a bayesian group sparse multi-task regression model with application to imaging genomics

We investigate the choice of tuning parameters for a Bayesian multi-level group lasso model developed for the joint analysis of neuroimaging and genetic data. The regression model we consider relates multivariate phenotypes consisting of brain summary measures (volumetric and cortical thickness values) to single nucleotide polymorphism (SNPs) data and imposes penalization at two nested levels, the first corresponding to genes and the second corresponding to SNPs. Associated with each level in the penalty is a tuning parameter which corresponds to a hyperparameter in the hierarchical Bayesian formulation. Following previous work on Bayesian lassos we consider the estimation of tuning parameters through either hierarchical Bayes based on hyperpriors and Gibbs sampling or through empirical Bayes based on maximizing the marginal likelihood using a Monte Carlo EM algorithm. For the specific model under consideration we find that these approaches can lead to severe overshrinkage of the regression parameter estimates in the highdimensional setting or when the genetic effects are weak. We demonstrate these problems through simulation examples and study an approximation to the marginal likelihood which sheds light on the cause of this problem. We then suggest an alternative approach based on the widely applicable information criterion (WAIC), an asymptotic approximation to leave-one-out crossvalidation that can be computed conveniently within an MCMC framework.
Vacancy-stabilized crystalline order in hard cubes

We examine the effect of vacancies on the phase behavior and structure of systems consisting of hard cubes using event-driven molecular dynamics and Monte Carlo simulations. We find a first-order phase transition between a fluid and a simple cubic crystal phase that is stabilized by a surprisingly large number of vacancies, reaching a net vacancy concentration of approximately 6.4% near bulk coexistence. Remarkably, we find that vacancies increase the positional order in the system. Finally, we show that the vacancies are delocalized and therefore hard to detect.
Predicate RCU: an RCU for scalable concurrent updates

Read-copy update (RCU) is a shared memory synchronization mechanism with scalable synchronization-free reads that nevertheless execute correctly with concurrent updates. To guarantee the consistency of such reads, an RCU update transitioning the data structure between certain states must wait for the completion of all existing reads. Unfortunately, these waiting periods quickly become a bottleneck, and thus RCU remains unused in data structures that require scalable, fine-grained, update operations. To solve this problem, we present Predicate RCU (PRCU), an RCU variant in which an update waits only for the reads whose consistency it affects, which are specified by a user-supplied predicate. We explore the trade-offs in implementing PRCU, describing implementations that reduce wait times by 10--100x with varying overhead on reads on modern x86 multiprocessor machines. We demonstrate the applicability of PRCU by applying it to two RCU-based concurrent algorithms---the Citrus binary search tree and a resizable hash table---and show experimentally that PRCU significantly improves the performance of both algorithms.
FTI: High performance Fault Tolerance Interface for hybrid systems

Large scientific applications deployed on current petascale systems expend a significant amount of their execution time dumping checkpoint files to remote storage. New fault tolerant techniques will be critical to efficiently exploit post-petascale systems. In this work, we propose a low-overhead high-frequency multi-level checkpoint technique in which we integrate a highly-reliable topology-aware Reed-Solomon encoding in a three-level checkpoint scheme. We efficiently hide the encoding time using one Fault-Tolerance dedicated thread per node. We implement our technique in the Fault Tolerance Interface FTI. We evaluate the correctness of our performance model and conduct a study of the reliability of our library. To demonstrate the performance of FTI, we present a case study of the Mw9.0 Tohoku Japan earthquake simulation with SPECFEM3D on TSUBAME2.0. We demonstrate a checkpoint overhead as low as 8% on sustained 0.1 petaflops runs (1152 GPUs) while check-pointing at high frequency.
Adult estimation, eye movements and math anxiety

Adult Estimation, Eye Movements and Math Anxiety By Robert T. Durette Dr. Mark H. Ashcraft, Examination Committee Chair Professor of Psychology University of Nevada, Las Vegas In this experiment the estimation ability of college undergraduates was examined using a number line task, with lines numbered 0-to-100, 0-to 1,000 and 0-to-723 presented on a computer monitor. Previous research on kindergarteners' through 6 graders' ability to estimate showed a progression from a logarithmic mental representation of numbers to a linear mental number line. Children's ability to estimate was found to correlate strongly with math achievement. We used this task to examine the hypothesis that remnants of the underlying logarithmic number line representation persist into adulthood despite formal educational experience with the number system (e.g. Dehaene, 1997). 0 to 723 number lines were presented to add novel midand end-points, due to previous research showing that the mid-points of 0 to 100 and 0 to 1,000 lines were used as reference points. Accuracy of estimates and reaction times were analyzed for each subject along with eye-movements in order to help define strategy use in performing the task. In particular, we captured participants' eye fixations within several defined regions of interest along the number lines as a way of identifying their estimation strategies. We presented overlays of fixations and saccades to show exemplars of the several strategies iii we have observed. Statistical analysis of these strategies was discussed and a comparison of strategy use with estimation accuracy was examined.
Cis‐regulatory evolution in a wild primate: Infection‐associated genetic variation drives differential expression of MHC‐DQA1 in vitro

Few studies have combined genetic association analyses with functional characterization of infection‐associated SNPs in natural populations of nonhuman primates. Here, we investigate the relationship between host genetic variation, parasitism and natural selection in a population of red colobus (Procolobus rufomitratus tephrosceles) in Kibale National Park, Uganda. We collected parasitological, cellular and genomic data to test the following hypotheses: (i) MHC‐DQA1 regulatory genetic variation is associated with control of whipworm (Trichuris) infection in a natural population of red colobus; (ii) infection‐associated SNPs are functional in driving differential gene expression in vitro; and (iii) balancing selection has shaped patterns of variation in the MHC‐DQA1 promoter. We identified two SNPs in the MHC‐DQA1 promoter, both in transcription factor binding sites, and both of which are associated with decreased control of Trichuris infection. We characterized the function of both SNPs by testing differences in gene expression between the two alleles of each SNP in two mammalian cell lines. Alleles of one of the SNPs drove differential gene expression in both cell lines, while the other SNP drove differences in expression in one of the cell lines. Additionally, we found evidence of balancing selection acting on the MHC‐DQA1 promoter, including extensive trans‐species polymorphisms between red colobus and other primates, and an excess of intermediate‐frequency alleles relative to genome‐wide, coding and noncoding RADseq data. Our data suggest that balancing selection provides adaptive regulatory flexibility that outweighs the consequences of increased parasite infection intensity in heterozygotes.
Obtaining best parameter values for accurate classification

In this paper we examine the effect that the choice of support and confidence thresholds has on the accuracy of classifiers obtained by classification association rule mining. We show that accuracy can almost always be improved by a suitable choice of threshold values, and we describe a method for finding the best values. We present results that demonstrate this approach can obtain higher accuracy without the need for coverage analysis of the training data.
Arbitrary shape multilayer interconnects EMC modelling and optimization

In very-large-scale-integration (VLSI), arbitrary structure of interconnections leads to unpredictable parasitic capacitance that generates EMC issues, i.e., parasitic noise, signal disorder, control failure, data asynchronous, etc. This paper investigates an EMC modelling and optimization method in calculating interconnect capacitance of VLSI interconnects based on the finite element method (FEM). Two- and three-dimensional interconnect models are simulated and the results of capacitance extraction are compared with experimental measurements, which proved the consistency and accuracy of FEM. Furthermore, optimizations of coupling capacitance are applied on multilayer interconnection structures by the non-dominated sorting genetic algorithm II (NSGA-II).
GPSCP: A general-purpose support-circuit preconditioning approach to large-scale SPICE-accurate nonlinear circuit simulations

To improve the efficiency of direct solution methods in SPICE-accurate nonlinear circuit simulations, preconditioned iterative solution techniques have been widely studied in the past decades. However, it still has been an extremely challenging task to develop general-purpose preconditioning methods that can deal with various large-scale nonlinear circuit simulations. In this work, a novel circuit-oriented, generalpurpose support-circuit preconditioning technique (GPSCP) is proposed to significantly improve the matrix solving time and reduce the memory consumption during large-scale nonlinear circuit simulations. We show that by decomposing the system Jacobian matrix at a given solution point into a graph Laplacian matrix as well as a matrix including all voltage and controlled sources, and subsequently sparsifying the graph Laplacian matrix based on support graph theory, the general-purpose support-circuit preconditioning matrix can be efficiently obtained, thereby serving as a very effective and efficient preconditioner in solving the original Jacobian matrix through Krylov-subspace iterations. Additionally, a novel critical node selection method and an energy-based spanning-graph scaling method have been proposed to further improve the quality of ultra-sparsifier support graph. To gain higher computational efficiency during transient circuit analysis, a dynamic support-circuit preconditioner updating approach has also been investigated. Our experimental results for a variety of large-scale nonlinear circuit designs show that the proposed technique can achieve up to 14.0X runtime speedups and 6.7X memory reduction in DC and transient simulations.
Effect of STA-MCA Anastomosis On the Course of Experimental Acute MCA Embolic Occlusion

The experiments in this report were designed to evaluate the effect of superficial temporalmiddle cerebral artery (STA-MCA) anastomosis on the course of middle cerebral artery (MCA) occlusion by emboli while avoiding a vessel clipping technique as well as the use of long-acting barbiturate anesthesia. Dogs were divided into 3 general groups: A) embolus placement 1 b following anastomosis; B) embolus placement 5 h prior to anastomosis; C) control group without anastomosis. Anastomosis prior to MCA occlusion has a favorable clinical effect and reduces the size of an infarction. Anastomosis 5 h after embolus placement is deleterious unless other therapeutic modalities can be shown to delay the course of infarction.
Exploiting Dining Preference for Restaurant Recommendation

The wide adoption of location-based services provide the potential to understand people's mobility pattern at an unprecedented level, which can also enable food-service industry to accurately predict consumers' dining behavior. In this paper, based on users' dining implicit feedbacks (restaurant visit via check-ins), explicit feedbacks (restaurant reviews) as well as some meta data (e.g., location, user demographics, restaurant attributes), we aim at recommending each user a list of restaurants for his next dining. Implicit and Explicit feedbacks of dining behavior exhibit different characteristics of user preference. Therefore, in our work, user's dining preference mainly contains two parts: implicit preference coming from check-in data (implicit feedbacks) and explicit preference coming from rating and review data (explicit feedbacks). For implicit preference, we first apply a probabilistic tensor factorization model (PTF) to capture preference in a latent subspace. Then, in order to incorporate contextual signals from meta data, we extend PTF by proposing an Implicit Preference Model (IPM), which can simultaneously capture users'/restaurants'/time' preference in the collaborative filtering and dining preference in a specific context (e.g., spatial distance preference, environmental preference). For explicit preference, we propose Explicit Preference Model (EPM) by combining matrix factorization with topic modeling to discover the user preference embedded both in rating score and text content. Finally, we design a unified model termed as Collective Implicit Explicit Preference Model (CIEPM) to combine implicit and explicit preference together for restaurant recommendation. To evaluate the performance of our system, we conduct extensive experiments with large-scale datasets covering hundreds of thousands of users and restaurants. The results reveal that our system is effective for restaurant recommendation.