Miracle-dz/UniFAR-FTUs huggingface dataset:
Framing Public Discussion of Gay Civil Unions

Although the framing of public opinion has often been conceptualized as a collective and so cial process, experimental studies of framing have typically examined only individual, psychological responses to alternative message frames. In this research we employ for the first time group conversations as the unit of analysis (following Gamson 1992) in an experimental study of framing effects. Two hundred and thirty-five American citizens in 50 groups (17 homo- geneously conservative groups, 15 homogeneously liberal groups, and 18 heterogeneous groups) discussed whether or not gay and lesbian partnerships should be legally recognized. Groups were randomly assigned to one of two framing conditions (a "homosexual marriage/ special rights" frame or a "civil unio n/equal rights" frame). Results indi- cated framing effects that were, in all cases, contingent on the ideologi- cal leanings of the group. The "marriage" frame tended to polarize group discussions along ideological lines. Both liberal and conservative groups appeared to find their opponents' frame more provocative, responding to them with a larger number of statements and expressing greater ambivalence than when reacting to more hospitable frames. Political conversation is a central feature of democratic life (Barber 1984; Dewey 1927; Tarde (1899) 1989). In talking through their ideas, people are able to sort out various considerations and to learn, in the process, what they think about shared concerns (Gutmann and Thompson 1996; Kuhn 1991).
Urine from Patients with Bladder or Kidney Cancer Increased Levels of Fibroblast Growth Factor-like Activity in Updated Version

Growth factor activity was partially purified from human renal tumors and a human bladder cancer cell line by heparin-Sepharose chromatography. This activity stimulated bovine capillary endothelial cell prolifer ation and DNA synthesis in BALB/c 3T3 cells. Partially purified growth factor preparations from these tumors contained a protein with an ap proximate molecular weight of 17,000 which was recognized by a polyclonal antiserum raised against a peptide fragment of basic fibroblast growth factor (FGF). This growth factor activity appears to be related to basic fibroblast growth factor. Measurement of FGF-like activity in 50 urine samples from 32 adult males showed that 55% (6 of 11 ) of the urine samples from patients with bladder cancer and 100% (7 of 7) of the urine samples from patients with kidney cancer contained activity equivalent to more than 20 ng of basic FGF/h of urine production. In contrast, only 6% (2 of 32) of the urine samples from controls, patients with a benign disease, or patients with a history of bladder or kidney cancer contained this level of growth factor activity. These results suggest that patients with bladder or kidney cancer release an FGF-like factor into urine which may be used as a marker for
Mesoscale Performance Simulations of Multicore Processor Systems with Asynchronous Memory Access

Increasing on-chip transistor densities allow for a myriad of design choices for modern multicore processors. However, conducting a meaningful design space exploration of large systems with detailed cycle-accurate simulations using large, complex workloads can be very time-consuming and can adversely impact product schedules. This is due to three main reasons: 1) the high (human) cost of developing cycle-accurate simulators, 2) long simulation times for any sufficiently detailed simulator of a large, complex system, and 3) long running times for modern workloads. While statistical sampling techniques address workload run lengths, there exists no proven technique to replace the use of detailed cycle-accurate simulators for design space exploration. In this paper, we introduce mesoscale simulation, which is a methodology for design space exploration that mitigates the cost of cycle-accurate simulators. Mesoscale simulation is a hybrid approach that combines elements of high-level modeling and lowlevel cycle-accurate simulators to enable the construction of fast, high-fidelity performance models. Such models can be used to quickly explore vast areas of the design space and prune it down to manageable levels for cycle-accurate simulator based studies. We describe a proof-of-concept mesoscale implementation of the memory subsystem of the Cell/B.E. processor and discuss results from running various workloads. $ This work was done while the author was employed by IBM STG Boeblingen. # This work was done while the author was employed by IBM Research Austin.
Node Scaling Analysis for Power-Aware Real-Time Tasks Scheduling

Multi-core processors achieve a trade-off between the performance and the power consumption by using Dynamic Voltage Scaling (DVS) techniques. In this paper, we study the power efficient scheduling problem of real-time tasks in an identical multi-core system, and present Node Scaling model to achieve power-aware scheduling. We prove that there is a bound speed which results in the minimal power consumption for a given task set, and the maximal value of task utilization, <inline-formula><tex-math notation="LaTeX">$u_{max}$</tex-math><alternatives> <inline-graphic xlink:type="simple" xlink:href="yu-ieq1-2485229.gif"/></alternatives></inline-formula>, in a task set is a key element to decide its minimal power consumption. Based on the value <inline-formula><tex-math notation="LaTeX">$u_{max}$ </tex-math><alternatives><inline-graphic xlink:type="simple" xlink:href="yu-ieq2-2485229.gif"/></alternatives></inline-formula>, we classify task sets into two categories: the bounded task sets and the non-bounded task sets, and we prove the lower bound of power consumption for each type of task set. Simulations based on Intel Xeon X5550 and PXA270 processors show Node Scaling model can achieve power efficient scheduling by applying to existing algorithms such as EDF-FF and SPA2. The ratio of power reduction depends on the multi-core processor's property which is defined as the ratio of the bound speed to the maximal speed of the cores. When the ratio of speeds decreases, the ratio of power reduction increases for all the power efficient algorithms.
Diffuse attenuation coefficient of downwelling irradiance: An evaluation of remote sensing methods

coastal waters, with Kd(490) ranging from � 0.04 to 4.0 m � 1 . The derived values are compared with the data calculated from in situ measurements of the vertical profiles of downwelling irradiance. The comparisons show that the two standard methods produced satisfactory estimates of Kd(l) in oceanic waters where attenuation is relatively low but resulted in significant errors in coastal waters. The newly developed semianalytical method appears to have no such limitation as it performed well for both oceanic and coastal waters. For all data in this study the average of absolute percentage difference between the in situ measured and the semianalytically derived Kd is � 14% for l = 490 nm and � 11% for l = 443 nm.
Robot dynamics and control

From the Publisher: This self-contained introduction to practical robot kinematics and dynamics includes a comprehensive treatment of robot control. Provides background material on terminology and linear transformations, followed by coverage of kinematics and inverse kinematics, dynamics, manipulator control, robust control, force control, use of feedback in nonlinear systems, and adaptive control. Each topic is supported by examples of specific applications. Derivations and proofs are included in many cases. Includes many worked examples, examples illustrating all aspects of the theory, and problems.
Segmentation of ISAR Images of Targets Moving in Formation

This paper proposes a new method to separate inverse synthetic aperture radar (ISAR) images using the range-Doppler algorithm when multiple targets fly closely spaced in a formation. This method is composed of three steps. The first step is an initial range-Doppler imaging of the whole set of targets to obtain a ¿bulk¿ image. In this step, range profiles are aligned using a new cost function, which is the sum of the amplitudes of the pixels lying along a polynomial that models the trajectory of the bulk image. To reduce the probability of incorrectly aligning high-amplitude pixels from different targets, pixel amplitudes are converted to binary form: A number ¿ of pixels with the greatest amplitudes are identified in the bulk range profile, and their amplitudes are converted to one; the amplitudes of the remaining pixels are converted to zero. This process gives each of the ¿ pixels the same weight on the cost function. Then, phase adjustment is used to coarsely separate targets in a 2-D image. The second step is the separation of the bulk image into component images using a window of the target size. The third step is a second range-Doppler imaging, in which each ISAR image is enhanced using range alignment and phase adjustment. Simulations using three targets composed of point scattering centers prove that the proposed method can effectively segment three targets flying in a formation.
Double General Point Interactions: Symmetry and Tunneling Times

We consider the one dimensional problem of a non-relativistic quantum particle scattering off a double barrier built from two generalized point interactions (each one characterized as a member of the four parameter family of point interactions). The properties of the double point barrier under parity transformations are investigated, using the distributional approach, and the constraints on the parameters necessary for the interaction to have a well-defined parity are obtained. We show that the limit of zero interbarrier distance of a renormalized odd arrangement with two $\delta'$ is either trivial or does not exist as a generalized point interaction. Finally, we specialize to double barriers with defined parity, calculate the phase and Salecker-Wigner-Peres clock times and argue that the emergence of the generalized Hartman effect is an artifact of the extreme opaque limit.
Improving Active Measurement Estimates Using One-Way Delays

Understanding network characteristics is essential to build accurate models necessary to improve the quality of multimedia real time applications. Some performance network parameters such as the round trip time (RTT) can be easily obtained in most cases. However, variables such as one-way delay (OWD) distributions and link capacities may be difficult to estimate without the use of special hardware, such as GPS equipment. Recently, several active measuring techniques have been proposed to cope with the problems that arise when one tries to measure such quantities based solely on probes sent between two end points and without the use of special hardware. In this work, we further extend previous techniques for measuring the one-way delay and bottleneck capacity, and present a few results to illustrate the proposed techniques.
Representing fundamental frequency contours generated by HMM-based speech synthesis using generation process model

Frame-by-frame representation is not appropriate for prosodic features, which are tightly related to speech units spreading a wide time span, such as words, phrases and so on. This causes an inherit problem in fundamental frequency (F0) contour generation by HMM-based speech synthesis. A method is developed to modify F0 contours in the framework of a generation process model by referring to linguistic information of input text (word boundary and accent type). It takes F0 variances obtained through HMM-based speech synthesis into account during the process. Through a listening experiment on synthetic speech, the method is proved to generate better quality as compared to the HMM-based speech synthesis on average. Since the generation process model can clearly relate its commands and linguistic (and para-/non- linguistic) information, the method has an additional advantage; changing speech styles, and /or adding further information (such as emphasis) can be easily done through manipulating the commands.
Nonsmooth optimization algorithm for mixed H2/H∞ synthesis

The mixed H2/Hinfin synthesis problem is addressed via nonsmooth mathematical programming. The proposed algorithm is of first order and can handle any controller structure of practical interest. Since computations are carried out in the frequency domain, the method does not suffer dimensional restrictions like LMI or BMI methods. Global convergence is established and several numerical tests are presented.
Resource recommendation based on topic model for educational system

In this paper, we propose a method for resource recommendation based on topic model in an e-learning system. The Web provides an extremely large and dynamic source of information. So it is now increasingly popular to provide personalized service in document recommendation. Personalized service can reduce information overload and, hence, increase user satisfaction. Topic model is a generative model for text mining, which has significant effects in both efficiency and accuracy. Latent Dirichlet Allocation (LDA), an approach to building topic models based on a formal generative model of documents, is and feasible and effective algorithm in text modeling. We propose an LDA-based interest model within the language modeling framework, and evaluate it on an e-learning system. In an e-learning system, topic model can provide a good vector model for the course document. Besides with the help of the topic model, we can build an exact model for users' interests, because in an e-learning system, we can get the users' access action and users' learning condition from the server. Thus the system can adopts interest mining technology and topic model to automatically identify the learner's interests and recommend interest-related resources to specific person. In this paper, we only focus on interests modeling and resource recommendation. The interest modeling system using proposed approach based on topic model is more effective. Meanwhile, the recommendation system based on user interests also gets better result.
Pioglitazone reverses insulin resistance and impaired CCK-stimulated pancreatic secretion in eNOS(-/-) mice: therapy for exocrine pancreatic disorders?

In mice, eNOS (endothelial nitric oxide synthase) maintains in vivo pancreatic secretory responses to carbachol or cholecystokinin octapeptide (CCK-8), maintains insulin sensitivity, and modulates pancreatic microvascular blood flow (PMBF). eNOS(-/-) mice are insulin resistant, and their exocrine pancreatic secretion is impaired. We hypothesized that the reduced exocrine pancreatic secretion in eNOS(-/-) mice is due to insulin resistance or impaired PMBF. To test this hypothesis, we gave eNOS(-/-) and wild-type (WT) mice pioglitazone (20 or 50 mg.kg(-1). day(-1)), an insulin-sensitizing peroxisome proliferator-activated receptor-gamma (PPAR-gamma) activator, and measured pancreatic protein secretion evoked by CCK-8 (160 pmol.kg(-1). h(-1), a maximal stimulus). We also measured insulin resistance, serum glucose, C-peptide, insulin, pancreatic RNA digestive enzyme expression, and PMBF (microsphere technique). In WT mice, pioglitazone did not increase CCK-8-stimulated protein output over baseline. In eNOS(-/-) mice, however, pioglitazone substantially increased the low CCK-8-stimulated protein output that is characteristic of these mutant mice (P < 0.005). Pioglitazone abolished the CCK-8-evoked hyperinsulinemia (P < 0.005) and increased insulin sensitivity of eNOS(-/-) mice (P < 0.05), the latter based on hyperinsulinemic-euglycemic clamp studies. Pioglitazone had no effect on PMBF or pancreas mRNA expression of insulin or digestive enzymes. We conclude that in hyperinsulinemic eNOS(-/-) mice, a nonobese model of insulin resistance relevant to diabetes mellitus and possibly chronic pancreatitis, reduced pancreatic secretion is caused, at least in part, by insulin resistance. Insulin-sensitizing PPAR-gamma agonists such as pioglitazone may thus simultaneously correct endocrine and exocrine pancreatic disorders.
Self-reported suicidality behavior and attitudes toward suicide among medical and paramedical students

Aims and Objectives: The aim of this study was to evaluate knowledge and attitudes toward suicide and suicidality behavior among medical and paramedical students. Materials and Methods: A cross-sectional study was conducted in a medical college of western India where undergraduate medical (238), physiotherapy (25), and nursing (137) students were enrolled. After taking informed consent, detailed assessment of knowledge, attitude towards suicide using Suicide Opinion Questionnaire and suicidality behavior using mini-international neuropsychiatric interview were done. Data were analyzed using appropriate statistical tests. Results: Ninety-three percent students agreed “people who are at risk can't be easily identified. ” Eighty percent students believed “potentially anyone can be a suicide victim. ” Acceptability of suicide was highest in nursing students; B.P.T students had highest knowledge regarding suicide. None had active suicidal ideation or planning. Only at a thought level, one-third of total population reported feeling of hopelessness sometime in their life. Sixteen percent, nearly double females (n = 299) thought sometimes in their life that “it would be better off dead” compared to 8% males (n = 101). Among three groups, nursing students showed highest suicidality behavior. Conclusions: Attitudes toward suicide and suicidality behavior differ among the groups with significant gender differences. Although acceptability is the highest among nursing students, the group is at higher risk with higher suicidal ideation. Students believe, “people who are at risk can't be easily identified;” hence, further exploration, awareness, and interventions are suggested.
An ordered-subsets proximal preconditioned gradient algorithm for total variation regularized PET image reconstruction

Statistical variability of the PET data pre-corrected for random coincidences or acquired in sufficiently high count rates can be approximated by a Gaussian distribution, which results in a penalized weighted least-squares (PWLS) cost function. In this study, a proximal preconditioned gradient algorithm accelerated with ordered subsets (PPG-OS) is proposed for the optimization of the PWLS function, while addressing its two challenges encountered by previous algorithms such as separable paraboloidal surrogates accelerated with ordered-subsets (SPSOS) and preconditioned conjugate gradient. First, the penalty and the weighting matrix of this function make its Hessian matrix ill-conditioned; thereby surrogate functions end up with high-curvatures and preconditioners would poorly approximate the Hessian matrix. The second challenge arises when using nonsmooth penalty functions such as total variation (TV), which makes the PWLS function not amenable to optimization using gradient-based algorithms. To deal with these challenges, we used a proximal point method to surrogate the PWLS function with a proxy, which is then split into a preconditioned gradient descent and a proximal mapping associated with the TV penalty. A dual formulation was used to obtain the proximal mapping the TV penalty and also its smoothed version, i.e. Huber penalty. The proposed algorithm was studied for three different diagonal preconditioners and compared with the SPS-OS algorithm. Using simulation studies, it was found that the proposed algorithm achieves a considerably improved convergence rate over the state-of-the-art SPS-OS algorithm. Bias-variance performance of the algorithm was th evaluated for the preconditioners. Finally, the proposed PPG-OS algorithm was assessment using clinical PET data.
Joint Segmentation and Tagging with Coupled Sequences Labeling

A Segmentation and tagging task is the fundamental problem in natural language processing (NLP). Traditional methods solve this problem in either pipeline or joint cross-label ways, which suffer from error propagation and large number of labels respectively. In this paper, we present a novel joint model for segmentation and tagging, which integrates two dependent Markov chains. One chain is used for segmentation, and the other is for tagging. The model parameters can be estimated simultaneously. Besides, we can optimize the whole model by improving the single chain. The experiments show that our model could achieve higher performance over traditional models on both English shallow parsing and Chinese word segmentation and POS tagging tasks. T A C
Image Mosaicing Using Binary Edge Detection

Image mosaicing (panoramic imaging) is a key concept in image processing field. Essentially, it works by combining two or more images by stitching them together so that they look as one image. The main issue in image mosaicing is the alignment between the corresponding points so that overlapping regions between combined images are not repeated. The aim of images mosaicing research is concentrated on solving problems arising through different image mosaicing techniques. In this paper, a new technique that uses the edge profile of images to determine the corresponding points, then the overlapping region and the connecting curve which will stitch the two images to create the resulting mosaic image is determined. The approach is simple and easy to implement but still delivers promising results.
Origin and tectonic evolution of the metamorphic sole beneath the Brooks Range ophiolite, Alaska

Structural field relations, petrologic and geochemical studies, and radiometric age aualysis of metamorphic rocks at the base of the Brooks Range ophiolite provide a record of the time, tectonic setting, and initial conditions of ophiolite emplacement during the Middle Jurassic western Brookian orogeny. The metamorphic sole of the Misheguk, Siniktanneyak, and Avan Hills ophiolite bodies is transitional with and geochemically similar to basalt, chert, limestone, and psammitic material mostly of the Copter Peak allochthon. Dynamothermal metamorphism of these rocks produced garnet-bearing amphibolite and quartz-mica schists that decrease in metamorphic grade and ductile strain inteusity downward. These high-grade rocks are separated by thin, fault-bounded intervals from underlying greenschist facies and unmetamorphosed basalt and sedimentary rocks. The maximum total thickness of both parts of the metamorphic sole is <500 m. Minimum temperature estimates, from garnet-biotite and garnet-amphibole geothermometric studies of rocks currently 5-50m below the ophiolite, range from 500 to 560°C at around 5 Kb. These conditions are similar to closing temperatures estimated for Ar retention in hornblende near the base of the ophiolite, which yields 4oAr/39Ar ages of 164-169 Ma. This age is concordant with, but slightly youuger than the mean age of ophiolite crystallization. The limited time between crystallization and tectonic emplacement of the Brooks Range ophiolite, and compositional similarities between the metamorphic sole and continental margin material imply spacial and temporal proximity of the ophiolite with the Brookian orogen prior to emplacement. Localization of strain at the base of the ophiolite during emplacement produced a ductile shear zone in the metamorphic sole that is characterized by mylonitic textures overprinted by postmetamorphic deformation. Microstructures document synkinematic crystal growth at high flow stress and strain rates. Kinematic indicators show mostly top-to-northwest sense of shear at the base of the ophiolite. Postmetamorphic deformation associated with the Brookian orogen shuffled various parts of the metamorphic sole and thrust it over shelf facies sedimentary material.