Miracle-dz/UniFAR-FTUs huggingface dataset:
ATTITUDES AND SOCIAL COGNITION _ Prejudice With and Without Compunction

Ss reported their standards for how they should respond and how they would respond in contact situations with Black people (Study 1) and homosexual men (Study 2). Interest centered on the affective consequences associated with should-would discrepancies. Low and moderately prejudiced Ss with discrepancies reacted with feelings of global discomfort and with more specific feelings of compunction (guilt and self-criticism). High prejudiced Ss with discrepancies experienced only global discomfort. Study 3 data indicated that low prejudiced Ss internalized their nonprejudiced standards and felt obligated to respond consistently with them. High prejudiced Ss' personal standards were less well internalized and appeared to be derived from their perceptions of society's standards, which Ss indicated were mixed (i.e., contained both egalitarian and discriminatory components). Implications for prejudice reduction and contemporary models of prejudice are discussed.
The influence of different long-circulating materials on the pharmacokinetics of liposomal vincristine sulfate

Purpose This study was designed to improve the in vivo pharmacokinetics of long-circulating vincristine sulfate (VS)-loaded liposomes; three different long-circulating materials, chitosan, poly(ethylene glycol)-1,2-distearoyl sn-glycero-3-phosphatidylethanolamine (PEG-DSPE), and poly(ethylene glycol)-poly-lactide-co-glycolide (PEG-PLGA), were evaluated at the same coating molar ratio with the commercial product Marqibo® (vincristine sulfate liposome injection [VSLI]). Materials and methods VS-loaded liposomes were prepared by a pH gradient method and were then coated with chitosan, PEG-DSPE, or PEG-PLGA. Physicochemical properties, including the morphology, particle size, zeta potential, encapsulation efficiency (EE%), pH, drug loading, and in vitro release, were determined. Preservation stability and pharmacokinetic studies were performed to compare the membrane-coated liposomes with either commercially available liposomes or the VS solution. Results The sphere-like morphology of the vesicles was confirmed by transmission electron microscope. Increased particle size, especially for the chitosan formulation, was observed after the coating process. However, the EE% was ~99.0% with drug loading at 2.0 mg/mL, which did not change after the coating process. The coating of long-circulation materials, except for chitosan, resulted in negatively charged and stable vesicles at physiological pH. The near-zero zeta potential exhibited by the PEG-DSPE formulation leads to a longer circulation lifetime and improved absorption for VS, when compared with the PEG-PLGA formulation. Compared with the commercial product, PEG was responsible for a higher plasma VS concentration and a longer half-life. Conclusion PEG-DSPE coating may be related to better absorption, based on the stability and a pharmacokinetic improvement in the blood circulation time.
COMPARISON OF MODIS AND PROXY-VIIRS DERIVED EVAPOTRANSPIRATION ESTIMATES FOR IMPROVED AGRICULTURAL BEST PRACTICES ASSESSMENT

The AnnAGNPS pollution model uses evapotranspiration as one of the inputs to predict runoff, sediment, nutrients, and pesticide contributions from land to streams. This modeling tool has been modified to accept evapotranspiration estimates derived from remotely sensed imagery, produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. This research evaluated the next generation of moderate resolution sensor, the Visible Infrared Imager Radiometer Suite (VIIRS), as an alternative source of remotely sensed evapotranspiration estimates for use as input into the AnnAGNPS pollution model. Two distinct sets of daily evapotranspiration maps were produced based on remotely sensed parameters, one set from MODIS and another set from proxy-VIIRS images. NDVI and LST values from both datasets, MODIS and proxy-VIIRS, were integrated with discrete AnnAGNPS evapotranspiration values based on field stations through the use of the VI-LST Triangular Space Method and linear multivariate regression. Daily regression models were developed using the information from the existing field stations as independent variables and the NDVI and LST pixel values corresponding to the field stations, as dependent variables. The developed models were then used to create two sets of daily evapotranspiration maps, providing data where field stations are not found. Comparisons between the two evapotranspiration maps were performed. Preliminary results indicate that the next generation of moderate resolution sensors will continue to provide AnnAGNPS an alternative source of gridded evapotranspiration estimates to overcome the limitations imposed by localized field stations.
FOURIER ANALYSIS OF PARALLEL BLOCK-JACOBI SPLITTING WITH TRANSPORT SYNTHETIC ACCELERATION IN TWO-DIMENSIONAL GEOMETRY

A Fourier analysis is conducted in two-dimensional (2D) Cartesian geometry for the discreteordinates (SN) approximation of the neutron transport problem solved with Richardson iteration (Source Iteration) and Richardson iteration preconditioned with Transport Synthetic Acceleration (TSA), using the Parallel Block-Jacobi (PBJ) algorithm. The results for the un-accelerated algorithm show that convergence of PBJ can degrade, leading in particular to stagnation of GMRES(m) in problems containing optically thin sub-domains. The results for the accelerated algorithm indicate that TSA can be used to efficiently precondition an iterative method in the optically thin case when implemented in the “modified” version MTSA, in which only the scattering in the low order equations is reduced by some non-negative factor β < 1.
Convergent Iterative CT Reconstruction With Sparsity-Based Regularization Sathish Ramani

Statistical image reconstruction for X-ray CT can provide improved image quality at reduced patient doses. An important component of statistical reconstruction methods is the regularizer. There has been increased interest in sparsity-based regularization, typically using l1 norms. The non-smooth nature of these regularizers is a challenge for iterative optimization methods and often causes slow convergence. Recently there has been renewed interest in augmented Lagrangian methods for such optimization problems, with certain variable splitting approaches [1] including the alternating direction method of multipliers (ADMM) [2]. Such algorithms have been applied successfully to image restoration problems. This paper describes an ADMM algorithm for iterative CT reconstruction using a regularized, weighted least-squares (WLS) cost function. Not only does ADMM accommodate non-smooth regularizers, but also by choosing an appropriate variable splitting it uses an inner iteration that is suitable for preconditioning using a circulant matrix (FFT) based on a kind of cone filter. Simulation results show that the proposed ADMM converges and that the cone filter preconditioner accelerates convergence.
On the Existence of Solutions to the Generalized Marguerre-von Kármán Equations

Using techniques from asymptotic analysis, the second author has recently identified equations that generalize the classical Marguerre-von Kármán equations for a nonlinearly elastic shallow shell by allowing more realistic boundary conditions, which may change their type along the lateral face of the shell. We first reduce these more general equations to a single “cubic” operator equation, whose sole unknown is the vertical displacement of the shell. This equation generalizes a cubic operator equation introduced by M. S. Berger and P. Fife for analyzing the von Kármán equations for a nonlinearly elastic plate. We then establish the existence of a solution to this operator equation by means of a compactness method due to J. L. Lions.
A New Local Adaptive Wavelet Image De-noising Method

In order to improve the signal to noise ratio of image, a local adaptive Wiener filter in wavelet domain is applied to a 2-D image. Several 1-D windows could be constructed on the direction character of sub-image in the filter window after wavelet transform. Then the adaptive filters could be obtained from the 1-D windows. With the effective weighted combination of filters in different 1-Dwindows, the sub-image local adaptive filters are generated. And the simulation of the adaptive filter shows it could remove the white noise of image and preserve the edge of images effectively.
Direct and Indirect Effects of Older Adults' Use of Online Communities on Socialization and Social Isolation

This study explored the potential associations among older adults’ online community uses, socialization, and social isolation. Results from the hierarchical regression analysis indicated that the quality and size of personal networks composed of online community members positively influences older adults’ socialization and reduces social isolation. However, the frequency of meeting with online community members in offline settings was not significantly associated with socialization. Moreover, the amount of time using online communities indirectly and significantly affected social isolation, mediated by socialization. Results from this study address the positive roles of online community uses in overcoming psychological difficulties among elderly people. ☞ keyword : Older Adults, Online Community Use, Socialization, Social Isolation
BPM/BPM+: Software-based dynamic memory partitioning mechanisms for mitigating DRAM bank-/channel-level interferences in multicore systems

The main memory system is a shared resource in modern multicore machines that can result in serious interference leading to reduced throughput and unfairness. Many new memory scheduling mechanisms have been proposed to address the interference problem. However, these mechanisms usually employ relative complex scheduling logic and need modifications to Memory Controllers (MCs), which incur expensive hardware design and manufacturing overheads. This article presents a practical software approach to effectively eliminate the interference without any hardware modifications. The key idea is to modify the OS memory management system and adopt a page-coloring-based Bank-level Partitioning Mechanism (BPM) that allocates dedicated DRAM banks to each core (or thread). By using BPM, memory requests from distinct programs are segregated across multiple memory banks to promote locality/fairness and reduce interference. We further extend BPM to BPM+ by incorporating channel-level partitioning, on which we demonstrate additional gain over BPM in many cases. To achieve benefits in the presence of diverse application memory needs and avoid performance degradation due to resource underutilization, we propose a dynamic mechanism upon BPM/BPM+ that assigns appropriate bank/channel resources based on application memory/bandwidth demands monitored through PMU (performance-monitoring unit) and a low-overhead OS page table scanning process. We implement BPM/BPM+ in Linux 2.6. 32.15 kernel and evaluate the technique on four-core and eight-core real machines by running a large amount of randomly generated multiprogrammed and multithreaded workloads. Experimental results show that BPM/BPM+ can improve the overall system throughput by 4.7%/5.9%, on average, (up to 8.6%/9.5%) and reduce the unfairness by an average of 4.2%/6.1% (up to 15.8%/13.9%).
Evaluation of MR-Derived Cerebral Oxygen Metabolic Index in Experimental Hyperoxic Hypercapnia, Hypoxia, and Ischemia

Background and Purpose— A noninvasive MRI method to measure cerebral oxygen metabolism has the potential to assess tissue viability during cerebral ischemia. The purposes of this study were to validate MR oxygenation measurements across a wide range of global cerebral oxygenation and to examine the spatiotemporal evolution of oxygen metabolism during focal middle cerebral artery occlusion in rats. Methods— A group of rats (n=28) under normal, hyperoxic hypercapnia and hypoxia were studied to compare MR-measured cerebral oxygen saturation (O2SatMRv) with blood gas oximetry measurements in the jugular vein (O2SatJV) and superior sagittal sinus (O2SatSSS). In a separate group of rats (n=31), MR-measured cerebral oxygen metabolic index (MR_COMI) was acquired at multiple time points during middle cerebral artery occlusion. Histogram analysis was performed on the normalized MR_COMI (rMR_COMI) to examine evolution of oxygen metabolism during acute ischemia. Results— Highly linear relationships were obtained between O2SatMRv and O2SatJV/O2SatSSS in rats under global cerebral oxygenation alterations. In the focal ischemia study, rMR_COMI values were significantly lower within the areas of eventual infarction than other regions. Moreover, the rMR_COMI values within the ischemic territory decreased with time, concomitant with an increase in the number of voxels with severely impaired oxygen metabolism. Conclusion— Accurate estimates of O2SatMRv can be obtained across a broad and physiologically relevant range of cerebral oxygenation. Furthermore, this method demonstrates a dynamic alteration of cerebral oxygen metabolism during acute ischemia in rats.
Knowledge management model for UUM’s Golf Club

Knowledge is an important asset that can determine the success of any organizations.It is a combination of information, social interaction, and contextual situation.This paper presents a study that attempts to identify the knowledge assets that exist within the UUM’s Golf Club (UUMGC), to classify the knowledge into tacit and explicit and finally to propose a Knowledge Management Model for UUM GC by adapting Nonaka’s SECI Model.The methodology adapted for this research is the Expert System Development Life Cycle (ESDLC). The proposed model can be used not only by UUM GC but also other similar organizations.
Seasonal snow accumulation in the mid-latitude forested catchment

The study deals with the snow cover characteristics (snow depth — SD and snow water equivalent — SWE) concerning the mid-latitude forested catchment. Namely, the influence of the forest canopy (Picea abies (L.) Karst. and Fagus sylvatica L. ) and altitude (ranging from 835 m a.s.l. to 1118 m a.s.l.) was investigated. Forest cover was proved to have a significant influence on the snow cover accumulation, reducing SWE by 50 % on average, compared to open sites. The elevation gradient concerning SWE ranged from 30 to 40 mm and from 5 to 20 mm per 100 m in open and forested sites, respectively. Its magnitude was found to be temporarily variable and positively related to the total seasonal snowfall amount. The SWE/SD variability among measurement sites (with different altitude) was higher in open sites compared to forested ones. The catchment SWE/SD variability increases significantly in the snowmelt period (March–April) both in open and forested locations. The differences among snow interception losses, concerning various elevations and the forest canopy, were not statistically significant.
The Construction of HISCAM: A Stratification Scale Based on Social Interactions for Historical Comparative Research

Abstract A new occupational stratification scale, “HISCAM” (historical CAMSIS), has been developed to facilitate the analysis of data coded to the Historical International Standard Classification of Occupations. This article describes the derivation and properties of the HISCAM measure. The scale was derived using patterns of inter-generational occupational connections, replicating a method of “social interaction distance” analysis which is widely used in contemporary sociology. Analysis was performed on data for the period of 1800–1938, principally derived from marriage registers covering Belgium, Britain, Canada, France, Germany, the Netherlands, and Sweden, and encompassing over two million inter-generational relationships. Researchers report how several different HISCAM scales were evaluated and show how this approach can explain social stratification and inequality in the past.
It's really not a rendering bug, you see

Most rendering algorithms deliberately employ approximations and other shortcuts for efficiency. These economies-not coding errors-produce characteristic image artifacts. This article classifies the best-known varieties. We wrote this article in the hope of saving programmers a lot of time debugging something that is really not a bug, but instead a limitation of the algorithm. Our taxonomy is not exhaustive, but it does include many common rendering problems that we have encountered over the years. Most of these limitations can be circumvented with the proposed solutions. In reality, there are more workarounds than true solutions. This imbalance warrants more research into proper solutions to these and similar problems.
Educ. Technol. Res., 39(1)

1.1. Expectancy and Value in Learning Motivation plays an important role in facilitating engagement in learning (e.g., PINTRICH 1999, ZIMMERMAN and SCHUNK 2011). One theoretical model that describes motivation is the expectancy-value model (ECCLES and WIGFIELD 2002, WIGFIELD and ECCLES 2000). According to this model, learners’ motivation comprises “expectancy” and “value,” which influence learning persistence, performance, and task choice. The motivational component “expectancy” refers to one’s subjective expectation of a successful outcome, while the motivational component “value” describes the value that one places on a task or task outcome (KAGE 2013). An example of empirical research on the relationship among expectancy, value, and learning behavior is the study by PINTRICH and DE GROOT (1990), who conceptualized expectancy as “self-efficacy” and value as “intrinsic value. ” Self-efficacy, defined by BANDURA (1977) as “the conviction that one can successfully execute the behavior required to produce the outcomes,” influences a wide range of behavior (LINNENBRINK and PINTRICH 2003). According to PINTRICH and DE GROOT (1990), the intrinsic value component includes students’ goals and beliefs about the importance and interest of the task. These authors demonstrated that self-efficacy and intrinsic value were positively related to learning strategy and performance. In a study of junior high school students in Japan, ITO (1996) found that self-efficacy and intrinsic value were related to various learning strategies. LEE et al. (2014) noted that self-efficacy, intrinsic value, and utility value (“usefulness of a task in accomplishing desired goals”) were negatively related to maladaptive strategies (e.g., self-handicapping). Thus, research has demonstrated that expectancy and belief in task value are components of motivation, that they influence learners’ engagement, and that they therefore play an important role in learning. While research has produced a body of findings, studies have generally been cross-sectional, analyzing data pertaining only to a single point in time. Needless to say, actual learning takes place over a long time span. Many university students in Japan study under a two-semester system; in a single semester, students attend courses for approximately four months. For this reason, it is necessary to examine learning using a longitudinal approach. One of the few studies to have taken such a perspective is that of POKAY and The Relationship between Self-Efficacy, Intrinsic Value, and Emotional Engagement: Using a Cross-Lagged Panel Model *
Elementary Diagrams in Institutions

We generalize the method of diagrams from conventional model theory to a simple institution-independent (i.e. independent of the details of the actual logic formalized as an institution) framework based on a novel categorical concept of elementary diagram of a model. We illustrate the power of our institution-independent method of elementary diagrams by developing several applications to institution liberality, institution-independent quasi-varieties, and limits and colimits of presentation models. The results obtained are illustrated systematically with examples from several different specification logics. In the introduction we also discuss the relevance of our institution-independent approach to the model theory of algebraic specification and computing science, but also to conventional and abstract model theory.
Mobile manipulation using NASA's Robonaut

The Johnson Space Center has developed a new mobile manipulation system with the combination of a Robonaut upper body mounted onto a Segway mobile base. The objective is to study a fluid and coordinated control of dexterous limbs on a mobile robot. The system has been demonstrated interacting with people, tools, and urban interfaces built for humans. Human interactions have included manually exchanging objects with humans, following people, and tracking people with hand held objects such as flashlights. Like other configurations of the Robonaut family, the upper body provides dexterity for using tools such as wire cutters, shovels, space flight gear, and handling flexible tethers and fabrics. The Segway base is a custom version called the Robotic Mobility Platform (RMP) built for DARPA, and provided to NASA for this collaborative effort. The RMP's active balance gives Robonaut a relatively small footprint for its height, allowing it to pass through doors and elevators built for humans, and use wheelchair accessible ramps and lifts. Lessons learned from this development are presented to improve the design of future mobile manipulation systems, and the Segway base provides mobility to Robonaut for Earth based testing.
Vision-based localization, mapping and control for autonomous MAV: EuRoC challenge results

This paper presents vision-based localization, mapping and control solutions for autonomous navigation of a micro-air vehicle (MAV) in GPS-denied environments. The proposed algorithms have been evaluated in the simulation contest of the FP7 project EuRoC (European Robotics Challenges) dedicated to " Plant Servicing and Inspection " , where our team composed of members from ONERA and ISIR-UPMC ranked 2nd over 21 European research laboratories and has been selected for the next stages of the project.
Low-order system identification and optimal control of intersample behavior in ILC

Iterative Learning Control (ILC) enables high tracking performance of batch repetitive processes. Common ILC approaches resort to discrete time system representations and hence are not able to guarantee good intersample behavior in case the underlying system evolves in continuous time. The aim of this paper is to explicitly deal with the intersample behavior in ILC. A multirate, parametric, and low-order approach to both identification for ILC and subsequent optimal ILC is presented that results in a low computational burden. The approach appropriately deals with the time-varying nature of multirate systems. The proposed multirate identification and ILC algorithms are shown to outperform common ILC approaches in a simulation example.