Miracle-dz/UniFAR-FTUs huggingface dataset:
Crossing the Finish Line: Completing College at America’s Public Universities

Acknowledgments vii Preface xiii Chapter 1. Educational Attainment: Overall Trends, Disparities, and the Public Universities We Study 1 Chapter 2. Bachelor's Degree Attainment on a National Level 20 Chapter 3. Finishing College at Public Universities 32 Chapter 4. Fields of Study, Time-to-Degree, and College Grades 57 Chapter 5. High Schools and "Undermatching" 87 Chapter 6. Test Scores and High School Grades as Predictors 112 Chapter 7. Transfer Students and the Path from Two-Year to Four-Year Colleges 134 Chapter 8. Financial Aid and Pricing on a National Level 149 Chapter 9. Financial Aid at Public Universities 166 Chapter 10. Institutional Selectivity and Institutional Effects 192 Chapter 11. Target Populations 207 Chapter 12. Looking Ahead 223 Appendix A. The Modern Evolution of America's Flagship Universities by Eugene M. Tobin 239 Notes 265 List of Figures 337 List of Tables 347 List of Appendix Tables 349 References 357 Index 377
The lycaenid butterfly Polyommatus icarus uses a duplicated blue opsin to see green

SUMMARY The functional significance of gene duplication is rarely addressed at the level of animal behavior. Butterflies are excellent models in this regard because they can be trained and the use of their opsin-based visual pigments in color vision can be assessed. In the present study, we demonstrate that the lycaenid Polyommatus icarus uses its duplicate blue (B2) opsin, BRh2, in conjunction with its long-wavelength (LW) opsin, LWRh, to see color in the green part of the light spectrum extending up to 560 nm. This is in contrast to butterflies in the genus Papilio, which use duplicate LW opsins to discriminate colors in the long-wavelength range. We also found that P. icarus has a heterogeneously expressed red filtering pigment and red-reflecting ommatidia in the ventral eye region. In behavioural tests, the butterflies could not discriminate colors in the red range (570–640 nm). This finding is significant because we have previously found that the nymphalid butterfly Heliconius erato has filter-pigment mediated color vision in the long wavelength range. Our results suggest that lateral filtering pigments may not always influence color vision in insects.
Comparing Auditory and Haptic Feedback for a Virtual Drilling Task

While visual feedback is dominant in Virtual Environments, the use of other modalities like haptics and acoustics can enhance believability, immersion, and interaction performance. Haptic feedback is especially helpful for many interaction tasks like working with medical or precision tools. However, unlike visual and auditory feedback, haptic reproduction is often difﬁcult to achieve due to hardware limitations. This article describes a user study to examine how auditory feedback can be used to substitute haptic feedback when interacting with a vibrating tool. Participants remove some target material with a round-headed drill while avoiding damage to the underlying surface. In the experiment, varying combinations of surface force feedback, vibration feedback, and auditory feedback are used. We describe the design of the user study and present the results, which show that auditory feedback can compensate the lack of haptic feedback. Categories and Subject Descriptors (according to ACM CCS) : Information Interfaces and Presentation [H.5. 1]: Multimedia Information Systems —Artiﬁcial, augmented, and virtual realities; Information Interfaces and Presentation [H.5. 1]: Multimedia Information Systems —Evaluation/methodology; Multimedia Information Systems [H.5. 2]: User Interfaces—Auditory (non-speech) feedback Multimedia Information Systems [H.5. 2]: User Interfaces— Haptic I/O
Peer Effects, Financial Aid, and Selection of Students into Colleges and Universities: An Empirical Analysis

The goal of this paper is to develop predictions regarding market consequences of peer effects in higher education and to offer empirical evidence about the extent to which those predictions are borne out in the data. We develop a model in which colleges seek to maximize the quality of the educational experience provided to their students. From this model we deduce predictions about the hierarchy of schools that emerges in equilibrium, the allocation of students by income and ability among schools, and about the pricing policies that schools adopt. In the empirical analysis, we use both university-level data provided primarily by Petersons and student-level data from the National Postsecondary Student Aid Study obtained from the NCES. The findings of this paper suggest that there is a hierarchy of school qualities which is characterized by substantial stratification by income and ability. The evidence on pricing by ability is supportive of positive peer effects in educational achievement from high ability at the college level. However, the evidence on pricing also suggests that more highly ranked schools exercise some degree of market power. This is reflected in the substantial variation of price with income coupled with discounts to more able students that are modest at best.
Experimental and Theoretical Evaluation of the Ethynyl Moiety as a Halogen Bioisostere

Bioisosteric replacements are widely used in medicinal chemistry to improve physicochemical and ADME properties of molecules while retaining or improving affinity. Here, using the p53 cancer mutant Y220C as a test case, we investigate both computationally and experimentally whether an ethynyl moiety is a suitable bioisostere to replace iodine in ligands that form halogen bonds with the protein backbone. This bioisosteric transformation is synthetically feasible via Sonogashira cross-coupling. In our test case of a particularly strong halogen bond, replacement of the iodine with an ethynyl group resulted in a 13-fold affinity loss. High-resolution crystal structures of the two analogues in complex with the p53-Y220C mutant enabled us to correlate the different affinities with particular features of the binding site and subtle changes in ligand binding mode. In addition, using QM calculations and analyzing the PDB, we provide general guidelines for identifying cases where such a transformation is likely to improve ligand recognition.
Estimation of Unaccounted Income Using Transport as a Universal Input: A Methodological Note

There has been a lot of interest in understanding and measuring the size of unaccounted incomes in economies. There are several methods to measure size of unaccounted income (or shadow economy) - e.g., monetary approach (or currency demand approach), latent variable approach and global indicator approach. Present paper proposes an alternative method by using transport as a universal input. The method is applied to Indian data. To capture the changing structural relationship between input-output and annual volatility of demands, we tested the methodology for two successive Input-Output tables and three consecutive financial years. Since the analysis is based on assumptions, a comparative static analysis is carried out to check the sensitivity of estimates to changes in the assumptions.
Multiport-Amplifier-Based Architecture Versus Classical Architecture for Space Telecommunication Payloads

This paper discusses the suitability of using a multiport amplifier (MPA) for a power section of space telecommunication payloads with power flexibility requirements. The performances of an MPA-based architecture are compared to those of a classical amplification architecture having one power amplifier per beam. This study is based on a 4 times 4 Ka-band MPA composed of four paralleled traveling-wave tube amplifiers (TWTAs). First, a static model of the MPA has been extracted from conventional characterizations. Second, the MPA has been characterized in a realistic environment for telecommunication operation. The good agreement between measured and simulated data serves to validate the MPA model. Once the model has been validated, exhaustive simulations are performed to compare the performances of the MPA-based and classical architectures in terms of power consumption and the TWTA's saturation power. As a result, the MPA approach proves to be an interesting solution because of its greater flexibility, lower power consumption, and lower saturation power required by the TWTAs
Paralysis: An Extensible Multi-tiered Guidance Environment for Program Parallelization and Analysis

The heterogeneous computing revolution continues unabated. Yet despite the vast number of naïve users in possession of bespoke software hoping to embrace the opportunities that this revolution has wrought, few approaches proposed in current literature can guide such users in these efforts. The most appropriate choice would appear to be a (semi-)automating compiler. However, these typically target a single device-type and demand the unguided use of directives. Consequently, they are of little use when naïve users are seeking answers to more fundamental questions, such as: which fragments of a program can/should be parallelized, which device should each fragment target, and what speedup will be attained. To this end, this paper expands on previous work and proposes Paralysis - an extensible guidance environment, tiered for varying programmer competencies with support for static and dynamic analysis techniques. At the highest level, guided user experiences are paramount. At the lowest level, underlying functionality is exposed as a set of plug-ins, ensuring longevity. A partial prototype, built atop the Cetus infrastructure, is described. It is used to analyze two serial programs for CUDA execution - the DFT and the Box Blur Filter. Speedups of 15x and 22x are achieved on the basis of the analysis.
A Solution to The Unit Commitment Problem Using Hybrid Genetic and particle swarm optimization Algorithms

The solution of the unit commitment problem (UCP) is a complex optimization problem. The exact solution of the UCP can he obtained by a complete enumeration of all feasible combinations of generating units, which could be a huge number. The objective is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for the next hours. This paper presents a hybrid genetic and particle swarm optimization algorithms (HGAPSO) to solve optimal Unit Commitment Problem (UCP). The HGAPSO is applied to the widely used ten-unit test system and its multiples (10-100). Comparing our results with those of many UC solving methods demonstrate that not only the HGAPSO procedure consider is the constraints very well, but also has some advantages, such as good convergence, fast calculating speed and high precision.
OFDM ( DMT ) Bit and Power Loading for Unequal Error Protection

This paper proposes an algorithm that distributes bits according to different noise margin levels, thereby realizing unequal error protection (UEP). The new approach is based on a non-UEP allocation algorithm by Chow, Cioffi, and Bingham. The new algorithm is designed to be robust to non-stationary impulse noise and channel variations by integrating a new SNR-sorting scheme. Simulation results show that the highly protected bits are spread over a high number of carriers at low SNR, thereby ensuring that SNR variations due to non-stationary noise will not influence these carriers much. Additionally, narrow-band interference will not hit a large amount of important data.
Assessment of left atrial volumes at 1.5 Tesla and 3 Tesla using FLASH and SSFP cine imaging.

PURPOSE To investigate left atrial volumes and function and their variability in healthy volunteers using steady state free precession (SSFP) and fast low angle shot (FLASH) sequences at both 1.5 and 3 T using both the short-axis and biplane area-length methods. MATERIALS AND METHODS Ten healthy volunteers underwent CMR at both 1.5 and 3 Tesla. The biplane area-length method utilized volumes from the horizontal and vertical long axis images. RESULTS There were no significant differences between left atrial short-axis volumes or function between 1.5 and 3 T assessed using either FLASH or SSFP sequences. The biplane area-length method underestimated maximal left atrial volume using FLASH by 12 mL at 3 T (18%) and by 10 mL (14%) at 1.5 T (p = 0.003 and p = 0.05 respectively). Variability was larger for left atrial measurements using the biplane area-length method. CONCLUSION Field strength had no effect on left atrial volume and function assessment using either FLASH or SSFP. The use of the short-axis method for the acquisition of left atrial parameters is more reproducible than the biplane area-length for serial measurements.
Bandwidth-Sensitivity-Aware Arbitration for FPGAs

Field-programmable gate arrays (FPGAs) commonly implement massively parallel circuits that require significant memory bandwidth. Due to I/O and memory limitations, parallel tasks often share bandwidth via arbitration, whose efficiency is critical to ensure parallelism is not wasted. In this letter, we introduce a bandwidth-sensitivity-aware heuristic for arbitration that analyzes the effect of memory bandwidth on performance for each application task, and then accordingly allocates bandwidth to minimize execution time. When compared to round robin (RR) arbitration, application speedups as high as 6.5&times;are achieved.
Using system justification motives to understand stakeholder resistance in ES project implementation

The research reported in this paper uses system justification theory (SJT) as a lens to understand stakeholder resistance to ES implementation. A case study involving a problematic enterprise systems implementation is presented and illustrates the efficacy of SJT in this respect. The findings of the research show that SJT explains a number of features of stakeholder resistance including the tendency of stakeholders to vigorously defend established systems on which people feel that they depend and from which they draw feelings of stability and predictability, the tendency of system defenders to attack not just the features of the new system but the advocates of the new system as well, the tendency of stakeholders to switch allegiances when the new system is seen to be inevitable, and the emotional and non-rational nature of some resistance behaviours. The paper concludes with some practical implications of SJT for the management of ES implementations.
Implementing Mapping Composition ( Extended Technical Report )

Mapping composition is a fundamental operation in metadata driven applications. Given a mapping over schemas σ1, σ2, and σ3, the composition problem is to find an equivalent mapping over only σ1 and σ3. We describe a new composition algorithm that targets practical applications. It incorporates view unfolding. It eliminates as many σ2 symbols as possible, even if not all can be eliminated. It covers constraints expressed using arbitrary monotone relational operators and, to a lesser extent, non-monotone operators. And it introduces the new technique of left composition. We describe our implementation, explain how to extend it to support user-defined operators, and present experimental results which validates its effectiveness.
From Clothing to Identity: Manual and Automatic Soft Biometrics

Soft biometrics have increasingly attracted research interest and are often considered as major cues for identity, especially in the absence of valid traditional biometrics, as in surveillance. In everyday life, several incidents and forensic scenarios highlight the usefulness and capability of identity information that can be deduced from clothing. Semantic clothing attributes have recently been introduced as a new form of soft biometrics. Although clothing traits can be naturally described and compared by humans for operable and successful use, it is desirable to exploit computer vision to enrich clothing descriptions with more objective and discriminative information. This allows automatic extraction and semantic description and comparison of visually detectable clothing traits in a manner similar to recognition by eyewitness statements. This paper proposes a novel set of soft clothing attributes, described using small groups of high-level semantic labels, and automatically extracted using computer-vision techniques. In this way, we can explore the capability of human attributes vis-a-vis those which are inferred automatically by computer vision. Categorical and comparative soft clothing traits are derived and used for identification/re-identification either to supplement soft body traits or to be used alone. The automatically and manually derived soft clothing biometrics are employed in challenging invariant person retrieval. The experimental results highlight promising potential for use in various applications.
Translation of the cell adhesion molecule ALCAM in axonal growth cones – regulation and functional importance

ALCAM is a cell adhesion molecule that is present on extending axons and has been shown to be crucial for elongation and navigation of retinal ganglion cell (RGC) axons. In the present study, we show that ALCAM mRNA is present in axonal growth cones of RGCs in vivo and in vitro, and that translation of ALCAM occurs in RGC growth cones separated from their soma. This growth cone translation is regulated by the 3′-untranslated region (3′-UTR) of ALCAM and depends on the activity of the kinases ERK and TOR (target of rapamycin). We also investigated the impact of the growth cone translation of ALCAM on axonal functions. Growth cone translation of ALCAM is crucial for the enhanced elongation of axons extending in contact with ALCAM protein. The local translation of ALCAM in the growth cone is able to rapidly counterbalance experimentally induced ALCAM internalization, thereby contributing to the maintenance of constant ALCAM levels in the plasma membrane. Assays where RGC axons have the choice to grow on laminin or both ALCAM and laminin – as is the case in the developing retina – reveal that the axonal preference for ALCAM-containing lanes depends on translation of ALCAM in growth cones. Taken together, these results show for the first time that translation of a cell adhesion molecule in growth cones, as well as the impact of this local translation on the behavior of axon and growth cone.
Different Transcript Patterns in Response to Specialist and Generalist Herbivores in the Wild Arabidopsis Relative Boechera divaricarpa

Background Plants defend themselves against herbivorous insects, utilizing both constitutive and inducible defenses. Induced defenses are controlled by several phytohormone-mediated signaling pathways. Here, we analyze transcriptional changes in the North American Arabidopsis relative Boechera divaricarpa in response to larval herbivory by the crucifer specialist lepidopteran Plutella xylostella (diamondback moth) and by the generalist lepidopteran Trichoplusia ni (cabbage semilooper), and compare them to wounding and exogenous phytohormone application. Methodology/Principal Findings We use a custom macroarray constructed from B. divaricarpa herbivory-regulated cDNAs identified by suppression subtractive hybridization and from known stress-responsive A. thaliana genes for transcript profiling after insect herbivory, wounding and in response to jasmonate, salicylate and ethylene. In addition, we introduce path analysis as a novel approach to analyze transcript profiles. Path analyses reveal that transcriptional responses to the crucifer specialist P. xylostella are primarily determined by direct effects of the ethylene and salicylate pathways, whereas responses to the generalist T. ni are influenced by the ethylene and jasmonate pathways. Wound-induced transcriptional changes are influenced by all three pathways, with jasmonate having the strongest effect. Conclusions/Significance Our results show that insect herbivory is distinct from simple mechanical plant damage, and that different lepidopteran herbivores elicit different transcriptional responses.
Distributed Network Resources Monitoring Based on Multi-agent and Matrix Grammar

Network resources monitoring and management is critical to ensure security and load balance of network and information system, especially in the increasingly extensively used cloud computing and distributed parallel architecture. This paper presents a distributed network resources monitoring solution based on multi-agent and matrix grammar. A distributed multi-agent architecture for network resources monitoring is described. The paper proposes a generic matrix grammar which uses WMI, CIM and SNMP to remotely collect and manage data from network components. The matrix grammar provides a generic mechanism to describe what to be monitored, how to collect and process data. A monitoring automation engine consisting of a matrix analyzer and a recipe processor is described. The proposed solution has good extensibility, scalability, and enables monitoring automation and software reusability.
A UTOMATICALLY C ONVERTING T ABULAR D ATA TO RDF : A N O NTOLOGICAL A PPROACH

Information residing in relational databases and delimited file systems are inadequate for reuse and sharing over the web. These file systems do not adhere to commonly set principles for maintaining data harmony. Due to these reasons, the resources have been suffering from lack of uniformity, heterogeneity as well as redundancy throughout the web. Ontologies have been widely used for solving such type of problems, as they help in extracting knowledge out of any information system. In this article, we focus on extracting concepts and their relations from a set of CSV files. These files are served as individual concepts and grouped into a particular domain, called the domain ontology. Furthermore, this domain ontology is used for capturing CSV data and represented in RDF format retaining links among files or concepts. Datatype and object properties are automatically detected from header fields. This reduces the task of user involvement in generating mapping files. The detail analysis has been performed on Baseball tabular data and the result shows a rich set of semantic information.
An optimized collaborative filtering recommendation algorithm

With the fast development of E-commerce, the magnitudes of users and commodities grow dramastically, resulting in the extremely sparse user rating data. Traditional products' similarity measurement methods perform poorly when facing sparse user rating data. Considering the extreme sparsity of the rating data, collaborative filtering algorithm based on item rating prediction is introduced. Meanwhile collaborative filtering recommendation technology does not take into account the new product whose rating is not available, although recommendation value is high. In this paper, we propose an improved strategy, which uses SVD (Singular Value Decomposition) matrix decomposition algorithm and cosine similarity to group users into clusters with common interests and further to extract the eigenvector of the commercial products to be evaluated by the users inside each group. By using BP (Back Propagation) neural network as the initial training, the proposed algorithm can predict the satisfaction of users group on new products. For those new products, the algorithm assigns higher recommending grade, and gives the priority during recommendation. Finally the results of this optimized collaborative filtering recommendation algorithm are presented. It is proven that, for new product recommendation, the performance of the new algorithm is 12% better than that of the traditional collaborative filtering recommendation algorithm.