Miracle-dz/UniFAR-FTUs huggingface dataset:
Long‐term outcomes in patients treated with proton therapy for localized prostate cancer

The aim of this retrospective study was to report long‐term clinical outcomes in patients treated with proton therapy (PT) for localized prostate cancer. Between 2001 and 2014, 1375 consecutive patients were treated with PT. Patients were classified into prognostic risk groups based on the National Comprehensive Cancer Network criteria. Freedom from biochemical relapse (FFBR), cancer‐specific survival (CSS) and incidence of late gastrointestinal (GI)/genitourinary (GU) toxicities were calculated. Multivariate analysis was performed to identify clinical prognostic factors for FFBR and late toxicities. The median follow‐up period was 70 months (range, 4–145 months). In total, 99% of patients received 74 Gy (relative biologic effectiveness [RBE]); 56% of patients received neoadjuvant androgen deprivation therapy. For the low‐, intermediate‐, high‐, and very high‐risk groups, 5‐year FFBR was 99% (95% confidence intervals [CI], 96–100%), 91% (95% CI, 88–93%), 86% (95% CI, 82–89%), and 66% (95% CI, 53–76%), respectively, and 5‐year CSS was 100% (95% CI, 100–100%), 100% (95% CI, 100–100%) , 99% (95% CI, 97–100%), and 95% (95% CI, 94–98%), respectively. Patient age, T classification, Gleason score, prostate‐specific antigen, and percentage of positive cores were significant prognostic factors for FFBR. Grade 2 or higher GI and GU toxicities were 3.9% and 2.0%. Patient age was a prognostic factor for both late GI and GU toxicities. This study represents the largest cohort of patients treated with PT for localized prostate cancer, with the longest follow‐up to date. Our results demonstrate that the biochemical control of PT is favorable particularly for high‐ and very high‐risk patients with lower late genitourinary toxicity and indicates the necessity of considering patient age in the treatment protocols.
High-Achieving and Average Students’ Reading Growth: Contrasting School and Summer Trajectories

ABSTRACT. Much is unknown about how initially high-achieving students grow academically, especially given the measurement issues inherent in assessing growth for the highest performing students. This study compared initially high-achieving and average students’ growth in reading (in a cohort of third-grade students from 2,000 schools) over 3 years. Using a 3-level longitudinal piecewise hierarchical linear model, we contrasted summer and school year growth rates to examine initially high-achieving and average students’ trajectories. Average students grew steeply during the school year and gained nothing over the summer. By contrast, initially high-achieving students grew more slowly than average students during school but maintained that same slower growth rate in the summer.
Design and Implementation of a Portable ACE-Based IPC Platform

ACE is a freely available, open-source object-oriented framework that implements many core design patterns for concurrent communication software. ACE provides reusable C++ wrappers, frameworks and real-time ORB available for most operating systems. In this paper, we introduce the functionality of ACE components, design an effective and portable IPC platform framework based on ACE middleware and implement the IPC platform system in C++. Eventually, we test our IPC platform, compare it with the non-ACE system and conclude its advantages and drawbacks.
Outlier-robust dimension reduction and its impact on hyperspectral endmember extraction

Hyperspectral endmember extraction is a process to extract end-member signatures from the observed hyperspectral data of an area. The presence of outliers in the data has been proved to pose a serious problem in endmember extraction. In this paper, unlike conventional outlier detectors which may be sensitive to window settings, we propose a robust affine set fitting (RASF) algorithm for joint dimension reduction and outlier detection without any window setting. Given the number of endmembers in advance, the RASF algorithm is to find a data-representative affine set from the corrupted data, while making the effects of outliers minimum, in the least-squares error sense. The proposed RASF algorithm is then combined with Neyman-Pearson hypothesis testing, termed RASF-NP, to further estimate the number of outliers present in the data. Computer simulations demonstrate the efficacy of the proposed method, and its impact on existing endmember extraction algorithms.
COMMUNITY COLLEGE RESIDENCE HALLS: A HIDDEN TREASURE

Residence halls have the potential for making significant contributions to the learning and development of community college students. Understanding students’ perceptions of both staff and peer contributions to the academic climate in their residence halls is critical. The results of this study indicate that residence life staff are perceived to be higher contributors to the academic climate in living environments than residential peers. The findings from this nationwide study provide benchmark data for community colleges with residence halls. Suggestions are made for how community colleges can reexamine the educational potential of residence halls.
Development of an information projection interface using a projector-camera system

This paper proposes a position-free interface system that enables a user to input and obtain information everywhere in the environment with a projector-camera system. Hand-waving detected in the image is used as a cue to start the system, to distinguish gestures based on the user's intension of operation from other daily-life motions, and to specify the position of the user's hand. Hand-waving detection is implemented based on combination of background subtraction method and skin color extraction. In addition, we focus on changes of brightness value in each pixel. The user's hand is tracked using a particle filter algorithm. The user designates the projection area freely on a plane in the environment with his/her hand. The projector mounted on a pan-tilt unit projects information according to the user's designation. Then, the user's fingertip is detected using simple template matching and he/she interacts with the projected information to input commands without any devices. As one of applications, we have developed an interface system to operate electrical appliances (TV) intuitively in a daily life scene.
The Impact of Self- and Peer-Grading on Student Learning

The 2001 U.S. Supreme Court Case of Falvo v. Owasso School System (Owasso Independent School District No I-011 v. Falvo) has focused national attention on the common classroom practice of peer-grading. In a unanimous decision the court reaffirmed the popular view that students grading each others' tests is valuable, saving teachers' time and augmenting student learning. Our study puts these presumed benefits to the test in 4 middle school science classrooms. We compared teacher-assigned grades to those awarded either by students to themselves or by their peers. By training students to grade with the help of a scoring rubric, a very high correlation was obtained between students and their teacher on test questions (r = 0.91 to 0.94). We found patterns of bias when students assigned grades. When grading others, students awarded lower grades to the best performing students than their teacher did. When grading themselves, lower performing students tended to inflate their own low scores. Performance on an unannounced, 2nd administration of the same test 1 week later measured the degree to which student-grading resulted in any increased understanding. Students who graded their peers' tests did not gain significantly more than a control group of students who did not correct any papers but simply took the same test again. Those students who corrected their own tests improved dramatically. Self-grading and peer-grading appear to be reasonable aids to saving teachers' time. Self-grading appears to result in increased student learning; peer-grading does not.
Dialogic Responsiveness: Toward Synthesis, Complexity, and Holism in Our Reponses to Young Literacy Learners

In this investigation of classroom literacy contexts, the term “dialogic responsiveness” is introduced and utilized in order to provide a holistic framework for synthesizing, researching, and describing the complexities of responsive dialogue. An in-depth perspective was provided via one reading teacher, who exemplified dialogic responsiveness, as she interacted with six focus students during literacy instruction. A breadth of perspectives was provided via four regular classroom teachers as they interacted with four of these focus students during literacy instruction. Findings reveal how these teachers were able to be responsive to the cultural, cognitive, emotional, motivational, and physical needs of young literacy learners. The findings also detail how each teacher's dialogic responsiveness influenced the literacy participation of students. The complexities of these findings are discussed by reviving and extending a metaphor used previously in the literature-the metaphor of weaving. This metaphor is argued to be useful because it provides holistic insight into the complexities of being dialogically responsive to young literacy learners.
Structure and specificity of an antibody targeting a proteolytically cleaved IgG hinge

The functional role of human antihinge (HAH) autoantibodies in normal health and disease remains elusive, but recent evidence supports their role in the host response to IgG cleavage by proteases that are prevalent in certain disorders. Characterization and potential exploitation of these HAH antibodies has been hindered by the absence of monoclonal reagents. 2095‐2 is a rabbit monoclonal antibody targeting the IdeS‐cleaved hinge of human IgG1. We have determined the crystal structure of the Fab of 2095‐2 and its complex with a hinge analog peptide. The antibody is selective for the C‐terminally cleaved hinge ending in G236 and this interaction involves an uncommon disulfide in VL CDR3. We probed the importance of the disulfide in VL CDR3 through engineering variants. We identified one variant, QAA, which does not require the disulfide for biological activity or peptide binding. The structure of this variant offers a starting point for further engineering of 2095‐2 with the same specificity, but lacking the potential manufacturing liability of an additional disulfide. Proteins 2014; 82:1656–1667. © 2014 Wiley Periodicals, Inc.
Validation of the Korean Version of the Acupuncture Expectancy Scale

Objectives Expectancy has been shown to affect patients’ responses to acupuncture therapy. However, no validated measure of expectancy for acupuncture is available in the Korean language. The Acupuncture Expectancy Scale (AES), a 4-item self-reporting questionnaire, is the validated instrument for measuring expectancies regarding acupuncture therapy. We translated the AES into Korean and examined its test–retest reliability and construct validity. Methods The AES was translated using a forward and backward translation procedure. Internal consistency was assessed in 275 participants with item-total correlations. Construct validity was also assessed by performing principal component analysis and correlating scores on the scale with the participants’ intention to receive acupuncture therapy. Test–retest reliability was assessed in 33 participants by calculating Cronbach's α and Spearman rank correlation coefficients. Results Internal consistency was high (Cronbach's α=0.910). Principal component analysis showed that expectancy of acupuncture treatment accounted for 79.2% of the variance. The AES was positively correlated with participants’ intention to receive acupuncture treatment (r=0.695, p<0.001). Test–retest reliability in 33 of the 275 participants was adequate, with the Spearman rank correlation coefficient ranging from 0.500 to 0.737 (p<0.001). Conclusions The Korean version of the AES is a valid and reliable instrument for measuring patients’ expectancies regarding acupuncture treatment in the Korean population.
Interventions to promote retention in substance abuse treatment

Objectives: Compare two methods of improving retention in substance abuse treatment for persons with traumatic brain injury. Design: Randomized clinical trial with control group comparison. Interventions: Provision of a financial incentive and reduction of logistical barriers. Outcome measures: Treatment attendance, perceived therapeutic alliance, premature termination. Results: Provision of a financial incentive was highly effective for facilitating early attendance and appeared to promote eventual successful treatment completion. Reduction of logistical barriers did not significantly improve attendance or successful discharge. The hypothesized role of improved therapeutic alliance as a consequence of intervention and a mediator for preventing premature termination was not supported. However, results suggested that intervention, particularly financial incentives, promoted congruence between counsellor and client perceived therapeutic alliance. Conclusions: For clients with traumatic brain injuries, provision of a financial incentive at an early point in substance abuse treatment substantially improves attendance and reduces the likelihood of premature termination. The basis for this effect appears to involve more than enhancement of the therapeutic alliance. We posit that concrete incentives can provide an opportunity for successful rule-governed behaviour that may generalize to other areas of improved impulse control.
Spirituality in Social Work: A Survey of Students at South African Universities

Academic discourse related to spirituality has proliferated globally. The rationale for its inclusion in social work education rests on the premise that spirituality is a critical strength in social work practice. This paper explores this aspect and highlights empirical research related to the inclusion of spirituality in training. It does this within the context of a SA study that was undertaken to explore the views of students with regard to the role of religion and spirituality in practice and the extent to which South African curricula considers religion and spirituality. The research was conducted by distributing questionnaires to final year social work students at schools of social work (N = 21); 342 completed surveys were returned yielding a response of 47%. The findings revealed high levels of religiosity or spirituality amongst students, a gap in the curriculum on spirituality and support for its inclusion in social work education.
Meat Consumption and Commitments on Meat Policy: Combining Individual and Public Health

Although meat consumption plays a significant role for individual and public health, there is only little empirical research on the motives of meat consumption informed by health psychology and hardly any on socio-political commitments concerning general meat production taking on a public health perspective. To fill this gap, a questionnaire study was conducted to examine the links between both disciplines. Correlational and multiple regression analyses reveal that individual meat consumption is primarily based on self-centred judgments of control beliefs protecting ones health and of taste, whereas socio-political commitments are based on a mixture of selfcentred judgments and animal ethics. Based on these results, it is concluded, that models on health behaviour should integrate the social perspective, and that in intervention programs issues of individual as well as public health should be given equal importance.
Correlation of computed tomography and positron emission tomography in patients with metastatic gastrointestinal stromal tumor treated at a single institution with imatinib mesylate: proposal of new computed tomography response criteria.

PURPOSE Response Evaluation Criteria in Solid Tumors (RECIST) are insensitive in evaluating gastrointestinal stromal tumors (GISTs) treated with imatinib. This study evaluates whether computed tomography (CT) findings of GIST after imatinib treatment correlate with tumor responses by [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET) and develops reliable, quantitative, CT response criteria. PATIENTS AND METHODS A total of 172 lesions selected by RECIST were evaluated in 40 patients with metastatic GISTs treated with imatinib. All patients had pretreatment and 2-month follow-up CTs and FDG-PETs. Multivariate analysis was performed using tumor size and density (Hounsfield unit [HU]) on CT and maximum standardized uptake value (SUVmax) on FDG-PET. Patients were observed up to 28 months. RESULTS Mean baseline tumor size and density on CT were 5.3 cm and 72.8 HU, respectively, and mean baseline SUVmax on FDG-PET was 5.8. Thirty-three patients had good response on FDG-PET. A decrease in tumor size of more than 10% or a decrease in tumor density of more than 15% on CT had a sensitivity of 97% and a specificity of 100% in identifying PET responders versus 52% and 100% by RECIST. Good responders on CT at 2 months had significantly longer time to progression than those who did not respond (P = .01). CONCLUSION Small changes in tumor size or density on CT are sensitive and specific methods of assessing the response of GISTs. If the prognostic value of our proposed CT response criteria can be confirmed prospectively, the criteria should be employed in future studies of patients with GIST.
Very-Large Scale Code Clone Analysis and Visualization of Open Source Programs Using Distributed CCFinder: D-CCFinder

The increasing performance-price ratio of computer hardware makes possible to explore a distributed approach at code clone analysis. This paper presents D-CCFinder, a distributed approach at large-scale code clone analysis. D-CCFinder has been implemented with 80 PC workstations in our student laboratory, and a vast collection of open source software with about 400 million lines in total has been analyzed with it in about 2 days. The result has been visualized as a scatter plot, which showed the presence of frequently used code as easy recognizable patterns. Also, D-CCFinder has been used to analyze a single software system against the whole collection in order to explore the presence of code imported from open source software.
Deep Context Modeling for Web Query Entity Disambiguation

In this paper, we presented a new study for Web query entity disambiguation (QED), which is the task of disambiguating different candidate entities in a knowledge base given their mentions in a query. QED is particularly challenging because queries are often too short to provide rich contextual information that is required by traditional entity disambiguation methods. In this paper, we propose several methods to tackle the problem of QED. First, we explore the use of deep neural network (DNN) for capturing the character level textual information in queries. Our DNN approach maps queries and their candidate reference entities to feature vectors in a latent semantic space where the distance between a query and its correct reference entity is minimized. Second, we utilize the Web search result information of queries to help generate large amounts of weakly supervised training data for the DNN model. Third, we propose a two-stage training method to combine large-scale weakly supervised data with a small amount of human labeled data, which can significantly boost the performance of a DNN model. The effectiveness of our approach is demonstrated in the experiments using large-scale real-world datasets.
Experience with a performance analyzer for multithreaded applications

The authors describe the CONVEX performance analyzer, CX/sub pa/, which has the capability to monitor parallel regions of code, in particular loops, executed in a time-sharing environment. The means by which profiling information is measured for a parallel region is described along with the operating system facilities required to support it. The effectiveness of the approach is evaluated and suggestions for improvement are made. The profiling of parallel regions is implemented on the CONVEX C200 series computers, tightly coupled, shared-memory, parallel/multiprocessor systems running Convex OS V8.0, a UNIX based operating system. <<ETX>>
Analysis of micronucleus induction of pyrimethamine in in vitro CHL cells and in in vivo mouse bone marrow cells.

In vivo and in vitro mutagenicity of pyrimethamine were examined in the micronucleus test. Pyrimethamine strongly induced micronuclei in a dose-dependent manner in the in vitro micronucleus test using the Chinese hamster lung (CHL) cell line, when treated at 0.2-1.6 micrograms/ml for 48 h. The in vivo micronucleus test was carried out in mice after the first, second, third and fourth administration of doses up to 40 mg/kg p.o. The results showed no increased frequency of micronuclei after any treatment, though pyrimethamine was shown to persist at levels > 2 micrograms/ml in plasma after a single oral administration of 50 mg/kg.
Efficient classification across multiple database relations: a CrossMine approach

Relational databases are the most popular repository for structured data, and is thus one of the richest sources of knowledge in the world. In a relational database, multiple relations are linked together via entity-relationship links. Multirelational classification is the procedure of building a classifier based on information stored in multiple relations and making predictions with it. Existing approaches of inductive logic programming (recently, also known as relational mining) have proven effective with high accuracy in multirelational classification. Unfortunately, most of them suffer from scalability problems with regard to the number of relations in databases. In this paper, we propose a new approach, called CrossMine, which includes a set of novel and powerful methods for multirelational classification, including 1) tuple ID propagation, an efficient and flexible method for virtually joining relations, which enables convenient search among different relations, 2) new definitions for predicates and decision-tree nodes, which involve aggregated information to provide essential statistics for classification, and 3) a selective sampling method for improving scalability with regard to the number of tuples. Based on these techniques, we propose two scalable and accurate methods for multirelational classification: CrossMine-Rule, a rule-based method and CrossMine-Tree, a decision-tree-based method. Our comprehensive experiments on both real and synthetic data sets demonstrate the high scalability and accuracy of the CrossMine approach
Pharmacoinformatics analysis to identify inhibitors of Mtb-ASADH

Aspartate-semialdehyde dehydrogenase (ASADH; EC 1.2.1.11) is a key enzyme in the biosynthesis of essential amino acids in prokaryotes and fungi, inhibition of ASADH leads to the development of novel antitubercular agents. In the present work, a combined structure and ligand-based pharmacophore modeling, molecular docking, and molecular dynamics (MD) approaches were employed to identify potent inhibitors of mycobacterium tuberculosis (Mtb)-ASADH. The structure-based pharmacophore hypothesis consists of three hydrogen bond acceptor (HBA), two negatively ionizable, and one positively ionizable center, while ligand-based pharmacophore consists of additional one HBA and one hydrogen bond donor features. The validated pharmacophore models were used to screen the chemical databases (ZINC and NCI). The screened hits were subjected to ADME and toxicity filters, and subsequently to the molecular docking analysis. Best-docked 25 compounds carry the characteristics of highly electronegative functional groups (–COOH and –NO2) on both sides and exhibited the H-bonding interactions with highly conserved residues Arg99, Arg249, and His256. For further validation of docking results, MD simulation studies were carried out on two representative compounds NSC51108 and ZINC04203124. Both the compounds remain bound to the key active residues of Mtb-ASADH during the MD simulations. These identified hits can be further used for lead optimization and in the design more potent inhibitors against Mtb-ASADH.