Miracle-dz/UniFAR-FTUs huggingface dataset:
Loop Transformations for Architectures with Partitioned Register Banks

Embedded systems require maximum performance from a processor within significant constraints in power consumption and chip cost. Using software pipelining, processors can often exploit considerable instruction-level parallelism (ILP), and thus significantly improve performance, at the cost of substantially increasing register requirements. These increasing register requirements, however, make it difficult to build a high-performance embedded processor with a single, multi-ported register file while maintaining clock speed and limiting power consumption. Some digital signal processors, such as the TI C6x, reduce the number of ports required for a register bank by partitioning the register bank into multiple banks. Disjoint subsets of functional units are directly connected to one of the partitioned register banks. Each register bank and its associate functional units is called a cluster. Clustering reduces the number of ports needed on a per-bank basis, allowing an increased clock rate. However, execution speed can be hampered because of the potential need to copy “non-local” operands among register banks in order to make them available to the functional unit performing an operation. The task of the compiler is to both maximize parallelism and minimize the number of remote register accesses needed. Previous work has concentrated on methods to partition virtual registers amongst the target architecture's clusters. In this paper, we show how high-level loop transformations can enhance the partitioning obtained by low-level schemes. In our experiments, loop transformations improved software pipelining by 27% on a machine with 2 clusters, each having 1 floating-point and 1 integer register bank and 4 functional units. We also observed a 20% improvement on a similar machine with 4 clusters of 2 functional units. In fact, by performing the described loop transformations we were able to show improvements of greater than 10% over schedules (for un-transformed loops) generated with the unrealistic assumption of a single multi-ported register bank.
Constrained spectral clustering for regionalization: Exploring the trade-off between spatial contiguity and landscape homogeneity

A regionalization system delineates the geographical landscape into spatially contiguous, homogeneous units for landscape ecology research and applications. In this study, we investigated a quantitative approach for developing a regionalization system using constrained clustering algorithms. Unlike conventional clustering, constrained clustering uses domain constraints to help guide the clustering process towards finding a desirable solution. For region delineation, the adjacency relationship between neighboring spatial units can be provided as constraints to ensure that the resulting regions are geographically connected. However, using a large-scale terrestrial ecology data set as our case study, we showed that incorporating such constraints into existing constrained clustering algorithms is not that straightforward. First, the algorithms must carefully balance the trade-off between spatial contiguity and landscape homogeneity of the regions. Second, the effectiveness of the algorithms strongly depends on how the spatial constraints are represented and incorporated into the clustering framework. In this paper, we introduced a truncated exponential kernel to represent spatial contiguity constraints for region delineation using constrained spectral clustering. We also showed that a Hadamard product approach that combines the kernel with landscape feature similarity matrix can produce regions that are more spatially contiguous compared to other baseline algorithms.
PEGASUS: A Peta-Scale Graph Mining System Implementation and Observations

In this paper, we describe PEGASUS, an open source Peta Graph Mining library which performs typical graph mining tasks such as computing the diameter of the graph, computing the radius of each node and finding the connected components. As the size of graphs reaches several Giga-, Tera- or Peta-bytes, the necessity for such a library grows too. To the best of our knowledge, PEGASUS is the first such library, implemented on the top of the Hadoop platform, the open source version of MapReduce. Many graph mining operations (PageRank, spectral clustering, diameter estimation, connected components etc.) are essentially a repeated matrix-vector multiplication. In this paper we describe a very important primitive for PEGASUS, called GIM-V (Generalized Iterated Matrix-Vector multiplication). GIM-V is highly optimized, achieving (a) good scale-up on the number of available machines (b) linear running time on the number of edges, and (c) more than 5 times faster performance over the non-optimized version of GIM-V. Our experiments ran on M45, one of the top 50 supercomputers in the world. We report our findings on several real graphs, including one of the largest publicly available Web Graphs, thanks to Yahoo! , with 6,7 billion edges.
Results of a 2-Week Inpatient Stay at the Department for Internal and Integrative Medicine: An Observational Study

Introduction. The Department for Internal and Integrative Medicine in Essen utilizes mind/body medical elements in order to empower patients with chronic diseases to better cope with their symptoms and to adopt a healthy lifestyle. This study explored the influence and predictors of a 2-week integrative treatment program on patients' quality of life. Methods. This observational study was conducted with inpatients as part of the quality assurance program. Patients' quality of life, psychological symptoms, and health locus of control were measured on admission and discharge and again 3, 6, and 12 months after discharge. Regression analyses were conducted to determine the factors predicting improved quality of life. Results. Data from 2486 inpatients treated in 2001–2004 were included (80% female, mean age 53.9 ± 14.3 years). Response rates decreased to 50% at 12 months. Small-to-moderate effects were found on patients' quality of life, anxiety, and depression. Patients' internal locus of control significantly increased. Improved quality of life was mainly predicted by lower baseline scores. Conclusion. Results of this study suggest that a 2-week inpatient treatment might sustainably reduce patients' symptoms and increase their quality of life; however, conclusions are only preliminary. More research is needed to enable the effectiveness to be judged conclusively.
QUANTITATIVE STUDIES OF THE INTERACTION BETWEEN PROGESTERONE AND PREGNANT MARE SERUM ON OVARIAN FUNCTION IN THE EWE.

Injections of progesterone were given to ewes to suppress ovarian cycles; pregnant mare serum gonadotrophin (pms) was administered within 2 days of the final injection of progesterone. Oestrus, numbers of ovulations and follicle growth were observed during the week following treatment. In some experiments, ewes were mated to fertile rams and fertility and fecundity were recorded. Experiments were carried out at different stages of the breeding season. Relationships between methods of suppression of ovarian cycles (dose and frequency of injections of progesterone) and methods of ovarian stimulation (dose and time of administration of pms in relation to the final progesterone injection) for each of the responses were examined. The most important finding was that for comparable dosage levels of pms, the numbers of ovulations were greater after progesterone injections on alternate days than after daily injections. Stage of the breeding season and introduction of rams influenced the results.
Hierarchical Optimal Control of MDPs

Fundamental to reinforcement learning, as well as to the theory of systems and control, is the problem of representing knowledge about the environment and about possible courses of action hierarchically, at a multiplicity of interrelated temporal scales. For example, a human traveler must decide which cities to go to, whether to fly, drive, or walk, and the individual muscle contractions involved in each step. In this paper we survey a new approach to reinforcement learning in which each of these decisions is treated uniformly. Each low-level action and high-level course of action is represented as an option, a (sub)controller and a termination condition. The theory of options is based on the theories of Markov and semi-Markov decision processes, but extends these in significant ways. Options can be used in place of actions in all the planning and learning methods conventionally used in reinforcement learning. Options and models of options can be learned for a wide variety of different subtasks, and then rapidly combined to solve new tasks. Options enable planning and learning simultaneously at a wide variety of times scales, and toward a wide variety of subtasks, substantially increasing the efficiency and abilities of reinforcement learning systems.
Multivoxel Pattern Analysis for fMRI Data: A Review

Functional magnetic resonance imaging (fMRI) exploits blood-oxygen-level-dependent (BOLD) contrasts to map neural activity associated with a variety of brain functions including sensory processing, motor control, and cognitive and emotional functions. The general linear model (GLM) approach is used to reveal task-related brain areas by searching for linear correlations between the fMRI time course and a reference model. One of the limitations of the GLM approach is the assumption that the covariance across neighbouring voxels is not informative about the cognitive function under examination. Multivoxel pattern analysis (MVPA) represents a promising technique that is currently exploited to investigate the information contained in distributed patterns of neural activity to infer the functional role of brain areas and networks. MVPA is considered as a supervised classification problem where a classifier attempts to capture the relationships between spatial pattern of fMRI activity and experimental conditions. In this paper , we review MVPA and describe the mathematical basis of the classification algorithms used for decoding fMRI signals, such as support vector machines (SVMs). In addition, we describe the workflow of processing steps required for MVPA such as feature selection, dimensionality reduction, cross-validation, and classifier performance estimation based on receiver operating characteristic (ROC) curves.
A Constraint-Based Framework for Computing Privacy Preserving OLAP Aggregations on Data Cubes

A constraint-based framework for computing privacy preserving OLAP aggregations on data cubes is proposed and experimentally assessed in this paper. Our framework introduces a novel privacy OLAP notion, which, following consolidated paradigms of OLAP research, looks at the privacy of aggregate patterns defined on multidimensional ranges rather than the privacy of individual tuples/data-cells, like similar efforts in privacy preserving database and data-cube research. To this end, we devise a threshold-based method that aims at simultaneously accomplishing the so-called privacy constraint, which inferiorly bounds the inference error, and the so-called accuracy constraint, which superiorly bounds the query error, on OLAP aggregations of the target data cube, following a best-effort approach. Finally, we complete our main theoretical contribution by means of an experimental evaluation and analysis of the effectiveness of our proposed framework on synthetic, benchmark and real-life data cubes.
Superior Staging of Liver Tumors with Laparoscopy and Laparoscopic Ultrasound

ObjectiveThe authors describe the technique of staging laparoscopy with laparoscopic contact ultrasonography in the preoperative assessment of patients with liver tumors, and assess its impact on the selection of patients for hepatic resection with curative intent. Summary Background DataLaparoscopy may be useful in the selection of patients with a variety of intra-abdominal malignancies for operative intervention. Laparoscopic ultrasonography is a new technique that combines the principles of high resolution intraoperative contact ultrasound with those of the laparoscopic examination, and thus, allows the laparoscopist to perform detailed assessment of the liver. MethodsThis study analyzes a cohort of 50 consecutive patients who were diagnosed as having potentially resectable liver tumors, and in whom staging laparoscopy was successfully undertaken. Laparoscopic ultrasonography was performed in 43 patients, and the impact of the ensuing findings on the decision to proceed to operative assessment of resectability is examined. The resectability rate in those patients assessed laparoscopically and subsequently submitted to laparotomy is compared with a preceding group of patients in whom no laparoscopic assessment was performed. ResultsLaparoscopy demonstrated factors precluding curative resection in 23 patients (46%). Laparoscopic ultrasonography identified liver tumors not visible during laparoscopy in 14 patients (33%), and provided staging information in addition to that derived from laparoscopy alone in 18/43 patients (42%). The resectability rate was significantly higher among those patients undergoing laparoscopic staging (93%) compared with those in whom operative assessment was undertaken without laparoscopy (58%). ConclusionsStaging laparoscopy with laparoscopic ultrasonography optimizes patient selection for liver resection with curative intent.
Preliminary findings of the effect of a 3-year after-school physical activity intervention on fitness and body fat: the Medical College of Georgia Fitkid Project.

OBJECTIVE To evaluate the effect of a 3-year after-school physical activity (PA) intervention on aerobic fitness and percent body fat (%BF). METHODS In total, 18 schools were randomized into intervention or control arms. Measurements were made at the beginning and end of the third, fourth and fifth grades. Fitness was measured with heart rate response to a bench-stepping task. %BF and bone density were measured with dual-energy x-ray absorptiometry. The intervention included 40 min of academic enrichment activities, during which healthy snacks were provided, and 80 min of moderate-to-vigorous PA (MVPA). RESULTS Data analyses were performed on 206 youths who remained in the same schools for the 3-year period, who were measured at all six time points and, for the intervention group, who attended at least 40% of the sessions in each of the 3 years. The group by time interactions were significant for fitness (p < 0.01) and %BF (p < 0.05). Children in intervention schools improved in fitness and %BF during the school years and returned to levels similar to those in control schools during the summers. Over the six measurement points, the intervention group increased more than the control group in bone density (p < 0.01), fat-free soft tissue (p < 0.01), weight (p < 0.01), height (p < 0.01), and body mass index (p < 0.05). CONCLUSIONS An after-school program focusing on MVPA had a beneficial effect on fitness and body composition. During the summers, the beneficial effect of the previous year's participation on fitness and %BF was lost. This highlights the importance of year-round programs to promote healthy growth in youths.
Digital Demography

Demography is the science of human populations and, at its most basic, focuses on the processes of (i) fertility, (ii) mortality and (iii) mobility. Whereas modern states are typically in a reasonable position to keep records on both fertility and mortality, through birth and death registrations, as well as through censuses, measuring the mobility of populations represents a particular challenge due to reasons ranging from inconsistencies in official definitions across countries, to the difficulty of quantifying illegal migration. At the same time, mere numbers, whether on births, deaths or migration events, shed little light on the underlying causes, hence providing insufficient information to policy makers. The use of digital methods and data sources, ranging from social media data to web search logs, offers possibilities to address some of the challenges of traditional demography by (i) improving existing statistics or helping to create new ones, and (ii) enriching statistics by providing context related to the drivers of demographic changes. This tutorial will help to familiarize participants with research in this area. First, we will give an overview of fundamental concepts in demographic research including the population equation. We also showcase traditional data collection and analysis methods such as census microdata, the construction of a basic life table, panel datasets and survival analysis. In the second part, we present a number of studies that have tried to overcome limitations of traditional approaches by using innovative methods and data sources ranging from geo-tagged tweets to online genealogy. We will put particular emphasis on (i) methodological challenges such as issues related to bias, as well as on (ii) how to collect open data from the World Wide Web. The slides and other material for this tutorial are available at https://sites.google. com/site/digitaldemography/.
Eomesodermin, a target gene of Pou4f2, is required for retinal ganglion cell and optic nerve development in the mouse

The mechanisms regulating retinal ganglion cell (RGC) development are crucial for retinogenesis and for the establishment of normal vision. However, these mechanisms are only vaguely understood. RGCs are the first neuronal lineage to segregate from pluripotent progenitors in the developing retina. As output neurons, RGCs display developmental features very distinct from those of the other retinal cell types. To better understand RGC development, we have previously constructed a gene regulatory network featuring a hierarchical cascade of transcription factors that ultimately controls the expression of downstream effector genes. This has revealed the existence of a Pou domain transcription factor, Pou4f2, that occupies a key node in the RGC gene regulatory network and that is essential for RGC differentiation. However, little is known about the genes that connect upstream regulatory genes, such as Pou4f2 with downstream effector genes responsible for RGC differentiation. The purpose of this study was to characterize the retinal function of eomesodermin (Eomes), a T-box transcription factor with previously unsuspected roles in retinogenesis. We show that Eomes is expressed in developing RGCs and is a mediator of Pou4f2 function. Pou4f2 directly regulates Eomes expression through a cis-regulatory element within a conserved retinal enhancer. Deleting Eomes in the developing retina causes defects reminiscent of those in Pou4f2-/- retinas. Moreover, myelin ensheathment in the optic nerves of Eomes-/- embryos is severely impaired, suggesting that Eomes regulates this process. We conclude that Eomes is a crucial regulator positioned immediately downstream of Pou4f2 and is required for RGC differentiation and optic nerve development.
Robust Formulations for Training Multilayer Perceptrons

The connection between robust statistical estimates and nonsmooth optimization is established. Based on the resulting family of optimization problems, robust learning problem formulations with regularization-based control on the model complexity of the multilayer perceptron network are described and analyzed. Numerical experiments for simulated regression problems are conducted, and new strategies for determining the regularization coefficient are proposed and evaluated.
Modeling effectiveness of GM mosquito release

A recent highly controversial mosquito control experiment had been conducted in Malaysia. The experiment was designed to assess the effectiveness of reducing mosquito population by releasing genetically modified (GM) male Aedes aegypti mosquitoes into a small inland district of Bentong in Pahang to outcompete the wild male mosquitoes. The compiled relevant data from the Grand Cayman experiments in 2009/2010 is used to develop and calibrate a numerical simulation model for assessing the effectiveness of releasing GM mosquito in controlling dengue mosquito population in the Grand Cayman. Simulation results indicate that releasing GM mosquitoes is not economically feasible in controlling wild A. aegypti population for three reasons. First, meaningful reduction of wild mosquito population is possible only if large one-off initial flooding ratio exceeding 10 transgenic males/wild male is applied. Second, continuous GM mosquito releases at the flooding rate exceeding 1 transgenic male for every 10 wild male per day must be maintained over an infinite time horizon in order to sustain low wild mosquito population. Third, the GM males must be released at many locations separated by only a few hundred meters to achieve meaningful results. The economic and logistic cost implication is exorbitant. Major difficulty remains to be resolved. In particular, in-depth cost-benefit analysis on this control program is essential to ensure long-term institutional and social support.
Cultural Reciprocity: Exploring the Impacts of Cross-Cultural Instruction on Professorial Self-Reflection.

Cultural reciprocity refers to the dynamic and material exchange of knowledge, values, and perspectives between two or more individuals of different cultural (e.g., racial, ethnic, socioeconomic, religious) backgrounds. In this paper, cultural reciprocity is discussed as it pertains to professors of education and their students, based on the history of their interactions and diversity of experiences in cross-cultural settings. The ongoing study is personal and collaborative as a Japanese-Canadian female, and an Anglo-Saxon male engage in self-reflection with respect to their experiences in teaching Canadian College of Education students in a cross-cultural setting. After a substantial literature review, narratives taken from e-mail correspondence and personal notes are used to relate a specific example in which the female teacher used her own experience to discuss the nature of prejudice, racism, and ethnicity in an educational foundations class. Reflection on responses from the male teacher and a discussion on reconstruction of reality in light of the female teacher's experiences in teaching in the Indian Teacher Education Program illustrated the use of cultural reciprocity in her classes and its positive effect on her students and her own personal and professional development. (Contains 14 references.) (ND) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. * *********************************************************************** Cultural Reciprocity: Exploring the Impacts of Cross-Cultural Instruction on Professorial Self-Reflection Wendy K. Lamont Department of Curriculum Studies/Indian Teacher Education Program College of Education, University of Saskatchewan Saskatoon, Saskatchewan CANADA S7N OX1 (306) 966-7612 Jonathan L. Black-Branch University of Oxford, Wolfson College Oxford, ENGLAND OX2 6UD Research Paper Presented at the 1996 Annual Meeting of the American Educational Research Association U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) This document has been reproduced as received from the person or organization originating it. Minor changes have been made to improve reproduction duality. Points of view or opinions staled in this document do not necessarily represent official OEFII position or policy. April, 1996 New York, NY BEST COPY AVAILABLE 2 "PERMISSION TO REPRODUCE THIS MATERIAL HAS Bfil GRANTE BY