Miracle-dz/UniFAR-FTUs huggingface dataset:
Custom Object Layout for Garbage-Collected Languages Gene Novark

Modern architectures require data locality to achieve performance. However, garbage-collected languages like Java limit the ability of programmers to influence object locality, and so impose a significant performance penalty. We present custom object layout, an approach that allows programmers to control object layout in garbage-collected languages. Custom object layout cooperates with copying garbage collection. At collection time, the garbage collector invokes programmer-supplied methods that direct object placement. Custom object layout is particularly effective at improving the locality of classes with well-known traversal patterns, such as dictionary data structures. We show that using custom object layout can reduce cache misses by 50%–77% and thus improves the query performance of dictionary data structures by 20%.
Computational analysis and eye movement experiments of white space in Chinese paintings

In this paper, we report a study examining the effect of white space on perceiving Chinese paintings. Our goal is to investigate whether white space in Chinese paintings is not simply a blank background space but actually meaningful for aesthetic perception. We applied a computational saliency model to analyze the influence of white space on viewers' visual information processing and conducted an eye movement study to confirm significance of white space. Specifically, we analyzed paintings of a well-known artist Wu Guanzhong, and we also collected users' subjective aesthetic rating. Our study results showed that white space is not just a silent background: it is intentionally designed to convey certain information and has a significant effect on viewers' aesthetic experience.
Filtering Junk Mail with a Maximum Entropy Model

The task of junk mail filtering is to rule out unsolicited bulk e-mail (junk) automatically from a user's mail stream. Two classes of methods have been shown to be useful for classifying e-mail messages. The rule based method uses a set of heuristic rules to classify e-mail messages while the statistical based approach models the difference of messages statistically, usually under a machine learning framework. Generally speaking, the statistical based methods are found to outperform the rule based method, yet we found, by combining different kinds of evidence used in the two approaches into a single statistical model, further improvement can be obtained. We present such a hybrid approach, utilizing a Maximum Entropy Model, and show how to use it in a junk mail filtering task. In particular, we present an extensive experimental comparison of our approach with a Naive Bayes classifier, a widely used classifier in e-mail filtering task, and show that this approach performs comparable or better than Naive Bayes method.
A nonparametric statistical approach for stereo correspondence

This paper introduces a novel non-parametric statistical metric that can decide if the recovered set of parameters from a computer vision optimization process can actually be considered as a statistically significant solution. The level of significance can be used as a quality metric of the solution which makes it possible (i) to compare the solutions obtained using different optimization methods, and also (ii) to set intuitive thresholds on the acceptance criteria. We chose the stereo correspondence optimization methods as the initial test bed for the new technique. We compare and combine the results of sum of squared differences (SSD) and sum of absolute differences (SAD) methods for stereo correspondence. We validated our claims by running experiments on standard stereo pairs with ground truth. The results showed that the introduced ideas actually work very well and they can be used to improve the optimization results from different sources.
A fuzzy-based algorithm for Web document clustering

Most existing methods of document clustering are based on a model that assumes a fixed-size vector representation of key terms or key phrases within each document. This assumption is not realistic in large and diverse document collections such as the World Wide Web. We propose a new fuzzy-based document clustering method (FDCM), to cluster documents that are represented by variable length vectors. Each vector element consists of two fields. The first is an identification of a key phrase (its name) in the document and the second denotes a frequency associated with this key phrase within the particular document. A new averaging method is defined for the cluster centroid calculating, and a membership function is developed for relating new documents to existing clusters. The proposed approach is described in detail and we show how it is implemented in a real world application from the area of Web monitoring.
On Mechanistic Modeling of Gene Content Evolution: Birth-Death Models and Mechanisms of Gene Birth and Gene Retention

Characterizing the mechanisms of duplicate gene retention using phylogenetic methods requires models that are consistent with different biological processes. The interplay between complex biological processes and necessarily simpler statistical models leads to a complex modeling problem. A discussion of the relationship between biological processes, existing models for duplicate gene retention and data is presented. Existing models are then extended in deriving two new birth/death models for phylogenetic application in a gene tree/species tree reconciliation framework to enable probabilistic inference of the mechanisms from model parameterization. The goal of this work is to synthesize a detailed discussion of modeling duplicate genes to address biological questions, moving from previous work to future trajectories with the aim of generating better models and better inference.
Insights from an Estimated Search-Based Monetary Model with Nominal Rigidities

We develop a search-based monetary dynamic stochastic equilibrium (DSGE) model with nominal rigidities by introducing the fundamental frictions that generate money demand in an otherwise standard New-Keynesian DSGE model. We use Bayesian methods to estimate two versions of the model based on post 1983 quarterly U.S. data and compare it to a money-in-the-utility (MIU) specification. While the decentralized market mechanism of the search-based models creates a stronger linkage between technology shocks and fluctuations in the stock of money, this linkage comes at a cost in terms of overall time series fit. On the other hand, if one uses the steady state relationships of the estimated DSGE models to predict velocity in periods of high target inflation rates as observed in the 1970s the search-based models deliver much more realistic predictions than the MIU model. In terms of welfare implications the estimated MIU model behaves very much like a New Keynesian DSGE model and a near-zero inflation rate is optimal. According to the search-based model, which also has embodied the same New Keynesian feature, the Friedman motive for keeping the nominal interest rate near zero dominates and negative inflation rates are optimal.
Discourse Structure MS-CIS-89-55 LINC LAB 159

Research on the factors and processes involved in pronoun interpretation has to date concentrated on anaphoric pronouns. Results have supported the now widely-held view that discourse understanding involves the creation of a partial, mental model of the situation described through the discourse. Anaphoric pronouns are taken to refer to elements of that model (often called discourse referents or discourse entities), usually ones that have, at the moment of referring, some special focus status. This paper examines deictic pronouns in particular, ones that refer to the interpretation of one or more clauses. I argue that referents for these pronouns must come from the interpretations of discourse segments on the right frontier of an evolving structure representing the discourse. Under the assumption that reference is always to an individual, this implies that discourse segment interpretations must also be part of the evolving discourse model. I discuss this in the last section of the paper. Comments University of Pennsylvania Department of Computer and Information Science Technical Report No. MSCIS-89-55. This technical report is available at ScholarlyCommons: http://repository.upenn. edu/cis_reports/848 Deictic Reference And Discourse Structure MS-CIS-89-55 LINC LAB 159
Resonant converters for pulsed electrochemical applications

Resonant converters offer an efficient alternative to linear supplies for pulsed electrochemical processes. This paper presents an open loop and closed loop comparison between the dc-dc series and series-parallel resonant converters for a pulsed 500W load. Placing restrictions on the resonant tank parameters proves necessary to achieve continuous transient waveforms. Generalized averaging is applied to each converter with frequency control and the small signal models are compared. The closed loop system proves to be robust using a single mode proportional integral controller. The series-parallel resonant converter is shown to be favourable for this application due to its simpler output stage and a detailed design is presented.
The experiences of female ministers in counselling female rape survivors: A phenomenological study

Rape is an act of humiliation that leaves the survivors ashamed. They therefore often try and hide from others and rarely seek help. Informal discussions with female ministers revealed that some of them had counselled female rape survivors. A descriptive phenomenological study, aimed at exploring and describing the experiences of female ministers in counselling female rape survivors through individual interviews, was conducted. Six ministers were interviewed. They experienced the dichotomy of being a woman and being a minister during their encounter with rape survivors. As women, they became emotionally involved in the suffering of the rape survivors, and as ministers they experienced that prayer and scripture reading in collaboration with counselling promote healing. They also experienced that rape survivors perceived them as approachable because of their gender, but less approachable because of their status as ministers.
Scaling laws for thermal conductivity of crystalline nanoporous silicon based on molecular dynamics simulations

This study establishes that the effective thermal conductivity keff of crystalline nanoporous silicon is strongly affected not only by the porosity f ν and the system’s length Lz but also by the pore interfacial area concentration Ai. The thermal conductivity of crystalline nanoporous silicon was predicted using non-equilibrium molecular dynamics simulations. The Stillinger-Weber potential for silicon was used to simulate the interatomic interactions. Spherical pores organized in a simple cubic lattice were introduced in a crystalline silicon matrix by removing atoms within selected regions of the simulation cell. Effects of the (i) system length ranging from 13 to 130 nm, (ii) pore diameter varying between 1.74 and 5.86 nm, and (iii) porosity ranging from 8% to 38%, on thermal conductivity were investigated. A physics-based model was also developed by combining kinetic theory and the coherent potential approximation. The effective thermal conductivity was proportional to (1 − 1.5f ν) and inversely propor.
Modulation of GAPDH expression and cellular localization after vaccinia virus infection of human adherent monocytes.

Vaccinia virus is able to replicate in many cell types and is known to modulate apoptosis in infected cells. In this study, expression of apoptosis-related genes was screened in human adherent monocytes after vaccinia infection using a DNA array. A marked increase of the key glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) expression was found. Increased expression and nuclear translocation of GAPDH have recently been reported to participate in apoptosis of many cell types. To confirm the array results, levels of GAPDH mRNA were estimated by RT-PCR, showing an increase at 4 h p.i. followed by a slight decrease, which correlated with the viral anti-apoptotic E3L gene transcript levels. Subcellular localization of the enzyme in human monocytes was examined by Western blot and immunostaining of the infected cells. Both experiments revealed accumulation of GAPDH in the nucleus at 14 h p.i. , which was completely suppressed at 24 h p.i. This might indicate GAPDH as a novel target for vaccinia anti-apoptotic modulation.
Online Network-on-Chip Switch Fault Detection and Diagnosis Using Functional Switch Faults

This paper presents efficient methods for online fault detection and diagnosis of Network-on-Chip (NoC) switches. The fault model considered in this research is a system level fault model based on the generic properties of NoC switch functionality. The proposed method is evaluated by fault simulation in a platform using this system level fault model. The experimental results show that with a relatively low area overhead, a large number of NoC switch faults can be detected and diagnosed.
Model selection using measure functions

The concept of measure functions for generalization performance is suggested. This concept provides an alternative way of selecting and evaluating learned models (classifiers). In addition, it makes it possible to state a learning problem as a computational problem. The the known prior (meta-)knowledge about the problem domain is captured in a measure function that, to each possible combination of a training set and a classifier , assigns a value describing how good the classifier is. The computational problem is then to find a classifier maximizing the measure function. We argue that measure functions are of great value for practical applications. Besides of being a tool for model selection, they: (i) force us to make explicit the relevant prior knowledge about the learning problem at hand, (ii) provide a deeper understanding of existing algorithms, and (iii) help us in the construction of problem-specific algorithms. We illustrate the last point by suggesting a novel algorithm based on incremental search for a classifier that optimizes a given measure function.
Short-term efficacy of recombinant human GH therapy in cured acromegaly patients with GH deficiency: a single-center experience

The effectiveness and short-term safety of recombinant human GH (r-hGH) in acromegaly patients with GH deficiency (GHD) after treatment are not well established. The study includes ten subjects with acromegaly who had GHD treated with r-hGH for 6 months. Control groups consisted of ten age-, gender-, and BMI-matched healthy subjects and ten active acromegaly patients who were treatment naïve. Body composition, quality of life (QoL), muscle strength, lipid profile, and cardiovascular risk factors were assessed in all subjects at baseline, and the same parameters were reassessed after 6 months of therapy with r-hGH in acromegaly with GHD. Repeat magnetic resonance imaging of the sella was performed in treated subjects. Optical colonoscopy was done and biopsies were taken from multiple sites for proliferation indices (Ki67). The median duration of GHD was 17.8 months and dose of r-hGH administered was 5.7±1.5 μg/kg per day. There was improvement in bone mineral content (P=0.01), bone mineral density (P=0.04), muscle strength (P<0.001), total cholesterol (P=0.003), high-density cholesterol (P<0.001), and QoL – score (P=0.005), and reduction in low-density cholesterol (P=0.003) and triglyceride (P=0.004) after treatment. There was no change in lean body mass, total body fat, hsCRP, lipoprotein (a), and fibrinogen levels. There was a modest increase in plasminogen activator inhibitor 1 (P=0.002), but it was lower compared with healthy controls and treatment naïve acromegalics (P=0.007). Six month-r-hGH therapy improves body composition, atherogenic lipid profile, QoL, and muscle strength in GHD patients who had acromegaly. Long-term prospective studies are needed to evaluate the effect of r-hGH therapy in these patients.
CREATING SPACE FOR CONNECTION: CREATIVITY IN THE CLASSROOM

Attention to a client’s culture is at the core of counseling services.Working within a client’s values and beliefs must be a lifelong commitment and not restricted to training alone, as cultural competence is a journey and not a destination. Two distinct paradigms available for training are the Multicultural Counseling Competence Model and the Cultural Humility Model. These two models provide structure for working within a client’s culture. The authors propose the integration of mindfulness techniques into classroom training activities to move beyond superficial application and into ownership of culturally appropriate engagement. ARTICLE HISTORY Received 29 May 2017 Revised 16 October 2017 Accepted 10 January 2018
The Accumulation of Deleterious Mutations in Rice Genomes: a Hypothesis on the Cost of Domestication

The extent of molecular differentiation between domesticated animals or plants and their wild relatives is postulated to be small. The availability of the complete genome sequences of two subspecies of the Asian rice, Oryza sativa (indica and japonica) and their wild relatives have provided an unprecedented opportunity to study divergence following domestication. We observed significantly more amino acid substitutions during rice domestication than can be expected from a comparison among wild species. This excess is disproportionately larger for the more radical kinds of amino acid changes (e.g. Cys4Tyr). We estimate that approximately a quarter of the amino acid differences between rice cultivars are deleterious, not accountable by the relaxation of selective constraints. This excess is negatively correlated with the rate of recombination, suggesting that 'hitchhiking' has occurred. We hypothesize that during domestication artificial selection increased the frequency of many deleterious mutations. Introduction How different are domesticated plants and animals from their wild progenitors at the molecular level? It is often postulated that only a few loci contribute to the process of domestication [1] and this has been corroborated in a few examples [2–9]. Therefore, the divergence at the molecular level might be relatively small, probably similar to the divergence between two individuals that are randomly sampled from the wild species. This suggestion is based on the direct effect of artificial selection. However, domestication can also indirectly affect the genome by interfering with natural selection in two different ways. First, during domestication, there can be extensive relaxation of natural selection on characters that are important in the wild but not in cultivation [10]. Many mating characters are in this category, for example, the attraction of potential mates [11]. The reduction in the effective population size during
1 SensoClean : Handling Noisy and Incomplete Data in Sensor Networks using Modeling

Sensor networks have shown tremendous growth in many domains such as environmental monitoring. The data captured from the physical world through these sensor devices, however, tend to be incomplete, noisy, and unreliable. Traditional data cleaning techniques cannot be applied to such data as they do not take into account the strong spatial and temporal correlations typically present in sensor data. Popular data modeling methods like Kalman filters and regression have shown good results in capturing spatio-temporal correlations. We implemented these methods in an extensible toolkit with graphical visualization, and explored their effectiveness in cleaning sensor data. We obtained good data cleaning results in our experiments using Kalman filters. Regression with a high-order polynomial also showed promising results, but worked poorly for data with high variability.
Study on Privacy and Security Methodologies in Cloud Storage

Cloud computing is an emerging environment where many advantages like ease of use and economical benefits are provided to the users. Where as the main issue is privacy and the security of the data stored . Even though cloud computing is providing many advantages, it cannot be used in many applications where privacy is an important concern. In this paper different methodologies that provide security and privacy are studied and compared based on the need for the cloud computing environment.
Simulation of a Swarm Based Painting Algorithm

This paper presents the simulation of a distributed algorithm for painting a priori known rectangular region (9) by swarm of mobile robots. The algorithm divides the whole region into some horizontal strips and each strip is assigned to a particular robot for painting. The simulation is done with Player/Stage Robotic Simulation software. We have simulated an artificial environment that resembles the algorithm and studied the performance of the algorithm. The simulated result proves the correctness of the algorithm.
The many faces of OSp(1|32)

We show that the complete superalgebra of symmetries, including central charges, that underlies F-theories, M-theories and type II string theories in dimensions 12, 11 and 10 of various signatures correspond to rewriting the same OSp(1|32) algebra in different covariant ways. One only has to distinguish the complex and the unique real algebra. We develop a common framework to discuss all signature theories by starting from the complex form of OSp(1|32). Theories are distinguished by the choice of basis for this algebra. We formulate dimensional reductions and dualities as changes of basis of the algebra. A second ingredient is the choice of a real form corresponding to a specific signature. The existence of the real form of the algebra selects preferred spacetime signatures. In particular, we show how the real d = 10 IIA and IIB superalgebras for various signatures are related by generalized T-duality transformations that not only involve spacelike but also timelike directions. A third essential ingredient is that the translation generator in one theory plays the role of a central charge operator in the other theory. The identification of the translation generator in these algebras leads to the star algebras of Hull, which are characterized by the fact that the positive-definite energy operator is not part of the translation generators. We apply our results to discuss different T-dual pictures of the D-instanton solution of Euclidean IIB supergravity.
Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments

MOTIVATION There has been much interest in using patterns derived from surface-enhanced laser desorption and ionization (SELDI) protein mass spectra from serum to differentiate samples from patients both with and without disease. Such patterns have been used without identification of the underlying proteins responsible. However, there are questions as to the stability of this procedure over multiple experiments. RESULTS We compared SELDI proteomic spectra from serum from three experiments by the same group on separating ovarian cancer from normal tissue. These spectra are available on the web at http://clinicalproteomics.steem. com. In general, the results were not reproducible across experiments. Baseline correction prevents reproduction of the results for two of the experiments. In one experiment, there is evidence of a major shift in protocol mid-experiment which could bias the results. In another, structure in the noise regions of the spectra allows us to distinguish normal from cancer, suggesting that the normals and cancers were processed differently. Sets of features found to discriminate well in one experiment do not generalize to other experiments. Finally, the mass calibration in all three experiments appears suspect. Taken together, these and other concerns suggest that much of the structure uncovered in these experiments could be due to artifacts of sample processing, not to the underlying biology of cancer. We provide some guidelines for design and analysis in experiments like these to ensure better reproducible, biologically meaningfully results. AVAILABILITY The MATLAB and Perl code used in our analyses is available at http://bioinformatics.mdanderson. org