Miracle-dz/UniFAR-FTUs huggingface dataset:
Series The Deutsch-Jozsa Problem : De-quantization and Entanglement

The Deustch-Jozsa problem is one of the most basic ways to demonstrate the power of quantum computation. Consider a boolean function f : {0, 1} n → {0, 1} and suppose we have a black box to compute f. The Deutsch-Jozsa problem is to determine if f is constant [i.e. f (x) = const, ∀x ∈ {0, 1} n ] or if f is balanced [i.e. f (x) = 0 for exactly half the possible input strings x ∈ {0, 1} n ] using as few calls to the black box computing f as is possible, assuming f is guaranteed to be constant or balanced. Classically it appears that this requires at least 2 n−1 + 1 black box calls in the worst case, but the well known quantum solution solves the problem with probability 1 in exactly one black box call. However, it has been found that in some cases equivalent classical, deterministic solutions also exist. We attempt to clarify the power of the quantum solution in order to gain better insight into where the power of quantum computation comes from, as well as the ability to determine when classical, deterministic counterparts can be found.
Lexical chains as representations of context for the detection and correction of malapropisms

Natural language utterances are, in general, highlyambiguous, and a unique interpretationcan usuallybe determined only by taking into account the constraining inﬂuence of the context in which theutterance occurred. Much of the research in natural language understanding in the last twenty yearscan be thought of as attempts to characterize and represent context and then derive interpretationsthatﬁt best with that context. Typically, this research was heavy with AI, taking context to be nothing lessthan a complete conceptual understanding of the preceding utterances. This was reasonable, as suchan understanding of a text was often the main task anyway. However, there are many text-processingtasksthatrequireonlya partialunderstandingofthetext, andhencea ‘lighter’representationofcontextis sufﬁcient. In this paper, we examine the idea oflexical chains as such a representation. We showhow they can be constructed by means of WordNet, and how they can be applied in one particularlinguistic task: the detection and correction of malapropisms.A malapropism is the confounding of an intended word with another word of similar sound orsimilar spelling that has a quite different and malapropos meaning, e.g., an ingenuous [for ingenious]machine forpeelingoranges. In thisexample, there isaone-letterdifference betweenthe malapropismand the correct word. Ignorance, or a simple typing mistake, might cause such errors. However, sinceingenuous is a correctly spelled word, traditional spelling checkers cannot detect this kind of mistake.In section 4, we will propose an algorithm for detecting and correcting malapropisms that is based onthe construction of lexical chains.
Expert Judgement and Expert Disagreement

As Hammond has argued, traditional explanations for disagreement among experts (incompetence, venality, and ideology) are inadequate. The character and fallibilities of the human judgement process itself lead to persistent disagreements even among competent, honest, and disinterested experts. Social Judgement Theory provides powerful methods for analysing such judgementally based disagreements when the experts’ judgement processes can be represented by additive models involving the same cues. However, the validity and usefulness of such representations depend on several conditions: (a) experts must agree on a problem definition, (b) experts must have access to the same information, and (c) experts must use the same organising principles. When these conditions are not met, methods for diagnosing and treating disagreement are poorly understood. As a start towards developing such an understanding, sources of expert disagreement are discussed and categorised.
A novel bioinformatics pipeline for identification and characterization of fusion transcripts in breast cancer and normal cell lines

SnowShoes-FTD, developed for fusion transcript detection in paired-end mRNA-Seq data, employs multiple steps of false positive filtering to nominate fusion transcripts with near 100% confidence. Unique features include: (i) identification of multiple fusion isoforms from two gene partners; (ii) prediction of genomic rearrangements; (iii) identification of exon fusion boundaries; (iv) generation of a 5'-3' fusion spanning sequence for PCR validation; and (v) prediction of the protein sequences, including frame shift and amino acid insertions. We applied SnowShoes-FTD to identify 50 fusion candidates in 22 breast cancer and 9 non-transformed cell lines. Five additional fusion candidates with two isoforms were confirmed. In all, 30 of 55 fusion candidates had in-frame protein products. No fusion transcripts were detected in non-transformed cells. Consideration of the possible functions of a subset of predicted fusion proteins suggests several potentially important functions in transformation, including a possible new mechanism for overexpression of ERBB2 in a HER-positive cell line. The source code of SnowShoes-FTD is provided in two formats: one configured to run on the Sun Grid Engine for parallelization, and the other formatted to run on a single LINUX node. Executables in PERL are available for download from our web site: http://mayoresearch.mayo. edu/mayo/research/biostat/stand-alone-packages.cfm.
Candles in the Wind: Resisting Repression in Liberia (1979–2003)

Scholars have been extending social-movement analysis beyond its base in the industrialized West to Latin America and Asia, but rarely to Africa. Social movements resisting repression in nondemocratic settings have usually had the help of external “opportunities” or favorable circumstances. This study, however, examines a peaceful social movement in Liberia, a movement that resisted repression under two regimes, advocating for human rights and democratic freedom without such “opportunities. ” How did this happen? The study finds four explanations: the formation of a microsocial movement with no formal leadership and only loosely connected strands of resistance, which were harder to control; a high level of commitment by participants; the skillful use of local media and international organizations to put pressure on the regime; and historical roots of resistance, especially in the 1970s.
Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors

MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.
Subunit Mobility and the Chaperone Activity of Recombinant αB-Crystallin

The comparison of the chaperone-like activity of native and covalently cross-linked human αB-crystallins has confirmed the important role of the subunit mobility in the chaperoning mechanism. Our data clearly demonstrate that the chaperone-like activity of α-crystallin is not only a surface phenomenon as was suggested by some researchers.
Reproducing and learning new algebraic operations on word embeddings using genetic programming

Word-vector representations associate a high dimensional real-vector to every word from a corpus. Recently, neural-network based methods have been proposed for learning this representation from large corpora. This type of word-to-vector embedding is able to keep, in the learned vector space, some of the syntactic and semantic relationships present in the original word corpus. This, in turn, serves to address different types of language classification tasks by doing algebraic operations defined on the vectors. The general practice is to assume that the semantic relationships between the words can be inferred by the application of a-priori specified algebraic operations. Our general goal in this paper is to show that it is possible to learn methods for word composition in semantic spaces. Instead of expressing the compositional method as an algebraic operation, we will encode it as a program, which can be linear, nonlinear, or involve more intricate expressions. More remarkably, this program will be evolved from a set of initial random programs by means of genetic programming (GP). We show that our method is able to reproduce the same behavior as human-designed algebraic operators. Using a word analogy task as benchmark, we also show that GP-generated programs are able to obtain accuracy values above those produced by the commonly used human-designed rule for algebraic manipulation of word vectors. Finally, we show the robustness of our approach by executing the evolved programs on the word2vec GoogleNews vectors, learned over 3 billion running words, and assessing their accuracy in the same word analogy task.
Bias in the estimation of global luminosity functions

We discuss a bias present in the calculation of the global luminosity function (LF) which occurs when analysing faint galaxy samples. This effect exists because of the different spectral energy distributions of galaxies, which are in turn quantified by the k-corrections. We demonstrate that this bias occurs because not all galaxy types are visible in the same absolute magnitude range at a given redshift and it mainly arises at high redshift since it is related to large k-corrections. We use realistic simulations with observed LFs to investigate the amplitude of the bias. We also compare our results to the global LFs derived from Hubble Deep Field-North and -South (HDF) surveys. We conclude that, as expected, there is no bias in the global LF measured in the absolute magnitude range where all galaxy types are observable. Beyond this range the faint-end slope of the global LF can be over/under-estimated depending on the adopted LF estimator. The effect is larger when the reference filter in which the global LF is measured, is far from the rest-frame filter in which galaxies are selected. The fact that LF estimators are differently affected by this bias implies that the bias is minimal when the different LF estimators give measurements consistent with one another at the faint-end. For instance, we show that the estimators are discrepant in the same way both in the simulated and HDF LFs. This suggests that the HDF LFs are affected by the presently studied bias. The best solution to avoid this bias is to derive the global LF in the reference filter closest to the rest-frame selection filter.
The complexity of compacting hierarchically specified layouts of integrated circuits

In many CAD systems for VLSI design the specification of a layout is internally represented by a set of geometric constraints that take the form of linear inequalities between pairs of layout components. Some of the constraints may be explicitly stated by the circuit designer. Others are internally generated by the CAD system, using the design rules of the fabrication process. Layout compaction is then equivalent to finding a minimum area layout satisfying all constraints. We discuss the complexity of the constraint resolution problem arising in this context. Hereby we allow circuits to be specified hierarchically. The complexity of the constraint resolution is then measured in terms of the length of the hierarchical specification. We show the following results: 1. It is decidable in polynomial (cubic) time whether a given hierarchical layout specification yields a consistent set of geometric constraints. The size of minimum area layouts satisfying the constraints can also be determined in cubic time. 2. For every layout specification that is consistent a hierarchical description L of a minimum area layout can be computed in polynomial time in the length of L. 3. There is a consistent layout specification with the following property: No layout satisfying the constraints is concise, i.e., every hierarchical layout description consistent with the specification has a length which grows exponentially in the length of the specification. 4. We define a subclass of so-called well-formed layout specifications. Each well-formed specification has a concise layout, which can be hierarchically described in linear space. Such a layout can be found in polynomial time. However, it is in general not a minimum area layout. Indeed, there is a consistent well-formed specification all of whose minimum area layouts are inconcise,. i.e., need exponential space to be described.
Dietary and genetic effects on age-related loss of gene silencing reveal epigenetic plasticity of chromatin repression during aging

During aging, changes in chromatin state that alter gene transcription have been postulated to result in expression of genes that are normally silenced, leading to deleterious age-related effects on cellular physiology. Despite the prevalence of this hypothesis, it is primarily in yeast that loss of gene silencing with age has been well documented. We use a novel position effect variegation (PEV) reporter in Drosophila melanogaster to show that age-related loss of repressive heterochromatin is associated with loss of gene silencing in metazoans and is affected by Sir2, as it is in yeast. The life span-extending intervention, calorie restriction (CR), delays the age-related loss of gene silencing, indicating that loss of gene silencing is a component of normal aging. Diet switch experiments show that such flies undergo a rapid change in their level of gene silencing, demonstrating the epigenetic plasticity of chromatin during aging and highlighting the potential role of diet and metabolism in chromatin maintenance, Thus, diet and related interventions may be of therapeutic importance for age-related diseases, such as cancer.
Mining negative sequential patterns

Sequential pattern mining is to discover all frequent sequences from a sequence database and has been an important issue in data mining. A lot of methods have been proposed for mining sequential pattern. However, conventional methods consider only the occurrences of itemsets in a sequence database, and the sequential patterns are referred to as positive sequential patterns. In practice, the absence of a frequent itemset in a sequence may imply significant information. In this paper, we introduce negative sequential pattern concept in which the absence of an itemset in a sequence is also considered. The major difficulties of negative sequential pattern mining are that there may be huge amounts of the candidates of negative sequences and most of them are meaningless. We proposed an algorithm for mining negative sequential patterns (NSPM). Using NSPM, we prune a number of redundant candidates by applying apriori-principle, and extract meaningful negative sequences from a large number of frequent negative sequences using the interestingness measure.
Cell surface properties of B16 melanoma variants with differing metastatic potential.

Abstract Several cell surface properties of three B16 melanoma variant lines, which exhibit differing lung-colonizing capacities, have been examined. Equal numbers of cells from the B16-F10Lr and B16-F1 lines, injected i.v. into syngeneic mice, produced significantly fewer lung nodules than did cells of the B16-F10 line. These wide differences in biological behavior could not, however, be ascribed to major qualitative differences in the cell surface properties studied. The 3 cell lines displayed similar quantitative and qualitative patterns of exposed surface proteins. The quantity of radioactive labeling of the major sialoglycoprotein (78,000 daltons) was inversely proportional to the capacity of cells to produce lung tumor colonies. Lectin-binding assays revealed that B16-F10Lr cells bound 50% less concanavalin A than did the B16-F1 or B16-F10 cells; the B16-F10 cells bound 40% less wheat germ agglutinin than did the B16-F1 or B16-F10Lr cells. Levels of 5′-nucleotidase activity were lower in B16-F10 cells than in B16-F1 and B16-F10Lr cells. At the same time, there was no reduction in levels of the cytoplasm-associated enzyme, acid phosphatase. No differences in membrane lipid fluidity among the cell lines were detected by either fluorescent polarization or photobleaching techniques. The kinetics of adhesion of B16-F10Lr and B16-F10 to a variety of substrates were very similar. The present data suggest that wide differences in metastatic behavior of B16 melanoma cells need not be correlated with major qualitative changes in a single cell surface biochemical or morphological characteristic.
Identifying Keys to Success in Innovative Teaching: Student Engagement and Instructional Practices as Predictors of Student Learning in a Course Using a Team-Based Learning Approach

When implementing innovative teaching techniques, instructors often seek to gauge the success of their methods. Proposing one approach to assessing classroom innovation, this study examines the ability of students’ ratings of engagement and instructional practices to predict their learning in a cooperative (team-based) framework. After identifying the factor structures underlying measures of student engagement and instructional practices, these factors were used as predictors of self-reported student learning in a general chemistry course delivered using a team-based learning approach. Exploratory factor analyses showed a four-factor structure of engagement: teamwork involvement, investment in the learning process, feelings about team-based learning, level of academic challenge; and a three-factor structure of instructional practices: instructional guidance, fostering self-directed learning skills, and cognitive level. Multiple linear regression revealed that feelings about team-based learning and perceptions of instructional guidance had significant effects on learning, beyond other predictors, while controlling gender, GPA, class level, number of credit hours, whether students began college at their current institution, expected highest level of education, racial or ethnic identification, and parental level of education. These results yield insight into student perceptions about team-based learning, and how to measure learning in a team-based learning framework, with implications for how to evaluate innovative instructional methods.
Quantification of serum immunoglobulin in rainbow trout Salmo gairdneri under various environmental conditions

The concentration of serum immunoglobulin in different groups of rainbow trout Salrno gairdneri was measured by means of a single radial immuno&ffusion test. The normal IgM concentration was 3.3 mg ml-' in a group of free-living trout. Hypergamrnaglobulinaemia was found in PKDinfected fish and in fish from a trout farm with VHS and ERM, while the IgM concentration was low in sera from fish living under aquarium con&tions. Inhvidual variations were very pronounced. The purity of reference preparations and the specificity of antisera used were examined by crossed in~munoelectrophoresis.
Optical properties of SMC X-ray binaries

This work represent the first major study of the optical and IR characteristics of the mass donor companions to the X-ray pulsars in the Small Magellanic Cloud (SMC). In this work several new counterparts have been identified, and possible ones confirmed, as companions to X-ray pulsars in the SMC giving a total of 34 such objects now identified. In addition this work presents three new binary periods and confirms two X-ray periods using optical data for objects in this group. This homogeneous sample has been studied as a group to determine important general characteristics that may offer insight into the evolution of such systems. In particular, the spectral class distribution shows a much greater agreement with those of isolated Be stars, and appears to be in some disagreement with the galactic population of Be stars in Be/X-ray binaries. Studies of the long term optical modulation of the Be star companions reveal an extremely variable group of objects, a fact which will almost certainly make a major contribution to the pronounced X-ray variability. The spatial distribution of these systems within the SMC is investigated and strongly suggests a link between massive star formation and the HI density distribution. Finally, studies of the circumstellar disk characteristics reveal a strong link with optical variability offering important clues into the long-term stability of such disks.
Utilitarianism and Personal Faith

Personal religion has, in recent years, been conceptualized in terms of a dichotomy. That defined as Intrinsic and Committed serves as a master-motive for living. Its Extrinsic-Consensual counterpart has been treated as utilitarian, instrumental, and superficial. Utilizing measures designed to evaluate the latter in the framework of American cultural values, Extrinsic-Consensual faith was shown to associate with concern for money, prestige and materialistic goals. In contrast, Intrinsic-Committed religion appeared to counter these tendencies while stressing social-religious-humanistic themes.