Miracle-dz/UniFAR-FTUs huggingface dataset:
Bending space–time: a commentary on Dyson, Eddington and Davidson (1920) ‘A determination of the deflection of light by the Sun's gravitational field’

The famous eclipse expedition of 1919 to Sobral, Brazil, and the island of Principe, in the Gulf of Guinea, led by Dyson, Eddington and Davidson was a turning point in the history of relativity, not only because of its importance as a test of Einstein's General Theory of Relativity, but also because of the intense public interest which was aroused by the success of the expedition. The dramatic sequence of events which occurred is reviewed, as well as the long-term impact of its success. The gravitational bending of electromagnetic waves by massive bodies is a subject of the greatest importance for contemporary and future astronomy, astrophysics and cosmology. Examples of the potential impact of this key tool of modern observational astronomy are presented. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society.
Role of Neutralizing Antibodies in Protective Immunity Against HIV

HIV continues to be a major health problem world wide, however the situation is particularly serious in Asian and Sub-Saharan countries. Therefore, development of an effective HIV vaccine could help to reduce the severity of the disease and prevent infection. Over the last two decades significant efforts have been made towards inducing potent humoral and cellular immune responses by vaccination, however antibodies and CTL responses alone are likely not sufficient for inducing sterilizing immunity or long-term control of viral replication. Therefore, it is generally believed that both humoral and cellular responses will be needed for an effective HIV vaccine. In support of humoral immunity, monoclonal antibodies that recognize critical neutralizing epitopes have shown to be effective at passive transfer experiments in conferring protection against challenge infection. However, antibodies to similar epitope specificities are difficult to induce by vaccination. Therefore, optimization of Env structure is needed for exposing appropriate neutralizing epitopes and masking non-neutralizing epitopes. Since the crystal structure of the core of Env glycoprotein has been solved, efforts are in progress to design novel Env immunogens that may induce effective neutralizing responses. Furthermore, there are HIV-1 strains that are resistant to neutralization by monoclonal antibodies, yet neutralized by pooled sera from HIV-1 patients. Therefore, efforts should be made to identify these novel epitopes and to design strategies to incorporate them in potential vaccines. To facilitate comparative evaluation of vaccine immunogens for their ability to induce cross clade neutralizing antibodies, efforts should be made to use standardized neutralization assays and standard virus panels. Once potent HIV Env structure have been identified, their effectiveness may be enhanced through the use of adjuvants, delivery systems and prime and boost strategies to improve the quality and magnitude of neutralizing responses.
Energy-Aware Migration of Groups of Virtual Machines in Distributed Data Centers

This paper proposes the Topology-aware Virtual Machine Selection (TAVMS) algorithm to choose sets of communicating groups of virtual machines (VMs) to be migrated to other data centers, aiming at global energy savings. It considers the migration of groups of VMs as well as the data center network topology, selecting VM groups with network proximity in order to increase the potential number of equipments to be switched off. Results obtained show that relevant energy savings can be achieved by using the proposed algorithm in the allocation of servers to the migration of virtual machines in a distributed data center scenario.
Characterization of Commercially Available Vaginal Lubricants: A Safety Perspective

Vaginal lubricants are widely used by women to help solve intercourse difficulties or as enhancers, but recent reports raise questions about their safety. Twelve commercially available gel products were tested for pH value, pH buffering capacity, osmolality and cytotoxicity relevant to vaginal delivery. Obtained data were analyzed in light of the recent Advisory Note by the World Health Organization (WHO) for personal lubricants to be concomitantly used with condoms. Results showed that most products do not comply with pH and osmolality recommended standards, thus posing a potential hazard. Four products presented values of osmolality around three-times higher than the maximum acceptable limit of 1200 mOsm/kg. In vitro cell testing further identified substantial cytotoxicity even at 1:100 dilutions for three products, contrasting with no significant effect of up to at least a 1:5 dilution of a Universal Placebo gel. However, no direct correlation between these last results and pH or osmolality was found, thus suggesting that the individual toxicity of specific formulation components plays an important role in the outcome of a particular product. Although further assessment is required, these results highlight potential safety issues related to the formulation of commercially available vaginal lubricants.
Similarity between the Myxococcus xanthus and Stigmatella aurantiaca reverse transcriptase genes associated with multicopy, single-stranded DNA

To determine the evolutional relationship of bacterial retroelements of Myxococcus xanthus and Stigmatella aurantiaca, the nucleotide sequence of 3,060 bases encompassing msr, msd, and the upstream region of msd (downstream of msr) of S. aurantiaca DW4 was determined and compared with the same region from M. xanthus. An open reading frame was found 92 bases upstream of msd which encoded a polypeptide of 480 amino acid residues having 73% identity with the reverse transcriptase of M. xanthus. Together with high homologies in msr (86%) and msd (81%) regions, the present data indicate that the reverse transcriptase genes as well as the retrons of M. xanthus (retron-Mx162) and S. aurantiaca (retron-Sa163) were derived from a common progenitor retron which possibly before the two myxobacterial species diverged.
A Model of Learning by Incrernenfal Analogical Reasoning and

This paper presents a mode! of analogical reasoning for learning. The mode! is based on two main ideas. First, that reasoning from an analogy presented by a teacher while explaining an unfamiliar concept is often determined by the causal abstractions known by the student to apply in the familiar domain referred to. Secondly, that such analogies, once introduced, are extended incrementally, in attempts to ncrount, fcr new situations by recalling additional situations from the same base domain. Protocols suggest that this latter process is quite useful but extremely error-prone. CARL, a computer program that learns semantic representations for assignment statements of the BASIC programming langurrge is dcricribcd as an illustration this kind of analogical reasoning. The motlr! maps and debugs inferences drawn from several commonly used analogies to assignment, in response to prcsentct! examples. It has often been said among AT researchers that learning one new concept requires knowing an enormous amount beforchanc! In learning by ana! ogy this is particularly true. This pnper outlines an approach to learning by analogy showing one way that the organization of that knowledge can also be importnnt. In developing the model presented here, I concentrated particularly on how analogies presented by a teacher or text might be used by a student in forming an initial mode! of events in an unfamiliar domain. The model was motivated in part by observations derived from recorded protocols of the behavior of several students I tutored in introductory computer programming in the BASIC language. A number of models of analogical reasoning in -41 have been drvcloped around forms of partial pattern matching, under which objects in one domain are first associated with those in another, and ordered relations or frames with case slots of some kind are then placed in correspondence [Evans 08, Hrown 77, M’inston 80, Winston 821. These algorithms were based on the assumption that a best partial match could be found by first accumulating evidence for al! possible object-toobject mappings between two situations and then choosing the one that placed the largest number of attributes and relations in correspondence.
Assessing motivational interviewing via co-active life coaching on selected smoking cessation outcomes

Abstract The objective of this study was to assess the impact of Motivational Interviewing (MI)-via-Co-Active Life Coaching (CALC) on: smoking behaviours, personal competency as well as changes in perceptions of identity, smoking, quitting and the intervention itself among young adults (aged 19–25 years) in Canada. A mixed methods intent-to-treat approach was taken; the impact of 8–10 MI-via-CALC sessions on smoking behaviour and personal competency of 40 young adult smokers was examined through both questionnaires and individual interviews over 1 year. The immediate-intervention group received MI-via-CALC starting right after enrolment, whereas the waitlist-intervention group was placed on a waitlist for 3 months and then received the intervention. The immediate-intervention group decreased significantly from baseline to post-intervention in smoking behaviours, including the number of cigarettes smoked per day and cigarette dependency; and increased significantly in personal competency, including self-esteem and self-efficacy compared with the waitlist-intervention group. Moreover, 27.5% of participants after receiving the intervention were smoke-free at 12-month post-intervention follow-up. Additionally, qualitative themes pertaining to perceptions of identity, smoking, quitting and the intervention and their changes over time were described and were consistent with quantitative findings. Together, the high cessation rate for the entire study as well as the significant decreases in smoking behaviours and increases in personal competency of the intervention group compared with the waitlist group underscore the impact on behaviour change. MI-via-CALC offers a theoretically grounded, practical and efficacious cessation strategy for young adult smokers.
Evidence-based Decision Making: Enhancing Systematic Reviews of Program Evaluation Results in Europe

Over the last 25 years, meta-analysis has been widely used to study the effects of practical treatment interventions in fields ranging from psychology and education to medicine and public health. The present article first describes the impact of meta-analysis. The article then presents a description of some preliminary results of a study of the main design characteristics of published interventions in Europe. In order to foster both better experimental designs and more systematic reviews in the European context, and to promote collaboration between different countries and research groups, the authors then describe and discuss the Campbell Collaboration (C2), a new international organization aimed at fostering public policies and practices based on systematic reviews of high-quality evidence. Though there is some overlap between the work of the Campbell Collaboration and its sibling organization the Cochrane Collaboration, Campbell focuses more on systematic reviews in the social, behavioral and educational areas. Reviewers in those areas encounter difficulties over the use of non-randomized designs, difficulties in effect-size computation, and the need for new computer software to better serve the needs of meta-analytic reviews in the social sciences.
Effects of a 60 Hz Magnetic Field Exposure Up to 3000 μT on Human Brain Activation as Measured by Functional Magnetic Resonance Imaging

Several aspects of the human nervous system and associated motor and cognitive processes have been reported to be modulated by extremely low-frequency (ELF, < 300 Hz) time-varying Magnetic Fields (MF). Due do their worldwide prevalence; power-line frequencies (60 Hz in North America) are of particular interest. Despite intense research efforts over the last few decades, the potential effects of 60 Hz MF still need to be elucidated, and the underlying mechanisms to be understood. In this study, we have used functional Magnetic Resonance Imaging (fMRI) to characterize potential changes in functional brain activation following human exposure to a 60 Hz MF through motor and cognitive tasks. First, pilot results acquired in a first set of subjects (N=9) were used to demonstrate the technical feasibility of using fMRI to detect subtle changes in functional brain activation with 60 Hz MF exposure at 1800 μT. Second, a full study involving a larger cohort of subjects tested brain activation during 1) a finger tapping task (N=20), and 2) a mental rotation task (N=21); before and after a one-hour, 60 Hz, 3000 μT MF exposure. The results indicate significant changes in task-induced functional brain activation as a consequence of MF exposure. However, no impact on task performance was found. These results illustrate the potential of using fMRI to identify MF-induced changes in functional brain activation, suggesting that a one-hour 60 Hz, 3000 μT MF exposure can modulate activity in specific brain regions after the end of the exposure period (i.e., residual effects). We discuss the possibility that MF exposure at 60 Hz, 3000 μT may be capable of modulating cortical excitability via a modulation of synaptic plasticity processes.
Massive MIMO 1-Bit DAC Transmission: A Low-Complexity Symbol Scaling Approach

We study multi-user massive multiple-input single-output systems and focus on downlink transmission for PSK modulation, where the base station employs a large antenna array with low-cost 1-bit digital-to-analog converters (DACs). The direct combination of existing beamforming schemes with 1-bit DACs is shown to lead to an error floor at medium-to-high SNR regime, due to the coarse quantization of the DACs with limited precision. In this paper, based on the constructive interference, we consider both a quantized linear beamforming scheme where we analytically obtain the optimal beamforming matrix and a non-linear mapping scheme where we directly design the transmit signal vector. Due to the 1-bit quantization, the formulated optimization for the non-linear mapping scheme is shown to be non-convex. The non-convex constraints of the 1-bit DACs are first relaxed into convex, followed by an element-wise normalization to satisfy the 1-bit DAC transmission. We further propose a low-complexity symbol scaling scheme that consists of three stages, in which the quantized transmit signal on each antenna element is selected sequentially. Numerical results show that the proposed symbol scaling scheme achieves a comparable performance to the optimization-based non-linear mapping approach, while the corresponding performance-complexity tradeoff is more favorable for the proposed symbol scaling method.
Modeling Chromosome Maintenance as a Property of Cell Cycle in Saccharomyces cerevisiae

Defects in DNA repair, synthesis, and chromosome transmission can often cause chromosome instability, which are understood with respect to molecular-genetic mechanisms. However, transition from descriptive models to quantitative ones is generally difficult. Here we use a computationally intensive numerical technique based on linear programming to analyze the processes of chromosome maintenance during the cell cycle in yeast, Saccharomyces cerevisiae. We first experimentally identify 19 genes that when ectopically expressed cause chromosome instability. We then build an 18 x 19 matrix by assaying the genetic interactions of pairs of genes that each normally functions to maintain chromosomes, including the 19 genes discovered here. We then use a ”seriation” algorithm based on linear optimization to find an optimal arrangement of rows and columns to confirm an optimum temporal arrangement of gene influence during cell cycle phases. We experimentally demonstrate that the method yields new biological insights, which we test and validate.
Flexible Codebook Design for Limited Feedback Systems Via Sequential Smooth Optimization on the Grassmannian Manifold

Grassmannian quantization codebooks play a central role in a number of limited feedback schemes for single and multi-user multiple-input multiple-output (MIMO) communication systems. In practice, it is often desirable that these codebooks possess additional properties that facilitate their implementation, beyond the provision of good quantization performance. Although some good codebooks exist, their design tends to be a rather intricate task. The goal of this paper is to suggest a flexible approach to the design of Grassmannian codebooks based on sequential smooth optimization on the Grassmannian manifold and the use of smooth penalty functions to obtain additional desirable properties. As one example, the proposed approach is used to design rank-2 codebooks that have a nested structure and elements from a phase-shift keying (PSK) alphabet. In some numerical comparisons, codebooks designed using the proposed methods have larger minimum distances than some existing codebooks, and provide tangible performance gains when applied to a simple MIMO downlink scenario with zero-forcing beamforming, per-user unitary beamforming and rate control (PU 2RC), and block diagonalization signalling. Furthermore, the proposed approach yields codebooks that attain desirable additional properties without incurring a substantial degradation in performance.
A Memetic Algorithm for Selection of 3D Clustered Features with Applications in Neuroscience

We propose a Memetic algorithm for feature selection in volumetric data containing spatially distributed clusters of informative features, typically encountered in neuroscience applications. The proposed method complements a conventional genetic algorithm with a local search utilizing inherent spatial relationships to efficiently identify informative feature clusters across multiple regions of the search volume. First, we demonstrate the utility of the algorithm on simulated data containing informative feature clusters of varying contrast-to-noise-ratios. The Memetic algorithm identified a majority of the relevant features whereas a conventional genetic algorithm detected only a subset sufficient for fitness maximization. Second, we applied the algorithm to authentic functional magnetic resonance imaging (fMRI) brain activity data from a motor task study, where the Memetic algorithm identified expected brain regions and subsequent brain activity prediction in new individuals was accurate at an average of 76% correct classification. The proposed algorithm constitutes a novel method for efficient volumetric feature selection and is applicable in any 3D data scenario. In particular, the algorithm is a promising alternative for sensitive brain activity mapping and decoding.
A Scalable Hybrid Regular Expression Pattern Matcher

In this paper, the authors present a reconfigurable hardware architecture for searching for regular expression patterns in streaming data. This new architecture is created by combining two popular pattern matching techniques: a pipelined character grid architecture (Baker, 2004), and a regular expression NFA architecture (Cho, 2006). The resulting hybrid architecture can scale the number of input characters while still maintaining the ability to scan for regular expression patterns
Social Cognition in the Internet Age: Same As It Ever Was?

The World Wide Web has inarguably become an integral part of the daily lives of the majority of the world's population. Many people spend more time online than with any given person on any particular day, yet the cognitive impact of being online remains understudied in psychology. We examine the research that has been done, and relate other related research findings, in an effort to attract more research to this area. We analyze some of the key factors that may have an impact on what and how we learn online, whether we are interacting with the cloud mind interpreted by Google or with other people via text based communication. We investigate how this development changes our perception of reality and how we may evaluate online information in ways that differ from face-to-face encounters. Living our lives in cyberspace changes what kinds of information we most frequently process and how we habitually deploy our cognitive resources, for better and for worse. When people interact with the Internet they may adopt particular mind-sets, modulating basic psychological processes. We integrate disparate lines of research in an effort to provide avenues for future investigation.
RNA analysis of B cell lines arrested at defined stages of differentiation allows for an approximation of gene expression patterns during B cell development

The development of a mature B lymphocyte from a bone marrow stem cell is a highly ordered process involving stages with defined features and gene expression patterns. To obtain a deeper understanding of the molecular genetics of this process, we have performed RNA expression analysis of a set of mouse B lineage cell lines representing defined stages of B cell development using Affymetrix™ microarrays. The cells were grouped based on their previously defined phenotypic features, and a gene expression pattern for each group of cell lines was established. The data indicated that the cell lines representing a defined stage generally presented a high similarity in overall expression profiles. Numerous genes could be identified as expressed with a restricted pattern using dCHIP‐based, quantitative comparisons or presence/absence‐based, probabilistic state analysis. These experiments provide a model for gene expression during B cell development, and the correctly identified expression patterns of a number of control genes suggest that a series of cell lines can be useful tools in the elucidation of the molecular genetics of a complex differentiation process.
Linking Entities to a Knowledge Base with Query Expansion

In this paper we present a novel approach to entity linking based on a statistical language model-based information retrieval with query expansion. We use both local contexts and global world knowledge to expand query language models. We place a strong emphasis on named entities in the local contexts and explore a positional language model to weigh them differently based on their distances to the query. Our experiments on the TAC-KBP 2010 data show that incorporating such contextual information indeed aids in disambiguating the named entities and consistently improves the entity linking performance. Compared with the official results from KBP 2010 participants, our system shows competitive performance.