Miracle-dz/UniFAR-FTUs huggingface dataset:
Combination therapy of RY10-4 with the γ-secretase inhibitor DAPT shows promise in treating HER2-amplified breast cancer

RY10-4, a novel protoapigenone analog, shows potent cytotoxicity against human breast cancer cells. However, breast cancer cell lines overexpressing human epidermal growth factor receptor 2 (HER2), SKBR3 and BT474, showed less sensitivity to RY10-4 when compared to breast cancer cells lines expressing lower levels of HER2, such as MDA-MB-231 and MCF-7 cells. This was associated with aberrant hyperactivity in Notch signaling in cells treated with RY10-4, since treatment with RY10-4 causes an increase in Notch activity by 2-to3.5-fold in SKBR3 and BT474 cell lines. The increase in activity was abrogated with a γ-secretase inhibitor, DAPT, or with Notch1 small-interfering RNA (si-Notch1). Cell proliferation was inhibited more effectively by RY10-4 plus DAPT or si-Notch1 than either agent alone. RY10-4 plus DAPT increases apoptosis in both HER2-overexpressing cell lines by two-fold compared to RY10-4 alone, while DAPT alone has no significant effects on apoptosis. In addition, we previously found RY10-4 could inhibit tumor growth through the PI3K/AKT pathway. Here we report that the combination of RY10-4 and DAPT exhibit additive suppression on AKT phosphorylation, contributing to the anti-cancer effects. In an animal model, this combination therapy inhibits the growth of SKBR3 tumor xenografts in nude mice to a greater extent than treatment with either reagent alone. These results indicate that the aberrant activation of Notch signaling impedes the inhibitory effect of RY10-4 on HER2-amplified cell proliferation. Furthermore, these adverse effects can be prevented by treatment combining RY10-4 with a Notch pathway inhibitor.
Submodular maximization by simulated annealing

We consider the problem of maximizing a nonnegative (possibly non-monotone) submodular set function with or without constraints. Feige et al. [9] showed a 2/5-approximation for the unconstrained problem and also proved that no approximation better than 1/2 is possible in the value oracle model. Constant-factor approximation has been also known for submodular maximization subject to a matroid independence constraint (a factor of 0.309 [33]) and for submodular maximization subject to a matroid base constraint, provided that the fractional base packing number ν is bounded away from 1 (a 1/4-approximation assuming that ν ≥ 2 [33]). In this paper, we propose a new algorithm for submodular maximization which is based on the idea of simulated annealing. We prove that this algorithm achieves improved approximation for two problems: a 0.41-approximation for unconstrained submodular maximization, and a 0.325-approximation for submodular maximization subject to a matroid independence constraint. On the hardness side, we show that in the value oracle model it is impossible to achieve a 0.478-approximation for submodular maximization subject to a matroid independence constraint, or a 0.394-approximation subject to a matroid base constraint in matroids with two disjoint bases. Even for the special case of cardinality constraint, we prove it is impossible to achieve a 0.491-approximation. (Previously it was conceivable that a 1/2-approximation exists for these problems.) It is still an open question whether a 1/2-approximation is possible for unconstrained submodular maximization.
Effects of Semantic Context and Fundamental Frequency Contours on Mandarin Speech Recognition by Second Language Learners

Speech recognition by second language (L2) learners in optimal and suboptimal conditions has been examined extensively with English as the target language in most previous studies. This study extended existing experimental protocols (Wang et al., 2013) to investigate Mandarin speech recognition by Japanese learners of Mandarin at two different levels (elementary vs. intermediate) of proficiency. The overall results showed that in addition to L2 proficiency, semantic context, F0 contours, and listening condition all affected the recognition performance on the Mandarin sentences. However, the effects of semantic context and F0 contours on L2 speech recognition diverged to some extent. Specifically, there was significant modulation effect of listening condition on semantic context, indicating that L2 learners made use of semantic context less efficiently in the interfering background than in quiet. In contrast, no significant modulation effect of listening condition on F0 contours was found. Furthermore, there was significant interaction between semantic context and F0 contours, indicating that semantic context becomes more important for L2 speech recognition when F0 information is degraded. None of these effects were found to be modulated by L2 proficiency. The discrepancy in the effects of semantic context and F0 contours on L2 speech recognition in the interfering background might be related to differences in processing capacities required by the two types of information in adverse listening conditions.
NOVOMIR: De Novo Prediction of MicroRNA-Coding Regions in a Single Plant-Genome

MicroRNAs (miRNA) are small regulatory, noncoding RNA molecules that are transcribed as primary miRNAs (pri-miRNA) from eukaryotic genomes. At least in plants, their regulatory activity is mediated through base-pairing with protein-coding messenger RNAs (mRNA) followed by mRNA degradation or translation repression. We describe NOVOMIR, a program for the identification of miRNA genes in plant genomes. It uses a series of filter steps and a statistical model to discriminate a pre-miRNA from other RNAs and does rely neither on prior knowledge of a miRNA target nor on comparative genomics. The sensitivity and specificity of NOVOMIR for detection of premiRNAs from Arabidopsis thaliana is ~0.83 and ~0.99, respectively. Plant pre-miRNAs are more heterogeneous with respect to size and structure than animal pre-miRNAs. Despite these difficulties, NOVOMIR is well suited to perform searches for pre-miRNAs on a genomic scale. NOVOMIR is written in Perl and relies on two additional, free programs for prediction of RNA secondary structure (RNALFOLD, RNASHAPES).
Challenges and opportunities for whole‐genome sequencing–based surveillance of antibiotic resistance

Infections caused by drug‐resistant bacteria are increasingly reported across the planet, and drug‐resistant bacteria are recognized to be a major threat to public health and modern medicine. In this review, we discuss how whole‐genome sequencing (WGS)–based approaches can contribute to the surveillance of the emergence and spread of antibiotic resistance. We outline the characteristics of sequencing technologies that are currently most used for WGS (Illumina short‐read technologies and the long‐read sequencing platforms developed by Pacific Biosciences and Oxford Nanopore). The challenges posed by the analysis of sequencing data sets for antimicrobial‐resistance determinants and the solutions offered by modern bioinformatics tools are discussed. Finally, we illustrate the power of WGS‐based surveillance of antimicrobial resistance by summarizing recent studies on the spread of the multidrug‐resistant opportunistic pathogen Klebsiella pneumoniae and the transferable colistin‐resistance gene mcr‐1, in which high‐throughput WGS analyses played essential roles. The implementation of WGS for surveillance of antibiotic‐resistant bacteria is technically feasible and cost effective and provides actionable results with reference to infection control. Consequently, the time has come for laboratories to implement routine genome sequencing as part of their surveillance programs for antibiotic‐resistant bacteria.
Robust Discriminative Clustering with Sparse Regularizers

Clustering high-dimensional data often requires some form of dimensionality reduction, where clustered variables are separated from "noise-looking" variables. We cast this problem as finding a low-dimensional projection of the data which is well-clustered. This yields a one-dimensional projection in the simplest situation with two clusters, and extends naturally to a multi-label scenario for more than two clusters. In this paper, (a) we first show that this joint clustering and dimension reduction formulation is equivalent to previously proposed discriminative clustering frameworks, thus leading to convex relaxations of the problem, (b) we propose a novel sparse extension, which is still cast as a convex relaxation and allows estimation in higher dimensions, (c) we propose a natural extension for the multi-label scenario, (d) we provide a new theoretical analysis of the performance of these formulations with a simple probabilistic model, leading to scalings over the form $d=O(\sqrt{n})$ for the affine invariant case and $d=O(n)$ for the sparse case, where $n$ is the number of examples and $d$ the ambient dimension, and finally, (e) we propose an efficient iterative algorithm with running-time complexity proportional to $O(nd^2)$, improving on earlier algorithms which had quadratic complexity in the number of examples.
SORPTION OF FERROUS AND FERRIC IRON BY EXTRACELLULAR POLYMERIC SUBSTANCES (EPS) FROM ACIDOPHILIC BACTERIA

The sorption of Fe(II) and Fe(III) by extracellular polymeric substances (EPS) of acidophilic bacteria Acidiphilium 3.2Sup(5) and Acidithiobacillus ferrooxidans, harvested from the ecosystem of the Tinto River (Huelva, Spain), was investigated. EPS from mixed cultures of both bacteria (EPSmixed) and pure cultures of A. 3.2Sup(5) (EPSpure) were extracted with ethylenediamine tetraacetic acid (EDTA) and were characterized by Fourier-transform infrared (FTIR), electron photoemission (XPS), x-ray diffraction (DRX), and energy dispersive x-ray (EDX) spectroscopy and scanning electron microscopy (SEM). EPS pure were loaded, in sorption tests, with Fe(II) and Fe(III). The results obtained indicate that the biochemical composition and structure of EPSmixed was very similar to that of EPSpure. Besides, results indicate that EPSmixed adsorbed Fe(II) and Fe(III) by preferential interaction with the carboxyl group, which favored the formation of Fe(II)/Fe(III) oxalates. These species were also formed in EPSpure loaded with Fe(II)/Fe(III). All this behavior suggested that the sorption of iron by EPSmixed was similar to sorption of EPSpure, which fitted the Freundlich model. Thus, the iron uptake of EPSmixed reached 516.7 ± 23.4 mg Fe/g-EPS at an initial concentration of 2.0 g/L of Fetotal and Fe(II)/Fe(III) ratio of 1.0.
Original research article Comparison of prospective daily diaries and retrospective recall to measure oral contraceptive adherence

Background: The purpose of this study was to determine if retrospective recall of oral contraceptive (OC) adherence provides data that are similar to data collected via daily diaries over the same time period. Factors associated with inconsistent agreement between prospective and retrospective measurements of adherence also were explored. Study Design: A total of 185 women participated in a longitudinal, prospective cohort of OC users, and 113 of these women provided complete information on OC adherence during follow-ups. Concordance beyond chance was assessed using weighted kappa statistics, and logistic regression was used to identify factors associated with inconsistent reporting of adherence. Results: There was substantial agreement between prospective and retrospective adherence information (weighted kappa=0.64; 95% CI: 0.52–0.77). Participants with a high school education or less and those who had problems with feeling sad while using OCs had increased odds of inconsistent reporting of adherence (OR=4.38, 95% CI: 1.41–13.61 and OR=3.52, 95% CI: 1.25–9.94, respectively). Conclusion: While prospective data collection via diaries may improve accuracy, the added expense and burden on study participants may not be necessary. However, the use of retrospective recall may not be appropriate for all study populations.
A Framework Proposal to Assess the LARG Index of a Supply Chain in a Fuzzy Context

Bearing in mind the new Supply Chain Management (SCM) paradigms, it is important that supply chains be aware of the implementation level of the main practices associated to each SCM paradigm (Lean, Agile, Resilient, and Green, hereafter referred as LARG). The main objective of this chapter is to propose a framework, based on Enterprise 2.0 approach, for global supply chains to assess their LARG index in order to evaluate the leanness, agility, resilience, and greenness of their practices. Enterprise 2.0 technologies and Fuzzy Logic techniques are used as enablers to the proposed LARG evaluation model in the following assessment tasks: 1) determination of an adequate set of Lean, Agile, Resilient, and Green practices; 2) consensual definition of the relative weights of the considered practices; 3) adjustment of the evaluation policy to the particular supply chain; and 4) effective follow-up of the assessment results.
GPT Meets PSR

We present a case study in confronting the GPT general-purpose planner with the challenging power supply restoration (PSR) benchmark for contingent planning. PSR is derived from a real-world problem, and the difficulty of modeling and solving it contrasts with that of the purely artificial benchmarks commonly used in the literature. This confrontation leads us to improve general techniques for contingent planning, to provide a PDDL-syle encoding of PSR which we hope to see used in planning competitions, and to report the first results on generating optimal policies for PSR.
Impact of Dynamic Loading on the Implant-abutment Interface Using a Gas-enhanced Permeation Test In Vitro

Purpose : To assess implant leakage under static conditions as well as during and after dynamic loading. Materials and methods : Implants (Astra Tech (A), Biomet 3i (B) and Nobel Biocare (C)) were evaluated for leakage (n=8/group). Testing to assess the gas pressure change over time (hPa/min) and infiltrated fluid volume, was performed in a Gas Enhanced Permeation Test (GEPT) to qualify embedding. Implant apexes were then drilled, abutments were mounted and resin build-ups were fabricated. GEPT was reassessed. Samples were afterward mounted in a computer-controlled masticator while tested to bacterial leakage, they were daily observed for turbidity. Samples were then reassessed using GEPT. Dunnett's and Fisher's exact tests were utilized to compare implant and to analyze bacterial leakage. Results : Significant differences in GEPT values were shown after loading (p=0.034). Leakage resistance was best for B when compared to C (p=0.023). Samples with higher GEPT values demonstrated earlier bacterial leakage, occurring after 1 or 2 days (A=4, B=0, C=6) and showing favorability for implant system B (p=0.009). Conclusion : Implants leaking under static conditions had increased potential for bacterial leakage under dynamic conditions. As strongly correlating to sophisticated analytical methods, GEPT is a promising technique for assessing the overall implant system leakage resistance.
Smoothed Quadratic Energies on Meshes

In this article, we study the regularization of quadratic energies that are integrated over discrete domains. This is a fairly general setting, often found in, but not limited to, geometry processing. The standard Tikhonov regularization is widely used such that, for instance, a low-pass filter enforces smoothness of the solution. This approach, however, is independent of the energy and the concrete problem, which leads to artifacts in various applications. Instead, we propose a regularization that enforces a low variation of the energy and is problem specific by construction. Essentially, this approach corresponds to minimization with respect to a different norm. Our construction is generic and can be plugged into any quadratic energy minimization, is simple to implement, and has no significant runtime overhead. We demonstrate this for a number of typical problems and discuss the expected benefits.
A Bayesian Mixed-Treatment Comparison Meta-analysis of Treatments for Alcohol Dependence and Implications for Planning Future Trials

Background. Several treatments for alcohol dependence have been tested in randomized controlled trials, giving rise to systematic reviews with a network of evidence structure, or mixed treatment comparisons (MTCs). Within the network, there are few direct comparisons of active treatments. Thus far, this network has not been adequately analyzed. For example, “indirect comparisons” between treatments (e.g., the comparison of treatments B:C obtained via estimates from A:B and A:C trials) have not been incorporated into estimates of treatment effects. This has implications for the planning of future randomized controlled trials. Methods. We applied recent developments in Bayesian MTC meta-analysis to analyze the network of evidence. Using these results, we proposed a methodology to inform, design, and power a hypothetical trial in the context of an updated meta-analysis for treatments that have been infrequently compared and therefore whose effect sizes are not well informed by a meta-analysis. Results. An MTC meta-analysis provides more accurate estimates than a pairwise meta-analysis and uncovers decisive differences between active treatments that have been infrequently directly compared. Weighting across all outcomes indicates that a combination (naltrexone + acamprosate) treatment has the highest posterior probability of being the “best” treatment. If a new clinical trial were to be conducted of a combination therapy versus acamprosate alone, there is no feasible sample size that would result in a decisive meta-analysis. Conclusions. An MTC meta-analysis should be used to estimate treatment effects in networks in which direct and indirect evidence are consistent and to inform the design of future studies.
Compressed quantitative acoustic microscopy

Scanning acoustic microscopy is a well-accepted modality for forming quantitative 2D maps of acoustic properties of soft tissues at microscopic scales. In our studies, the sample is raster-scanned with a spatial step size of 2 μm using a 250 MHz transducer resulting in 3D RF data cubes. Each RF signal is processed to obtain, for each spatial location, acoustic parameters, e.g., the speed of sound. The scanning time is directly dependent on the sample size and can range from few minutes to hours. In order to maintain constant experimental conditions for the sensitive thin sectioned samples, the scanning time is an important practical issue. Hence, the main objective of this work is to reduce the scanning time by reconstructing acoustic microscopy images from spatially under sampled measurements, based on the theory of compressive sampling. A recently proposed approximate message passing method using a Cauchy maximum a posteriori image denoising algorithm is thus employed to account for the non-Gaussianity of quantitative acoustic microscopy wavelet coefficients.
APPLICABILITY OF AN AGENT-BASED MODELING CONCEPT TO MODELING OF TRANSPORTATION PHENOMENA

Today's transportation problems are found in the complex interactions of social, financial, economic, political, and engineering issues. The traditional approach to analyzing transportation problems has been the top-down approach, in which a set of overall objectives is defined and specific parts are fitted in the overall scheme. The effectiveness of this analysis process has been challenged when many issues need to be addressed at once and the individual parts participants to decisions have greater autonomy. A factor contributing to this phenomenon is the greater opportunity and power for individual parts to communicate and to interact with one another. As a result, it has become increasingly difficult to predict or control the overall performance of a large system, or to diagnose particular phenomena. In the past decade, the concept of agent-based modeling has been developed and applied to problems that exhibit a complex behavioral pattern. This modeling approach considers that each part acts on the basis of its local knowledge and cooperates and/or competes with other parts. Through the aggregation of the individual interactions, the overall image of the system emerges. This approach is called the bottom-up approach. This paper examines the link between today's transportation problems and agent-based modeling, presents the framework of agent based modeling, notes recently used examples applied to transportation, and discusses limitations. The intent of this paper is to explore a new avenue for the direction of modeling and analysis of increasingly complex transportation systems.
Environmental and Cultural Implications of Visitor Access in the Kimberley Region, Australia

Abstract The Kimberley coast in Australia's far north-west is the traditional country and home of a number of Indigenous groups and hosts some of the country's richest cultural heritage, most spectacular rock art, scenery and wildlife, making it an attractive tourism destination. A growing expedition cruise industry provides the main means of visitor access to remote coastal sites and offers excursions to shore-based attractions in what are mostly Aboriginal Reserve lands. In light of concerns about environmental and cultural site impacts resulting from increasing visitor numbers, this study examined biophysical site impacts along access trails to shore-based attractions and used qualitative methods to ascertain cultural impacts. The synthesis of the findings highlights that cultural concerns arising from visitor access without having sought traditional owner consent for such access, combined with a lack of traditional owner involvement in the planning, management or running of visitor activities, overshadow currently low environmental impacts of onshore expedition cruise activities. To overcome the continuing impasse regarding the issue of unsanctioned visitor access, the Kimberley urgently needs a coordinated approach by key stakeholders and the traditional owners which recognises and acknowledges the historical context. Such a process would facilitate tourism activities to become culturally sustainable.
Politics and Policymaking in Education: Explorations in Policy Sociology

List of Figures. Preface. Introduction. 1 Policy Matters! 2 Discipline and Chaos: the New Right and Discourses of Derision 3 The New Right and Education Policy 4 Industrial Training or New Vocationalism? Structures and Discourses 5 Towards the Post-Fordist School? 6 Curriculum plc: the ERA, policy, partnerships and the school curriculum 7 Colouring in the boxes: the struggles over a National Curriculum 8 Endnote. Appendix 1 List of Acronyms and Abbreviations. Appendix 2 List of Interviewees and Comment on Interviews. References. Index.
How to...write and analyse a questionnaire.

Questionnaires are used in a wide range of settings to gather information about the opinions and behaviour of individuals. As with any other branch of science, the validity and reliability of the measurement tool, i.e. the questionnaire, needs to be rigorously tested to ensure that the data collected is meaningful. The design and method of administration of a questionnaire will also influence the response rate that is achieved and the quality of data that is collected. This paper discusses the issues that should be considered when designing and undertaking a questionnaire study.
Erim Report Series Research in Management Strategies, Uncertainty and Performance of Small Business Startups Bibliographic Data and Classifications

Personal strategies of owners/founders of small business startups are related to performance and to environmental uncertainty. This is done using a longitudinal data set of some 50 Dutch startups. The results suggest a dynamic process between strategy and performance. A discrimination is made between four strategies (reactive, critical point, complete planning and opportunistic). The role of uncertainty is discussed. The dynamic process is embedded in the PERSUADE model.