Miracle-dz/UniFAR-FTUs huggingface dataset:
Directed self-assembly of microscale hydrogels by electrostatic interaction

The unique benefit of electrostatic self-assembly of microscale components in solution is demonstrated for the first time. In particular, positive and negative treatment of poly(ethylene glycol) (PEG) facilitates a novel bottom-up assembly approach using electrostatic interaction from microgels with opposite charges. Fundamental investigations of electrostatic interaction of microgels reveal that the contact area of microgels determines the total energy of construct and thus the final patterns. The electrostatic self-assembly approach enables the fabrication of large and complex biological related structures (e.g., multi-layer spheroid) with accurate control. By the design of the microgels, the thickness and number of microgels in each layer can be controlled. Biological investigations of positive and negative treatments of PEG further prove the possibility of using this approach in tissue engineering, regenerative medicine and drug delivery.
Asset-Based Civics for, With, and by Immigrant Students: Three Sites of Enriched Teaching and Learning for Immigrant and Native-Born Students

Abstract In this qualitative collective case study with 6 high school civics teachers, I found that using an asset-based approach to teaching civics for, with, and by immigrant students enriched teaching and learning for immigrant and native-born students, although participants missed some opportunities for deeper exploration. I used a combined theoretical framework of additive acculturation, civic education, and codetermination, and nested this study in immigrant civic education and asset-based literature. Data revealed 3 “sites” of enriched civics teaching and learning when teachers employed an asset-based approach: adding comparative and international perspectives, initiating critical civic discourse, and challenging native-born students’ assumptions.
Usual voice quality features and glottal features for emotional valence detection

We focus in this paper on the detection of emotions collected in real-life context. In order to improve our emotional valence detection system, we have tested new voice quality features that are mainly used for speech synthesis or voice transformation: the relaxation coefficient (Rd) and the functions of phase distortion (FPD); but also usual voice quality features. Distributions of voice quality features across speakers, gender, age and emotions are shown over the IDV-HR ecological corpus. Our results conclude that glottal and usual voice quality features are of interest for emotional valence detection even facing diverse kind of voices in ecological situations.
GRAPHICAL MODEL REPRESENTATIONS OF WORD LATTICES

We introduce a method for expressing word lattices within a dynamic graphical model. We describe a variety of choices for doing this, including a technique to relax the time information associated with lattice nodes in a way that trades off hypothesis expansion with presumed segmentation boundary accuracy. Our approach uses a set of time-inhomogeneous and algorithmically expressed conditional probability tables to encode the lattice. The approach was implemented as part of the graphical model toolkit, and word error rate improvements on the Switchboard corpus indicate that our technique is a viable means to incorporate large state space speech recognition systems into a graphical model.
Antiproliferative Mechanisms of the Flavonoids 2,2′-Dihydroxychalcone and Fisetin in Human Prostate Cancer Cells

We have previously demonstrated the antiproliferative effect of two flavonoids—2,2′-dihydroxychalcone (DHC), a novel synthetic flavonoid, and fisetin, a naturally occurring flavonol—in prostate cancer cells. In this study, we further examine the mechanisms of these compounds on survival and proliferation pathways. DHC and fisetin (1–50 μM) caused a dose-dependent reduction in viability, a concomitant increase in apoptosis in PC3 cells at 72 h, and a decrease in clonogenic survival at 24 h treatment. DHC was considerably more potent than fisetin in these cytotoxicity assays. The mechanism of accelerated cellular senescence was not activated by either compound in PC3 or lymph node carcinoma of the prostate (LNCaP) cells. Gene expression alterations in PC3 and LNCaP cells treated with 15 μM DHC and 25 μM fisetin for 6 to 24 h were determined by oligonucleotide array. Amongst the most highly represented functional categories of genes altered by both compounds was the cell cycle category. In total, 100 cell cycle genes were altered by DHC and fisetin including 27 genes with key functions in G2/M phase that were downregulated by both compounds. Other functional categories altered included chromosome organization, apoptosis, and stress response. These results demonstrate the multiple mechanisms of antitumor activity of DHC and fisetin in prostate cancer cells in vitro.
A Parallel and Modular Pattern Classification Framework for Large-Scale Problems

The number of samples that are available on the internet to train pattern classifiers is increasing rapidly, while traditional pattern classification techniques based on a single computer system are powerless to process these large-scale data sets. This chapter presents a parallel and modular pattern classification framework for coping with large-scale pattern classification problems. The proposed framework follows a divide-andconquer strategy that easily assigns a given large-scale problem to an available parallel and distributed computing infrastructure. The framework consists of three independent parts: decomposing training data sets, training component classifiers in a parallel way, and combining trained component classifiers. In order to evaluate the performance of the proposed framework, we perform experiments on a large-scale Japanese patent classification problem, containing about 3,500,000 patent documents. The experimental results show that our framework has the following attractive features: (a) The framework is general, and therefore any traditional pattern classification techniques such as support vector machines can be easily embedded in the framework as component classifiers. (b) The framework can incorporate explicit domain or prior knowledge into learning through the process of dividing training data sets. (c) The framework has good scalability and is easily implementable in hardware.
Lessons in implementing infection prevention

This paper has been developed from a conference presentation given by Professor Alison Holmes at the IPS Learning Labs launch event (2015). In it the implementation of research into clinical practice is discussed with reference to the upcoming Health Foundation Spotlight Report. The difficulties of engaging those in clinical practice are discussed with the importance of involvement of clinical leaders being highlighted. The importance of recognising that implementation science as a social process to bring credibility and legitimacy is also stressed. Following this, the Spotlight Report that is focused on strengthening implementation in the UK is discussed. There remains considerable scope for improvement and the impact of surveillance, targets and fatigue are considered. The tension between top–down and bottom–up approaches to implementation are discussed and a recommendation for a blended approach when implementing measures that are the components of an organisational infection prevention and control strategy is proposed. There also needs to be more scrutiny of the reasons for the failure of research implementation through an examination of the ‘soft periphery’ that comprises the organisational structure, systems and people that will be responsible for implementing and sustaining an intervention.
On Optimal Budget-Driven Scheduling Algorithms for MapReduce Jobs in the Heterogeneous Cloud

In this paper, we consider task-level scheduling algorithms with res-pect to budget and deadline constraint s for a bag of MapReduce jobs on a set of provisioned heterogeneous (virtual) machines in cloud platforms. Heterogeneity is manifested in the ”pay-as-you-go” charging model we use, where service machines with different performance have different service rates. We organize the bag of jobs as aκ-stage workflow and achieve, for specific optimization goals, the following results. First, given a total monetary budget Bj for a particular stage j, we propose a greedy algorithm for distributing the budget, with minimal stage execution timeas our goal. Based on the structure of this problem, we further prove the optimality of our algorithm in terms of the budget used and the execution time achieved. We then combine this algorithm with dynamic programming techniques to propose an optimal scheduling algorithm that obtains a minimum scheduling length inO(κB). The algorithm is efficient if the total budget B is polynomially bounded by the number of tasks in the MapReduce jobs, which is usually the case in practice. Second, we consider the dual of this optimization problem to minimize the cost when the (time) deadline of the computatio n D is fixed. We convert this problem into the standard multiplechoice knapsack problem via a parallel transformation. Our empirical studies verify the proposed optimal algorithms. Keywords-Heterogeneous Clouds, MapReduce optimization, optimal Hadoop scheduling algorithm, budget constraints
Career Satisfaction among Dual-Career Administrators

This study, based on responses from 69 dual-career college and university administrators, examined the relationship between perceived career satisfaction and (a) career salience, (b) career demand, and (c) use of eight role-management strategies. Analysis showed that career salience, career demand, and use of the strategy of organization jointly explained 39% of the variance in career satisfaction.
Training Young Activists

This article examines how nonprofit activist youth groups shape the civic and political trajectories of their adolescent members. Based on analyses of survey and semi-structured interview data gathered from low-income, racially diverse, and immigrant alumni members of grassroots youth organizing groups and from a comparison sample, findings suggest that adolescent activist groups foster high levels of civic and political participation in early adulthood. Similar to other public-oriented volunteer associations—such as student government—activist groups impart civic skills and experiences that facilitate later involvement. Yet activist groups may function as particularly intensive training grounds for future participation by developing members’ political consciousness and engaging them in political processes. In spite of operating within a neoliberal context that sometimes inhibits the political activity of nonprofits, contemporary grassroots youth organizing groups, somewhat like the 1960s’ civil rights groups decades earlier, can propel some young people toward ongoing engagement with social movements.
Regularization of Diffusion-Based Direction Maps for the Tracking of Brain White Matter Fascicles

Magnetic resonance diffusion tensor imaging (DTI) provides information about fiber local directions in brain white matter. This paper addresses inference of the connectivity induced by fascicles made up of numerous fibers from such diffusion data. The usual fascicle tracking idea, which consists of following locally the direction of highest diffusion, is prone to erroneous forks because of problems induced by fiber crossing. In this paper, this difficulty is partly overcomed by the use of a priori knowledge of the low curvature of most of the fascicles. This knowledge is embedded in a model of the bending energy of a spaghetti plate representation of the white matter used to compute a regularized fascicle direction map. A new tracking algorithm is then proposed to highlight putative fascicle trajectories from this direction map. This algorithm takes into account potential fan shaped junctions between fascicles. A study of the tracking behavior according to the influence given to the a priori knowledge is proposed and concrete tracking results obtained with in vivo human brain data are illustrated. These results include putative trajectories of some pyramidal, commissural, and various association fibers.
Overmodulation control of five-phase inverters with full DC-bus voltage utilization

The paper presents novel strategy of synchronous control of five-phase inverters in the zone of overmodulation. New time-domain-based approach for analysis and synthesis of algorithms of synchronized pulsewidth modulation (PWM) allows providing smooth three-stage transition from a linear modulation region to the ten-step control mode of five-phase systems with space-vector modulation. Simulations give the behavior of five-phase inverters with synchronized PWM during overmodulation. The spectra of the phase-to-neutral voltage of five-phase power conversion systems with algorithms of synchronized PWM do not contain even harmonics and sub-harmonics in the zone of overmodulation, which is especially important for the high power/high current applications.
Encore: 3D Printed Augmentation of Everyday Objects with Printed-Over, Affixed and Interlocked Attachments

One powerful aspect of 3D printing is its ability to extend, repair, or more generally modify everyday objects. However, nearly all existing work implicitly assumes that whole objects are to be printed from scratch. Designing objects as extensions or enhancements of existing ones is a laborious process in most of today's 3D authoring tools. This paper presents a framework for 3D printing to augment existing objects that covers a wide range of attachment options. We illustrate the framework through three exemplar attachment techniques -- print-over, print-to-affix and print-through, implemented in Encore, a design tool that supports a set of analysis metrics relating to viability, durability and usability that are visualized for the user to explore design options and tradeoffs. Encore also generates 3D models for production, addressing issues such as support jigs and contact geometry between the attached part and the original object. Our validation helps to illustrate the strengths and weaknesses of each technique. For example, print-over is stronger than print-to-affix with adhesives, and all the techniques' strengths are affected by surface curvature.
Treatment of childhood and adolescent depression with mianserin

The efficacy of mianserin in treating adult depression is now well established. Since there are no publications concerning the use of mianserin in children, the authors set up an open pilot study of 110 depressed children and adolescents aged 8–19 years. The average dose of mianserin was 1 mg/kg/day. Efficacy of treatment was noticeable by the end of the first week and was maintained throughout the 60 day study period. Evaluation was based on both clinical observations and changes in scores obtained from 80 subjects. Side‐effects were minimal leading to temporary withdrawal of treatment in only seven cases. The profile of mianserin in children and adolescents is similar to that of adults. It is an antidepressant with an anxiolytic component, and has a regulating effect on sleep. In view of its efficacy, compliance, and the very low incidence of side‐effects, mianserin appears to be a useful treatment for depression in children and adolescents. The results of this open study justify the development of further controlled studies.
Effect of steroidal saponin from Yucca schidigera extract on ruminal microbes

The effects of steroidal saponins (SAP) isolated from Yucca schidigera extract on ruminal bacteria and fungi were investigated in pure culture studies. Prevotella bryantii, Ruminobacter amylophilus, Selenomonas ruminantium and Streptococcus bovis were cultured through ten 24‐h transfers in ruminal fluid medium containing 0 or 25 µg SAP ml−1 (measured as smilagenin equivalents). The four strains, each non‐exposed or pre‐exposed to SAP, were then inoculated into medium containing 0 or 250 µg smilagenin equivalents ml−1 and 24‐h growth curves were determined. The cellulolytic ruminal bacteria Ruminococcus flavefaciens, Fibrobacter succinogenes and Rc. albus were cultured for 72 h on Whatman no. 1 filter paper in medium containing 0, 9, 90 or 180 µg SAP ml−1 for the determination of filter paper digestion and endoglucanase activity. The ruminal bacteria differed in their responses to SAP. Steroidal saponins in the medium reduced the growth of Strep. bovis (P < 0·01 at 2, 3, 4, 5, 6 and 8 h), P. bryantii (P < 0·05 at 4, 5, 6, 8, 10 and 24 h) and Rb. amylophilus (P < 0·05 at 14 and 24 h), but the growth of S. ruminantium was enhanced (P < 0·05) at 10, 14 and 24 h. The growth curves of all four non‐cellulolytic species were similar (P > 0·05) between pre‐exposed and non‐exposed cultures and the concentrations of total SAP and soluble (deglycosylated) SAP in the liquid fraction were unchanged (P > 0·05) over time. Steroidal saponins inhibited the digestion of filter paper by all three cellulolytic bacteria, but F. succinogenes was less (P < 0·05) sensitive to SAP and more (P < 0·05) effective at deglycosylating SAP than were Rc. flavefaciens or Rc. albus. Transmission electron microscopy revealed that SAP altered the cell walls of the SAP‐inhibited non‐cellulolytic bacteria. The ruminal fungi, Neocallimastix frontalis and Piromyces rhizinflata, were cultured on filter paper in medium containing 0, 0·45, 2·25 or 4·5 µg SAP ml−1. Filter paper digestion by both fungi was completely inhibited by 2·25 µg SAP ml−1. Steroidal saponins from Y. schidigera inhibit cellulolytic ruminal bacteria and fungi, but their effects on amylolytic bacteria are species dependent and similar to the effects of ionophores. As such, SAP may be useful in nutritional applications targeting starch‐digesting ruminal micro‐organisms.
Predicting Physiological Concentrations of Metabolites from Their Molecular Structure

Physiological concentrations of metabolites can partly be explained by their molecular structure. We hypothesize that substances containing certain chemical groups show increased or decreased concentration in cells. We consider here, as chemical groups, local atomic configurations, describing an atom, its bonds, and its direct neighbor atoms. To test our hypothesis, we fitted a linear statistical model that relates experimentally determined logarithmic concentrations to feature vectors containing count numbers of the chemical groups. In order to determine chemical groups that have a clear effect on the concentration, we use a regularized (lasso) regression. In a dataset on 41 substances of central metabolism in different organisms, we found that the physical concentrations are increased by the occurrence of amino and hydroxyl groups, while aldehydes, ketones, and phosphates show decreased concentrations. The model explains about 22% of the variance of the logarithmic mean concentrations.
Jointly Disambiguating and Clustering Concepts and Entities with Markov Logic

We present a novel approach for jointly disambiguating and clustering known and unknown concepts and entities with Markov Logic. Concept and entity disambiguation is the task of identifying the correct concept or entity in a knowledge base for a single- or multi-word noun (mention) given its context. Concept and entity clustering is the task of clustering mentions so that all mentions in one cluster refer to the same concept or entity. The proposed model (1) is global, i.e. a group of mentions in a text is disambiguated in one single step combining various global and local features, and (2) performs disambiguation, unknown concept and entity detection and clustering jointly. The disambiguation is performed with respect to Wikipedia. The model is trained once on Wikipedia articles and then applied to and evaluated on different data sets originating from news papers, audio transcripts and internet sources.
Three-dimensional linear articulatory modeling of tongue, lips and face, based on MRI and video images

In this study, previous articulatory midsagittal models of tongue and lips are extended to full three-dimensional models. The geometry of these vocal organs is measured on one subject uttering a corpus of sustained articulations in French. The 3D data are obtained from magnetic resonance imaging of the tongue, and from front and profile video images of the subject's face marked with small beads. The degrees of freedom of the articulators, i.e., the uncorrelated linear components needed to represent the 3D coordinates of these articulators, are extracted by linear component analysis from these data. In addition to a common jaw height parameter, the tongue is controlled by four parameters while the lips and face are also driven by four parameters. These parameters are for the most part extracted from the midsagittal contours, and are clearlyinterpretable in phonetic/biomechanical terms. This implies that most 3D features such as tongue groove or lateral channels can be controlled by articulatory parameters defined for the midsagittal model. Similarly, the 3D geometry of the lips is determined by parameters such as lip protrusion or aperture, that can be measured from a profile view of the face.
CAD of multi-resonator rectenna for micro-power generation

We introduce a compact, lightweight and highly efficient multi-resonator rectenna (rectifying antenna) designed to harvest the RF energy really obtainable in humanized environments. Such sources, radiated from cell phones, radio transmitters and Wi-Fi equipments, are ubiquitously available but have very low power densities, at different frequency bands, with unknown directions of incidence and polarization. In order to harvest a significant quantity of energy it is mandatory to put a very special care in the design of each part of the receiving/storing system. For this purpose a combination of resonant antennas, each one designed for a specific application-dependent frequency band, is optimised together with the rectifying circuit and the load. This is accomplished by a rigorous design tool, based on the concurrent use of nonlinear and electromagnetic CAD methods. Multi-source non linear simulation of the harvester in realistic operating conditions predicts a DC power of a few hundred μW, which represents the typical energy requirement of a sensor node.
The Concept and Measurement of the Quality of School Life

The Quality of School Life (QSL) is defined by three dimensions of student reactions: (1) satisfaction with school in general, (2) commitment to school work, and (3) attitudes toward teachers. A 27-item QSL scale is presented that shows reliability and validity across educational levels (elementary, middle and high school) based on 4,266 student survey responses. Concurrent and discriminative validity is demonstrated using measures of academic achievement, participation, personality, family background, and sociometric data from peers and teachers. Scaling techniques, factor analysis, and an extension of Sechrest’s test for incremental validity document the multi-dimensional design of the scale.