Miracle-dz/UniFAR-FTUs huggingface dataset:
Large-Scale Phylogenetic Classification of Fungal Chitin Synthases and Identification of a Putative Cell-Wall Metabolism Gene Cluster in Aspergillus Genomes

The cell wall is a protective and versatile structure distributed in all fungi. The component responsible for its rigidity is chitin, a product of chitin synthase (Chsp) enzymes. There are seven classes of chitin synthase genes (CHS) and the amount and type encoded in fungal genomes varies considerably from one species to another. Previous Chsp sequence analyses focused on their study as individual units, regardless of genomic context. The identification of blocks of conserved genes between genomes can provide important clues about the interactions and localization of chitin synthases. On the present study, we carried out an in silico search of all putative Chsp encoded in 54 full fungal genomes, encompassing 21 orders from five phyla. Phylogenetic studies of these Chsp were able to confidently classify 347 out of the 369 Chsp identified (94%). Patterns in the distribution of Chsp related to taxonomy were identified, the most prominent being related to the type of fungal growth. More importantly, a synteny analysis for genomic blocks centered on class IV Chsp (the most abundant and widely distributed Chsp class) identified a putative cell wall metabolism gene cluster in members of the genus Aspergillus, the first such association reported for any fungal genome.
Convexified Convolutional Neural Networks

We describe the class of convexified convolutional neural networks (CCNNs), which capture the parameter sharing of convolutional neural networks in a convex manner. By representing the nonlinear convolutional filters as vectors in a reproducing kernel Hilbert space, the CNN parameters can be represented as a low-rank matrix, which can be relaxed to obtain a convex optimization problem. For learning two-layer convolutional neural networks, we prove that the generalization error obtained by a convexified CNN converges to that of the best possible CNN. For learning deeper networks, we train CCNNs in a layer-wise manner. Empirically, CCNNs achieve performance competitive with CNNs trained by backpropagation, SVMs, fully-connected neural networks, stacked denoising auto-encoders, and other baseline methods.
Professional Development School Trade-Offs in Teacher Preparation and Renewal.

As a major component of the reform and restructuring movement in education, professional Judith Haymore development schools (PDSs) aim to provide new Sandholtz is director of models of teacher education and development (Dar the Comprehensive ling-Hammond, 1994). One of the most common Teacher Education collaborative arrangements for preparing prospec Institute, School of tive teachers (Yinger & Hendricks, 1990), profes Education, University of sional development schools have four main goals: to California, Riverside; maximize student learning, to support professional Shannon Husted Dadlez teaching practice, to enhance the professional educa just completed her Ph.D. tion of novice and veteran teachers, and to encourage at University of research and inquiry related to educational practice California, Riverside, and (Holmes Group, 1990; Levine, 1988, 1992). is a mentor teacher in the Extending beyond other school reform efforts, Riverside Unified School professional development schools offer promising District. possibilities in creating new frames for teacher learn
MicroRNA-124 enhances response to radiotherapy in human epidermal growth factor receptor 2-positive breast cancer cells by targeting signal transducer and activator of transcription 3

Aim To determine whether microRNA (miR)-124 enhances the response to radiotherapy in human epidermal growth factor receptor 2 (HER2)-positive breast cancer cells by targeting signal transducer and activator of transcription 3 (Stat3). Methods miR-29b expression was measured in 80 pairs of breast tumor samples and adjacent normal tissues collected between January 2013 and July 2014. Activity changes of 50 canonical signaling pathways upon miR-124 overexpression were determined using Cignal Signal Transduction Reporter Array. Target gene of miR-124 was determined using Targetscan and validated by Western blotting and dual-luciferase assay. Cell death rate was assessed by propidium iodide (PI)/ Annexin V staining followed by flow cytometry analysis. Stat3 and miR-124 expression was further measured in 10 relapsed (non-responder) and 10 recurrence-free HER2-positive breast cancer patients. Results MiR-124 expression was down-regulated in HER2 positive breast cancers compared with normal tissues, and was negatively associated with tumor size. MiR-124 overexpression in HER2 positive breast cancer cell line SKBR3 significantly reduced the activity of Stat3 signaling pathway compared with control transfection (P < 0.001). Bioinformatic prediction and function assay suggested that miR-124 directly targeted Stat3, which is a key regulator of HER2 expression. MiR-124 overexpression down-regulated Stat3 and potently enhanced cell death upon irradiation. Consistently, chemical inhibitor of Stat3 also sensitized HER2-positive breast cancer cells to irradiation. Moreover, increased Stat3 expression and reduced miR-124 expression were associated with a poor response to radiotherapy in HER2-positive breast cancers. Conclusions Weak miR-124 expression might enhance Stat3 expression and radiotherapy resistance in HER2-positive breast cancer cells.
Selected Revised Papers from the 4th International Workshop on Graph Computation Models

: Graph conditions are a means to express structural properties for graph transformation systems and graph programs in a large variety of application areas. With HR ∗ graph conditions, non-local graph properties like “there exists a path of arbitrary length” or “the graph is circle-free” can be expressed. We show, by induction over the structure of formulas and conditions, that (1) any node-counting monadic second-order formula can be expressed by an HR ∗ condition and (2) any HR ∗ condition can be expressed by a second-order graph formula.
SEMIPARAMETRIC MIXTURE OF BINOMIAL REGRESSION WITH A DEGENERATE COMPONENT

Many datasets contain a large number of zeros, and cannot be modeled directly using a single distribution. Motivated by rain data from a global climate model, we study a semiparametric mixture of binomial regressions, in which both the component proportions and the success probabilities depend on the predictors nonparametrically. An EM algorithm is proposed to estimate this semiparametric mixture model by maximizing the local likelihood function. We also consider a special case in which the component proportions are constant while the component success probabilities still depend on the predictors nonparametrically. This model is estimated by a one-step backfitting procedure, and the estimates are shown to achieve the optimal convergence rates. The asymptotic properties of the estimates for both models are established. The proposed procedures are applied to rain data from a global climate model and historical rain data from Edmonton, Canada. Simulation studies show that satisfactory estimates are obtained for the proposed models for finite samples.
City size and household food consumption: an application of the AIDS model to food demand elasticities in Spain

Empirical evidence on consumer behavior is of major importance in the formulation and analysis of economic policies. Changes in prices, income level, or decisions regarding taxes or other structural reforms that effect relative prices may produce very different effects depending on family income distribution or also across space. The aim of this paper is to estimate expenditure and own-price elasticities for ten aggregated food product groups using the Spanish Household Budget Survey for the year 2010. These products are the ones for which the survey provides information regarding prices and quantities, thus allowing the application of the Almost Ideal Demand System model (AIDS). This stimation procedure allows comparisons to be made not only among different levels of income, but also how relevant could be the place of residence characteristics. The results confirm that the size of the city in which the household resides has a similar significant and relevant effect on consumption patterns as family income level. This is especially clear with own-price elasticities. In Spain, large cities show a greater response to price changes tan small cities or rural areas.
Simulation of flood flow in a river system using artificial neural networks

Abstract. Artificial neural networks (ANNs) provide a quick and flexible means of developing flood flow simulation models. An important criterion for the wider applicability of the ANNs is the ability to generalise the events outside the range of training data sets. With respect to flood flow simulation, the ability to extrapolate beyond the range of calibrated data sets is of crucial importance. This study explores methods for improving generalisation of the ANNs using three different flood events data sets from the Neckar River in Germany. An ANN-based model is formulated to simulate flows at certain locations in the river reach, based on the flows at upstream locations. Network training data sets consist of time series of flows from observation stations. Simulated flows from a one-dimensional hydrodynamic numerical model are integrated for network training and validation, at a river section where no measurements are available. Network structures with different activation functions are considered for improving generalisation. The training algorithm involved backpropagation with the Levenberg-Marquardt approximation. The ability of the trained networks to extrapolate is assessed using flow data beyond the range of the training data sets. The results of this study indicate that the ANN in a suitable configuration can extend forecasting capability to a certain extent beyond the range of calibrated data sets.
The value of breast MRI in high‐risk patients with newly diagnosed breast cancer to exclude invasive disease in the contralateral prophylactic mastectomy: Is there a role to choose wisely patients for sentinel node biopsy?

The aim of this study was to evaluate the presence of clinically and mammographically occult disease using breast MRI in a cohort of cancer patients undergoing contralateral prophylactic mastectomy (CPM) and the utmost indication of axillary assessment (sentinel node biopsy (SLNB)) for this side. A retrospective review of patients with unilateral invasive breast cancer or ductal carcinoma in situ (DCIS) from institutional MRI registry data (2004–2010) was conducted. Characteristics of patients undergoing CPM with breast MRI obtained less than 6 month before surgery were evaluated. A total of 2322 consecutive patients diagnosed with DCIS or stage I to III infiltrating breast cancer underwent preoperative breast MRI. Of these, 1376 patients (59.2%) had contralateral clinical breast exam and mammography without abnormalities; and 116 patients (4.9%) underwent CPM (28 excluded patients had breast MRI more than 6 months before CPM). The mean age of the 88 patients was 49 years (range 28–76 years). Two (2.3%) DCIS identified on surgical pathology specimen were not depicted by MRI and the 5 mm T1N0 invasive cancer (1.1%) was identified on MRI. Preoperative MRI showed 95% accuracy to demonstrate absence of occult disease with negative predicted value (NPV) of 98% (95% CI: 91.64–99.64%). Occult disease was present in 3.4% of CPM. MRI accurately identified the case of invasive cancer in this cohort. The high negative predictive value suggests that MRI can be used to select patients without consideration of SLNB for the contralateral side.
A 490uW fully MICS compatible FSK transceiver for implantable devices

A low power fully MICS compatible FSK transceiver for implantable devices is implemented in 0.18um CMOS technology with 0.7V supply. The Q-enhancement LNA attenuates image and adjacent channels more than 30 and 13dB, respectively, eliminating the necessity of I/Q LO generation and poly-phase filter. The DCO replaces the frequency synthesizer to reduce the power consumption and to eliminate the XO. The 1mm2 fabricated transceiver consumes 490uW with a data rate of 250kb/s, corresponding to energy consumption of 1.96nJ/b.
Cultural belonging and peer relations among young people in multi-ethnic

abstract 314 Forum Cultural belonging and peer relations among young people in multi-ethnic Norwegian suburbs T OVE S TEEN -O LSEN Introduction A sense of collective identity an d the feeling of belonging maytake many forms. People may identify with other members ofa group but not feel that they belong in the sense of being ac-cepted, or they may feel that they are accepted and belong, butdo not fully identify with other members of the group (Anth-ias, 2006). Belonging is about emotional attachment and aboutfeeling safe and at home (Yuval-Davis, 2006). To belong is toshare values, practices, and social , symbolic, and material ties. Itis not merely a question of identification or ethnicity. In thissense, belonging is closely rela ted to shared experiences and tothe feeling of inclusion and exclusion. Studies have shown that children with an immigrant back-ground often strive hard to be accepted or included in peergroups of the majority culture (Fangen, 2009; Lappalainen,2006; Lindgren, 2010). Norwegian schools are not free fromsocial exclusion and bullying on the basis of racism (Fandrem,
Highly Sensitive In Vivo Imaging of Trypanosoma brucei Expressing “Red-Shifted” Luciferase

Background Human African trypanosomiasis is caused by infection with parasites of the Trypanosoma brucei species complex, and threatens over 70 million people in sub-Saharan Africa. Development of new drugs is hampered by the limitations of current rodent models, particularly for stage II infections, which occur once parasites have accessed the CNS. Bioluminescence imaging of pathogens expressing firefly luciferase (emission maximum 562 nm) has been adopted in a number of in vivo models of disease to monitor dissemination, drug-treatment and the role of immune responses. However, lack of sensitivity in detecting deep tissue bioluminescence at wavelengths below 600 nm has restricted the wide-spread use of in vivo imaging to investigate infections with T. brucei and other trypanosomatids. Methodology/Principal findings Here, we report a system that allows the detection of fewer than 100 bioluminescent T. brucei parasites in a murine model. As a reporter, we used a codon-optimised red-shifted Photinus pyralis luciferase (PpyRE9H) with a peak emission of 617 nm. Maximal expression was obtained following targeted integration of the gene, flanked by an upstream 5′-variant surface glycoprotein untranslated region (UTR) and a downstream 3′-tubulin UTR, into a T. brucei ribosomal DNA locus. Expression was stable in the absence of selective drug for at least 3 months and was not associated with detectable phenotypic changes. Parasite dissemination and drug efficacy could be monitored in real time, and brain infections were readily detectable. The level of sensitivity in vivo was significantly greater than achievable with a yellow firefly luciferase reporter. Conclusions/Significance The optimised bioluminescent reporter line described here will significantly enhance the application of in vivo imaging to study stage II African trypanosomiasis in murine models. The greatly increased sensitivity provides a new framework for investigating host-parasite relationships, particularly in the context of CNS infections. It should be ideally suited to drug evaluation programmes.
Body mass index and exon 19 mutation as factors predicting the therapeutic efficacy of gefitinib in patients with epidermal growth factor receptor mutation‐positive non‐small cell lung cancer

Many randomized clinical trials have demonstrated that epidermal growth factor receptor‐tyrosine kinase inhibitors (EGFR‐TKIs) are advantageous over standard chemotherapy, either as front‐line treatment or as further management of patients with EGFR mutation‐positive non‐small‐cell lung cancer (NSCLC). However, which subgroup of these patients could benefit more from EGFR‐TKIs needs to be further explored. In the present study, we explored the predictive factors in such cohorts of patients who received gefitinib.
Forms of ethical and intellectual development in the college years

Since its original publication in 1970, this landmark book byWilliam Perry has remained the cornerstone of much of the studentdevelopment research that followed. Using research conducted withHarvard undergraduates over a fifteen-year period, Perry derived anAnduring framework for characterizing student development--a schemeso accurate that it still informs and advances investigations intostudent development across gAnders and cultures.
Winds in Collision: high-energy particles in massive binary systems

High-resolution radio observations have revealed that non-thermal radio emission in WR stars arises where the stellar wind of the WR star collides with that of a binary companion. These colliding-wind binary (CWB) systems offer an important laboratory for investigating the underlying physics of particle acceleration. Hydrodynamic models of the binary stellar winds and the wind-collision region (WCR) that account for the evolution of the electron energy spectrum, largely due to inverse Compton cooling, are now available. Radiometry and imaging obtained with the VLA, MERLIN, EVN and VLBA provide essential constraints to these models. Models of the radio emission from WR146 and WR147 are shown, though these very wide systems do not have defined orbits and hence lack a number of important model parameters. Multi-epoch VLBI imaging of the archetype WR+O star binary WR140 through a part of its 7.9-year orbit has been used to define the orbit inclination, distance and the luminosity of the companion star to enable the best constraints for any radio emitting CWB system. Models of the spatial distribution of relativistic electrons and ions, and the magnetic energy density are used to model the radio emission, and also to predict the high energy emission at X-ray and gamma-ray energies. It is clear that high-energy facilities e.g. GLAST and VERITAS, will be important for constraining particle acceleration parameters such as the spectral index of the energy spectrum and the acceleration efficiency of both ions and electrons, and in turn, identify unique models for the radio spectra. This will be especially important in future attempts to model the spectra of WR140 throughout its complete orbit. A WCR origin for the synchrotron emission in O-stars, the progenitors of WR stars, is illustrated by observations of Cyg OB2 No. 9.
The spectrum effect in tests for risk prediction, screening, and diagnosis

The spectrum effect describes the variation between settings in performance of tests used to predict, screen for, and diagnose disease. In particular, the predictive use of a test may be different when it is applied in a general population rather than in the study sample in which it was first developed. This article discusses the impact of the spectrum effect on measures of test performance, and its implications for the development, evaluation, application, and implementation of such tests.
THE EFFECTS OF NEUROFEEDBACK TRAINING IN THE COGNITIVE DIVISION OF THE ANTERIOR CINGULATE GYRUS

This study examines the efficacy of neurofeedback training in the cognitive division of the anterior cingulate gyrus and describes its relationship with cortical regions known to be involved in executive functions. This study was conducted with eight non-clinical students, four male and four female, with a mean age of twenty-two. Learning occurred in the ACcd at significant levels over sessions and in the anterior regions that receive projections from the AC. There appears to be a multidimensional executive circuit that increases in the same frequency in apparent synchrony with the AC and it may be possible to train this sub-cortical region using LNFB.
Smoke Detection Based on Deep Convolutional Neural Networks

An effective smoke detection from visual scenes is crucial to avoid large scale fire around the world. But it is still challenging due to its large variations in color, texture and shapes. To improve smoke detection accuracy, a new approach based on deep convolutional neural networks is proposed which can be trained end to end from raw pixel values to classifier outputs and automatically extract features from images. Experiments show that this method achieves 99.4% detection rates with 0.44% false alarm rates on the large dataset which obviously outperforms existing traditional methods.
Renal function recovery after laparosocopic pyeloplasty

Introduction To observe the renal function recovery measured by diuretic renography in short and medium follow–up of patients with transperitoneal Anderson–Hynes laparoscopic pyeloplasty. Material and methods We performed a retrospective review from our series of laparoscopic pyeloplasties, and we applied the following selection criteria: 1) to have at least two MAG3 diuretic renography during the follow–up, performed with a gap of 4–6 months between them; 2) to have at least one year follow–up. Fulfilling these criteria, we have selected 35 patents of 62. Results During follow–up, statistically significant improvement comparing with the pre–surgical value has been observed in diuretic renography in the operated kidney in all selected patients during the time of follow up in terms of: functional uptake ratio (FUR), furosemide excretion and total excretion. No statistically significant differences were found in excretion time and spontaneous excretion parameters. By dividing patients in two age groups <40 years and >40 years we found no statistically significant differences between them in relation to the improvement of the FUR. Conclusions Laparoscopic pyeloplasty not only corrects the UPJO, it also may recover renal function demonstrated after one year follow up with diuretic renography. Laparoscopic pyeloplasty should be procedure of choice even in those patients with poor renal function at diagnosis, whenever there are chances of recovering renal function, regardless patients age.
Attitude Adaptation in Satisficing Games

Satisficing game theory is an alternative to traditional game theory which offers more flexibility in modeling players in social interactions. Unfortunately, satisficing players with conflicting attitudes may implement dysfunctional behaviors, resulting in poor performance. We present a method based on evolutionary game theory by which players may adapt their attitudes to their circumstances, allowing them to overcome dysfunction. Additionally, we extend the Nash equilibrium concept to satisficing games, showing that the method presented leads the players toward equilibrium in their attitudes. These ideas are applied to the ultimatum game as a simple example
Growth and Institutions: A Review of the Evidence

Africa's disappointing economic performance, the East Asian financial crisis, and the weak record of the former Soviet Union have focused attention on the role of institutions in determining a country's economic growth. This article critically reviews the literature that tries to link quantitative measures of institutions, such as civil liberties and property rights, with growth of gross domestic product across countries and over time. An important distinction is made between indicators that measure the performance or quality of institutions and those that measure political and social characteristics and political instability. The evidence suggests a link between the quality of institutions and investment and growth, but the evidence is by no means robust. Copyright 2000 by Oxford University Press.