Miracle-dz/UniFAR-FTUs huggingface dataset:
Specific in vivo knockdown of protein function by intrabodies

Intracellular antibodies (intrabodies) are recombinant antibody fragments that bind to target proteins expressed inside of the same living cell producing the antibodies. The molecules are commonly used to study the function of the target proteins (i.e., their antigens). The intrabody technology is an attractive alternative to the generation of gene-targeted knockout animals, and complements knockdown techniques such as RNAi, miRNA and small molecule inhibitors, by-passing various limitations and disadvantages of these methods. The advantages of intrabodies include very high specificity for the target, the possibility to knock down several protein isoforms by one intrabody and targeting of specific splice variants or even post-translational modifications. Different types of intrabodies must be designed to target proteins at different locations, typically either in the cytoplasm, in the nucleus or in the endoplasmic reticulum (ER). Most straightforward is the use of intrabodies retained in the ER (ER intrabodies) to knock down the function of proteins passing the ER, which disturbs the function of members of the membrane or plasma proteomes. More effort is needed to functionally knock down cytoplasmic or nuclear proteins because in this case antibodies need to provide an inhibitory effect and must be able to fold in the reducing milieu of the cytoplasm. In this review, we present a broad overview of intrabody technology, as well as applications both of ER and cytoplasmic intrabodies, which have yielded valuable insights in the biology of many targets relevant for drug development, including α-synuclein, TAU, BCR-ABL, ErbB-2, EGFR, HIV gp120, CCR5, IL-2, IL-6, β-amyloid protein and p75NTR. Strategies for the generation of intrabodies and various designs of their applications are also reviewed.
Fuzzy Logic Controller with Maximum Power Point Tracking using Creative Design of DC to DC Buck Converter for Photovoltaic Power System

The studies on the photovoltaic (PV) generation are extensively increasing, since it is considered as an essentially inexhaustible and broadly available energy resource. However the output power induced in the photovoltaic module depends on solar radiation and temperature of the solar cells. Therefore to maximize the efficiency of the renewable solar energy system. It is necessary to track the maximum power point of the PV panel. In this paper, a maximum power point tracker using fuzzy set theory is presented to improve energy conversion efficiency 96.5%. The new method gives a very good maximum power operation of any PV module under different conditions such as changing insolation and temperature. The simulation studies show the effectiveness of the proposed algorithm.
Isolation and Identification of Endophytic Bacteria Antagonistic to Camellia Oleifera Leaf Blight Base on Informatics

Leaf blight is a common Camellia oleifera disease caused by Pestalotiopsis microspora. The damaged young leaves show blight symptom, resulting in yield reduction. This study was to isolate antagonistic bacteria from Camellia oleifera tissue for control of the leaf blight. Antagonistic bacteria was screened from 175 endophytic bacterias by confront culture method. The results of the study showed that the antagonistic effect of YB13 strain was the best with 84.7% inhibitory rate. According to the results of the researching on morphology, cultural characteristics, physiological and biochemical propertices, 16S gene sequence and molecular phylogenetic tree, YB13 was identified as Bacillus subtilis.
Relationship satisfaction, emotional distress,and relationship dissolution: : a population-based study on pregnant women and their partners

Background Recognition of maternal emotional distress during pregnancy and the identification of risk factors for this distress are of considerable clinicaland public health importance. The mental health of the mother is important for the physical and psychological health of her children and the welfare of the family. The first aim of the present study was to identify risk factors for maternal emotional distress during pregnancy with special focus on partner relationship satisfaction. The second aim was to assess interaction effects between relationship satisfaction and the main predictors. Methods Pregnant women enrolled in the Norwegian Mother and Child Cohort Study (n = 51,558) completed a questionnaire with questions about maternal emotional distress, relationship satisfaction, and other risk factors. Associations between 39 predictor variables and emotional distress were estimated by multiple linear regression analysis. Results Relationship dissatisfaction was the strongest predictor of maternal emotional distress ( = 0.25). Other predictors were dissatisfaction at work ( = 0.11), somatic disease ( = 0.11), work related stress ( = 0.10) and maternal alcohol problems in the preceding year ( = 0.09). Relationship satisfaction appeared to buffer the effects of work stress, dissatisfaction at work, frequent moving, and somatic disease (P < 0.005).
Diagnosing timing related cell internal defects for FinFET technology

The semiconductor industry is encountering an increasing number of front-end-of-line defects in the advanced FinFET technology nodes due to extremely small feature size and complex manufacturing processes required for FinFET transistors. Traditional delay diagnosis algorithm has a limited support for cell internal timing related failures based on transition delay faults, and tends to provide a large suspect list. It cannot provide the precise defect location inside the cell that is necessary for effective physical failure analysis and statistical yield learning. In this work, we present a new cell-aware delay diagnosis algorithm, based on accurate delay fault models derived by analog simulation, which can pinpoint the defect location within a cell for various timing related cell internal defects. Preliminary results for real silicon failures show that significant diagnosis resolution improvement can be achieved by the proposed method.
Evidence on Dropout Phenomena at Universities

3 Preface This publication is an excerpt from the full technical report 'Dropout Phenomena at Universities: What is Dropout? Why does Dropout Occur? What Can be Done by the Universities to Prevent or Reduce it? A systematic review', which was completed in April 2013. The purpose of this excerpt is to present the knowledge we have on dropout phenomena at European universities in a short, precise and comprehensible form to allow readers to orient themselves on the subject in a more readable manner. Thanks to the The Swiss Council for Educational Research, the members of the review group and to all the colleagues and researchers who have contributed to this brief presentation of the results of the systematic review. The complete report with references and appendices can be found at Danish Clearinghouse for Educational Research derives knowledge from research. We collect, analyse and distribute results from educational research to politicians, practitioner and other researchers working at all educational levels. Among other things, we investigate whether it is possible to determine what types of initiatives have a positive effect on various educational outcomes by looking across studies. Moreover, Danish Clearinghouse facilitates research & development in educational institutions. 5 Introduction – dropout phenomena at universities Conceptualising university dropout Dropout from university studies is only apparently a straightforward concept. The term 'university dropout' is commonly used to describe situations where a student leaves the university study in which (s)he has enrolled before having obtained a formal degree. The terms used to describe university dropout from a student perspective are many: dropout, departure, withdrawal, academic failure, non-continuance, non-completion, whereas their positive counterparts are: persistence, continuance, completion etc. From an institutional and governmental perspective student attrition rate is a commonly applied term, whereas retention and graduation rate often indicate the positive outcomes (Jones, 2008: 1). University dropout can be more or less voluntary in character as seen from the individual student's perspective. A student can drop out of his/her university study due to failure to meet the academic standards and demands within university in which case dropout should be viewed as involuntary. On the other hand, a student can decide to drop out of his/her university study for reasons more voluntary in character, for instance, in pursuit of another subject of study and/or another university, in which case the dropout is better described as a student transfer within the system of higher education (or alternatively, …
FIRST STEPS WITH PROGRAM MARK : LINEAR MODELS

Program MARK is the most comprehensive software application available for analyzing data from marked individuals, making full use of the linear models paradigm to provide a robust analytical and statistical framework. I briefly describe how to use MARK to implement some general linear models, focusing on the structure and modification of the design matrix. My intent is to provide a general understanding of the main concepts, as applied generally to analysis of variance and specifically to analysis of data from marked individuals. With any software application as complex and comprehensive as MARK, a great many details exist that are potentially important for a given analysis. Some details are theoretical (determined by the type of data being analyzed and the models being fit), and some mechanical (involving various means to use MARK to accomplish the desired task). A basic understanding of these concepts is essential for using MARK, for either simple or complex analyses. Increasingly, the management and conservation of natural systems requires the statistical analysis of data to draw inferences concerning the populations inhabiting those systems. This increasing use of statistical methods has in part been advanced by the growing availability of computer software, which has made application of various statistical models (including many theoretical ones) both tractable and efficient for wildlife and conservation scientists. This relationship between software and application has been fundamental to recent increases in data analysis from marked individuals. Whereas the general concepts behind some typical data analyses (e.g., mark– recapture analysis of data from live encounters, recovery analysis of data from dead recoveries, analysis of known-fate telemetry data) are familiar, applying these approaches to data analysis has often lagged because of the difficulty in finding and using appropriate computer software. Further, the available software was often written by specialists, for specialists, and was often difficult to use without significant technical support. Over the past 15 years, there has been a significant increase in the number of software applications available for analysis of data from marked individuals. However, many of the early efforts (e.g., JOLLY, JOLLYAGE; Pollock et al. 1990)—although significantly easier to use than previously available software (e.g., SURVIV; White 1983)—were extremely limited in their utility. Much software consisted of a set of pre defined (" canned ") models that the user then selected among; little if any flexibility existed in the software to modify the analysis to suit individual needs and purposes. While program …
A Novel Spectral Clustering and its Application in Image Processing

This paper proposes an improved spectral clustering algorithm based on neighbour adaptive scale, who fully considers the local structure of dataset using neighbour adaptive scale, which simplifies the selection of parameters and makes the improved algorithm insensitive to both density and outliers. This paper illustrates the proposed algorithm not only has inhibition for certain outliers but is able to cluster the data sets with different scales. Experiments on UCI data sets show that the proposed method is effective. Some experiments were also performed in image clustering and image segmentation to demonstrate its excellent features in application.
Conditional Predictive Regions For Stochastic Processes

Studies on pointwise prediction of nonlinear time series have revealed some distinguishing features of nonlinear prediction. Being signiicantly diierent from linear prediction, the prediction accuracy for nonlinear time series depends on the current position in the state space. Furthermore, small perturbation in current position can lead to considerable errors in nonlinear prediction (see Yao and Tong 1994a.) The above features can also be observed in state-dependent interval/region prediction. In this paper, we consider two types of region predictors | the maximum conditional density region and the shortest conditional modal interval, both of them depending on the current position in the state space. When the underlying conditional distribution is skewed or multi-modal, the two proposed predictors outperform the predictive interval constructed from the conditional percentiles. Based on the data f(X t ; Y t); 1 t ng, which are the observations from a strictly stationary process, the conditional distribution function of Y t given X t is estimated using the kernel regression procedure. Further, we estimate the two predictive regions for Y t from X t (t > n) based on the estimated conditional distribution functions. The sensitivity measure deened in the form of the Kullback-Leibler information has been used to monitor the errors in the coverage probabilities of any predictive regions as well as the changes in the width of the conditional modal intervals due to small perturbation in X t. Both simulated and real data sets are used as illustrations.
Single-Layer Waveguide Circuit to control Sidelobe and Crossover Levels in Butler-Matrix Beam-Switching Antenna

The Butler matrix [1] is a beam-forming network for a multi-beam array antenna. The main-beam direction can be switched according to the input port. Conventional Butler matrix suffers from high crossover levels between adjacent main beams of -3.7dB and high sidelobe levels of -11.4dB independent on the number of ports, theoretically. In order to solve these problems, the configuration of a circuit has been proposed to control the crossover and sidelobe levels by using two-way dividers with 180-degree difference [2]. This paper presents this circuit configuration by single-layer post-wall waveguides [3] to integrate with a Butler matrix and a slotted waveguide antenna by complete single layer.
Type II dehydroquinase: molecular replacement with many copies

The type II dehydroquinase enzyme is a symmetrical dodecameric protein which crystallizes in either high-symmetry cubic space groups or low-symmetry crystal systems with multiple copies in the asymmetric unit. Both systems have provided challenging examples for molecular replacement; for example, a triclinic crystal form has 16 dodecamers (192 monomers) in the unit cell. Three difficult examples are discussed and two are used as test cases to compare the performance of four commonly used molecular-replacement packages.
PRELIMINARY VERSION - PRELIMINARY VERSION -PRELIMINA Modeling Tutoring Knowledge

LORIA, Universit Henr i Poincar Nancy1 Campus scientifique, BP 239, 54506 Vandoeuvre Cedex, FRANCE bourdeau@teluq.uqam. ca monique.grandbastien@loria.fr Abstract. This chapter introduces Part II on modeling tutoring knowledge in ITS r esearch. Starting with its origin and with a characterization of tutoring, it proposes a general defin ition of tutoring, and a description of tutoring functions, variables, and interactions. The I nteraction Hypothesis is presented and discussed, followed by the development of the tut orial component of ITSs, and their evaluation. New challenges are described, such as integrating the emotional states of the learner. Perspectives of opening the Tutoring Model and of equipping it with social intelligence are also presented.
30-day hospital readmission of older adults using care transitions after hospitalization: a pilot prospective cohort study

Purpose Patients leaving the hospital are at increased risk of functional decline and hospital readmission. The Employee and Community Health service at Mayo Clinic in Rochester developed a care transition program (CTP) to provide home-based care services for medically complex patients. The study objective was to determine the relationship between CTP use, 30-day hospital readmission, and Emergency Room (ER) visits for adults over 60 years with high Elder Risk Assessment scores. Patients and methods This was a pilot prospective cohort study that included 20 patients that used the CTP and 20 patients discharged from the hospital without using the CTP. The medically complex study patients were drawn from the department of Employee and Community Health population between October 14, 2011 and September 27, 2012. The primary outcomes were 30-day hospital readmission or ER visit after discharge from the hospital. The secondary outcomes were within-group changes in grip strength, gait speed, and quality of life (QOL). Patients underwent two study visits, one at baseline and one at 30 days postbaseline. The primary analysis included time-to-event from baseline to rehospitalization or ER visit. Paired t-tests were used for secondary outcomes, with continuous scores. Results Of the 40 patients enrolled, 36 completed all study visits. The 30-day hospital readmission rates for usual care patients were 10.5% compared with no readmissions for CTP patients. There were 31.6% ER visits in the UC group and 11.8% in the CTP group (P = 0.37). The secondary analysis showed some improvement in physical QOL scores (pre: 32.7; post: 39.4) for the CTP participants (P < 0.01) and no differences in gait speed or grip strength. Conclusion Based on this pilot study of care transition, we found nonsignificant lower hospital and ER utilization rates and improved physical QOL scores for patients in the CTP group. However, the data leads us to recommend future studies with larger sample sizes (N = 250).
A Boosting-Based Spatial-Spectral Model for Stroke Patients’ EEG Analysis in Rehabilitation Training

Studies have shown that a motor imagery electro encephalogram (EEG)-based brain-computer interface (BCI) system can be used as a rehabilitation tool for stroke patients. Efficient classification of EEG from stroke patients is fundamental in the BCI-based stroke rehabilitation systems. One of the most successful algorithms for EEG classification is the common spatial patterns (CSP). However, studies have reported that the performance of CSP heavily relies on its operational frequency band and channels configuration. To the best of our knowledge, there is no agreed upon clinical conclusion about motor imagery patterns of stroke patients. In this case, it is not available to obtain the active channels and frequency bands related to brain activities of stroke patients beforehand. Hence, for using the CSP algorithm, we usually set a relatively broad frequency range and channels, or try to find subject-related frequency bands and channels. To address this problem, we propose an adaptive boosting algorithm to perform autonomous selection of key channels and frequency band. In the proposed method, the spatial-spectral configurations are divided into multiple preconditions, and a new heuristic supervisor of stochastic gradient boost strategy is utilized to train weak classifiers under these preconditions. Extensive experiment comparisons have been performed on three datasets including two benchmark datasets from the famous BCI competition III and BCI competition IV as well as one self-acquired dataset from stroke patients. Results show that our algorithm yields relatively higher classification accuracies compared with seven state-of-the-art approaches. In addition, the spatial patterns (spatial weights) and spectral patterns (bandpass filters) determined by the algorithm can also be used for further analysis of the data, e.g., for brain source localization and physiological knowledge exploration.
Mesh Connectivity Compression for Progressive-to-Lossless Transmission

A progressive mesh connectivity compression technique is proposed in this paper. Our method is based on the edge collapse and vertex splitting technique for progressive mesh compressiondecompression. This is an efficient and reversible method that can be used for progressive-to-lossless transmission. We derive a theoretical upper bound for the lossless connectivity compression bit rate, when the isolated vertices are ignored. Our experiments show that all the meshes we have used can be compressed better than the derived bit rate upper bound. Furthermore, our method can ensure that less than 10% of the vertices generate accidental code. According to our analysis, the optimal bound for triangular mesh coding can be 3, smaller than some of the reported results in recent literature.
Envelope model for resonant converters and application in LLC converters

This paper presents the large and small signal envelope models for switching networks and rectifiers with variable frequency phase-shifted control for resonant converters. The model can be used to quickly perform DC and AC analysis with SPICE-compatible soft tools for a converter with frequency control, duty cycle control and variable frequency and variable control. Then the large signal envelope model of a LLC converter is given, the DC and AC sweep results with P SPICE are presented, by which its characteristic can be analyzed. Finally the verified results are given.
The Role of Interorganizational Fit in Global Account Management

In this paper, we apply the concept of interorganizational fit to the use of global account management programs in multinational corporations. It is predicted that greater fit between vendor and customer on a variety of strategic as well as structural aspects will result in higher performance of the relationship. This is contrasted with a bargaining perspective approach to managing customer relationships. Support for the hypotheses is found using a survey of 106 global account managers in 16 multinational corporations.
Aerosol backscatter and extinction retrieval from airborne coherent Doppler wind lidar measurements

A novel method for coherent Doppler wind lidars (DWLs) calibration is shown in this work. Concurrent measurements of a ground based aerosol lidar operating at 532 nm and an airborne DWL at 2 gm are used in combination with sun photometer measurements for the retrieval of backscatter and extinction profiles. The presented method was successfully applied to the measurements obtained during the Saharan Aerosol Long-range Transport and Aerosol Cloud -Interaction Experiment (SALTRACE: http://www.pa.op.dlr.de/saltrace), which aimed to characterize the Saharan dust long range transport between Africa and the Caribbean.