Miracle-dz/UniFAR-FTUs huggingface dataset:
Deficiency in spliceosome-associated factor CTNNBL1 does not affect ongoing cell cycling but delays exit from quiescence and results in embryonic lethality in mice

CTNNBL1 is an armadillo-repeat protein that associates with the CDC5L/Prp19 complex of the spliceosome. Unlike the majority of spliceosomal proteins (and despite having no obvious homologs), CTNNBL1 is inessential for cell viability as revealed by studies in both vertebrate B cell lines and in fission yeast. Here, however, we show that ablation of CTNNBL1 in the mouse germline results in mid-gestation embryonic lethality but that lineage-specific CTNNBL1 ablation in early B cell precursors does not affect the production and abundance of mature B lymphocytes. However, CTNNBL1-deficient resting B lymphocytes show sluggish exit from quiescence on cell activation, although once entry into cycle has initiated, proliferation and differentiation in response to mitogenic stimuli continue largely unaffected. A similar sluggish exit from quiescence is also observed on reprovision of nutrients to nitrogen-starved CTNNBL1-deficient yeast. The results indicate that, whereas other RNA splicing-associated factors have been connected to cell cycle progression, CTNNBL1 plays no essential role in cycling cells but does fulfill an evolutionarily conserved function in helping cells to undergo efficient exit from quiescence following activation.
Cytolytic T lymphocytes displaying natural killer (NK)-like activity: expression of NK-related functional receptors for HLA class I molecules (p58 and CD94) and inhibitory effect on the TCR-mediated target cell lysis or lymphokine production.

Natural killer (NK) cells express surface receptors for defined groups of HLA class I alleles. The specific interaction between these receptors and HLA class I molecules expressed on target cells results in inhibition of NK-mediated target cell lysis. In this report, we analyzed whether similar mechanisms were operating in cytolytic T lymphocytes (CTLs) capable of lysing NK-sensitive target cells. T cell clones were screened for their ability to lyse K562 target cells. The selected clones expressed either gamma delta or alpha beta TCR. The majority of these clones failed to lyse the HLA class I+ R8/15375 cell line; however, upon addition of the previously described A6-136 (IgM) or 6A4 F(ab')2 anti-HLA class I mAbs, target cells were efficiently lysed. Lysis of autologous phytohemagglutinin blasts in the presence of anti-HLA class I mAbs occurred primarily with TCR gamma delta+ CTLs. Recognition of HLA class I molecules on target cells implies the expression of NK-related specific receptors in CTL clones. Indeed, phenotypic analysis of > 300 CTL clones with NK-like activity revealed that 28% expressed p58 molecules (specific for HLA-C alleles) while 30% expressed CD94 molecules (specific for the Bw6 specificity). These receptor molecules were found to function as inhibitory receptors, as revealed by the effect of anti-p58 or anti-CD94 mAbs (of IgG isotype) on the lysis of the Fc gamma R+ K562 target cells. (ABSTRACT TRUNCATED AT 250 WORDS)
Data-Driven Multiresolution Camera Using the Foveal Adaptive Pyramid

There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a relatively small region, but covering a wide field of view. This is the aim of foveal vision systems. Briefly, they propose to sense a large field of view at a spatially-variant resolution: one relatively small region, the fovea, is mapped at a high resolution, while the rest of the image is captured at a lower resolution. In these systems, this fovea must be moved, from one region of interest to another one, to scan a visual scene. It is interesting that the part of the scene that is covered by the fovea should not be merely spatial, but closely related to perceptual objects. Segmentation and attention are then intimately tied together: while the segmentation process is responsible for extracting perceptively-coherent entities from the scene (proto-objects), attention can guide segmentation. From this loop, the concept of foveal attention arises. This work proposes a hardware system for mapping a uniformly-sampled sensor to a space-variant one. Furthermore, this mapping is tied with a software-based, foveal attention mechanism that takes as input the stream of generated foveal images. The whole hardware/software architecture has been designed to be embedded within an all programmable system on chip (AP SoC). Our results show the flexibility of the data port for exchanging information between the mapping and attention parts of the architecture and the good performance rates of the mapping procedure. Experimental evaluation also demonstrates that the segmentation method and the attention model provide results comparable to other more computationally-expensive algorithms.
Evaluation of the growth response of six invasive species to past, present and future atmospheric carbon dioxide.

The response of plant species to future atmospheric carbon dioxide concentrations [CO(2)] has been determined for hundreds of crop and tree species. However, no data are currently available regarding the response of invasive weedy species to past or future atmospheric [CO(2)]. In the current study, the growth of six species which are widely recognized as among the most invasive weeds in the continental United States, Canada thistle (Cirsium arvense (L.) Scop. ), field bindweed (Convolvulus arvensis L.), leafy spurge (Euphorbia esula L.), perennial sowthistle (Sonchus arvensis L.), spotted knapweed (Centaurea maculosa Lam.), and yellow star thistle (Centaurea solstitialis L.) were grown from seed at either 284, 380 or 719 micromol mol(-1) [CO(2)] until the onset of sexual reproduction (i.e. the vegetative period). The CO(2) concentrations corresponded roughly to the CO(2) concentrations which existed at the beginning of the 20th century, the current [CO(2)], and the future [CO(2)] projected for the end of the 21st century, respectively. The average stimulation of plant biomass among invasive species from current to future [CO(2)] averaged 46%, with the largest response (+72%) observed for Canada thistle. However, the growth response among these species to the recent [CO(2)] increase during the 20th century was significantly higher, averaging 110%, with Canada thistle again (+180%) showing the largest response. Overall, the CO(2)-induced stimulation of growth for these species during the 20th century (285-382 micromol mol(-1)) was about 3x greater than for any species examined previously. Although additional data are needed, the current study suggests the possibility that recent increases in atmospheric CO(2) during the 20th century may have been a factor in the selection of these species.
Towards the Augmented Pathologist: Challenges of Explainable-AI in Digital Pathology

Digital pathology is not only one of the most promising fields of diagnostic medicine, but at the same time a hot topic for fundamental research. Digital pathology is not just the transfer of histopathological slides into digital representations. The combination of different data sources (images, patient records, and *omics data) together with current advances in artificial intelligence/machine learning enable to make novel information accessible and quantifiable to a human expert, which is not yet available and not exploited in current medical settings. The grand goal is to reach a level of usable intelligence to understand the data in the context of an application task, thereby making machine decisions transparent, interpretable and explainable. The foundation of such an "augmented pathologist" needs an integrated approach: While machine learning algorithms require many thousands of training examples, a human expert is often confronted with only a few data points. Interestingly, humans can learn from such few examples and are able to instantly interpret complex patterns. Consequently, the grand goal is to combine the possibilities of artificial intelligence with human intelligence and to find a well-suited balance between them to enable what neither of them could do on their own. This can raise the quality of education, diagnosis, prognosis and prediction of cancer and other diseases. In this paper we describe some (incomplete) research issues which we believe should be addressed in an integrated and concerted effort for paving the way towards the augmented pathologist.
Ontologies in Software Testing: A Systematic Literature Review

Ontologies have been widely recognized as an important instrument for supporting Knowledge Management (KM). In order to look for a domain ontology that can be used in KM in software testing, in this paper, we investigate, by means of a Systematic Literature Review (SLR), ontologies in the software testing domain, including questions related to their coverage of the software testing domain, and how they were developed.
The Effect of Kraussianone‐2 (Kr2), a Natural Pyrano‐isoflavone from Eriosema kraussianum, in an L‐NAME‐ induced Pre‐eclamptic Rat Model

This study aimed to investigate the effects of Kraussianone‐2 (Kr2), a pyrano‐isoflavone isolated from the roots of Eriosema kraussianum N. E. Br. (Fabaceae) on various fetal and physiological parameters in pregnant, L‐NAME treated Sprague–Dawley rats. Twenty‐four pregnant Sprague–Dawley dams were divided into three groups (n = 8), i.e. the control group (CON), the experimental control group (PRE), where the pre‐eclampsia‐like symptoms were induced using L‐NAME, and the experimental group (EK2), where the pre‐eclampsia‐like symptoms were once again induced using L‐NAME, however, these animals were treated with Kr2. On gestation day 20 the animals were sacrificed, at which time a laparotomy was performed and the number of live pups were counted and their corresponding birth and placental weights were recorded. Blood was also collected in heparin‐coated tubes and the plasma samples were then analysed for specific variables using commercially available kits for rats. Kraussianone‐2 administration decreased fetal mortality and demonstrated a trend toward increasing birth and placental weights in this model. Furthermore, Kr2 administration also reduced blood pressure amplification and decreased the plasma concentrations of two antiangiogenic factors, soluble fms‐like tyrosine kinase1 (sFlt‐1) and soluble endoglin (sEng). We speculate that Kr2, by improving uterine artery blood flow, results in improved fetal outcomes and decreased antiangiogenic factors in pregnant, L‐NAME treated, Sprague–Dawley rats. Copyright © 2012 John Wiley & Sons, Ltd.
Review literature about relationship between Spiritual Intelligence and Job Satisfaction

Over the years, many researches have been done to find the best criteria to predict coordination of individuals with their surrounding environment, based on specific characteristics of each person. Hence, the concept of IQ was introduced. Many years after introduction of this intelligence and its applications all over the world, researchers found its limitations and introduced another type of intelligence, called Emotional intelligence. Emotional intelligence is the ability of inhibition and adjusting emotions and logic in a way that leads us to happiness. During late 20th century, some evidences revealed there is another type of intelligence which can complete the image of human intelligence. Danah Zohar (1997) introduced spiritual intelligence for the first time and proved its existence using some scientific reasons. Using this intelligence, people can view their lives with extended view and act efficiently in their lives. Today, spiritual intelligent is discussed not only in individual area but in organizational area, and has entered not only psychological domain, but other human science areas- such as management. Most of scientists believe that spiritual intelligence is the most important type of intelligence which has the power to change our life, society, and history.
Is There an Informal Employment Wage Penalty in Egypt?

This paper considers the private sector wage earners in Egypt and examine their wage distribution during 1998-2012 using Egyptian Labor Market Panel Survey. We first estimate Mincer wage equations both at the mean and at different quantiles of the wage distribution taking into account observable characteristics. Then we make use of the panel feature of the data and estimate models taking into account unobservable characteristics. We also consider the possibility of nonlinearity in covariate effects and estimate a variant of matching models. In all cases we find a persistent informal wage penalty in the face of extensive sensitivity checks. It is smaller when unobserved heterogeneity is taken into account and larger at the top than at the bottom of the conditional wage distribution. We also examine the informal wage penalty over time during the study period and in different groups according to experience and education. The informal wage penalty has increased recently over time and is larger for the better educated but smaller for the more experienced.
High leptin and resistin expression in chronic heart failure: adverse outcome in patients with dilated and inflammatory cardiomyopathy

The expression of leptin and resistin is known to be positively correlated with the incidence of chronic heart failure (CHF). Both adipokines have been implicated in immunomodulation and cardiac remodelling. Therefore, we performed for the first time a clinical study to elucidate the effects of leptin and resistin on progression of CHF in patients with non‐ischaemic dilated (DCM) and inflammatory (DCMi) cardiomyopathy.
CD68 and interleukin 13, prospective immune markers for esophageal squamous cell carcinoma prognosis prediction

Purpose Oncology immunity was reported to play a key role in cancer development and progression, so we investigated the prediction role of several immune markers in esophageal squamous cell carcinoma (ESCC) patients after operation in this study. Patients and Methods 66 primary ESCC tumor tissues and four sets of tissue microarrays including 705 primary ESCC tumor tissues from four centers were collected and analyzed. Expressions of several immune markers in ESCC tumor tissue were detected with immunohistochemistry staining. Their distribution densities were analyzed with InForm™ 2.0. 1 software. All statistic analyses were performed with SPSS16.0 and Stata version 10.0. Results Survival analyses assessed by Kaplan-Meier plots and log-rank tests demonstrated that densities of CD68 and interleukin 13 (IL-13) in tumor stroma were positively correlated with the overall survival of ESCC patients after operation (p < 0.01 for CD68, p < 0.001 for IL-13). Further, a model based on tumor stroma densities of CD68 and IL-13 was constructed and it could significantly classify patients with poor or good prognosis. This model could further identify high-risk group and low-risk group at the same Tumor lymph Nodes Metastases (TNM) stage. Lastly, a more accuracy model based on TNM stage, densities of CD68 and IL-13 was constructed to predict the prognosis of ESCC patient after operation. Conclusion Combining the TNM staging system and densities of CD68 and IL-13 could substantially improve the prognosis prediction accuracy of ESCC patient after operation, which might be an excellent tool for selecting patients for individualized therapy in future.
Advances and challenges in super‐resolution

Super‐Resolution reconstruction produces one or a set of high‐resolution images from a sequence of low‐resolution frames. This article reviews a variety of Super‐Resolution methods proposed in the last 20 years, and provides some insight into, and a summary of, our recent contributions to the general Super‐Resolution problem. In the process, a detailed study of several very important aspects of Super‐Resolution, often ignored in the literature, is presented. Specifically, we discuss robustness, treatment of color, and dynamic operation modes. Novel methods for addressing these issues are accompanied by experimental results on simulated and real data. Finally, some future challenges in Super‐Resolution are outlined and discussed. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 47–57, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20007
Ligament Model Fidelity in Finite Element Analysis of the Human Lumbar Spine

Ligament Model Fidelity in Finite Element Analysis of the Human Lumbar Spine Mitchell Scott Hortin Department of Mechanical Engineering, BYU Master of Science The purpose of this project is to quantify the effects of increasing spinal ligament fidelity on the mechanics of the human lumbar spine using finite element analysis (FEA). In support of this goal, a material characterization study was completed to provide anisotropic, nonlinear material parameters for the human anterior longitudinal ligament. (ALL). Cadaveric samples of the human ALL were tested using a punch test technique. Multiaxial force-deformation data were gathered and fit to a commonly used transversely isotropic material model using an FEA system identification routine. The resulting material parameters produced a curve that correlated well with the experimental curve (R2≥0.98). Recently published material data on several major spinal ligaments have been incorporated into an existing finite element model of the human lumbar spine. This data includes the results from the above mentioned material characterization, similar material characterizations of the supraspinous (SSL) and interspinous (ISL) ligaments, localized material properties of the SSL and pre-strain data for the ISL, SSL and ALL. These results have been incorporated both separately and compositely into the finite element model and each configuration has been simulated in spinal flexion, extension, axial rotation and lateral bending. Results suggest that the effects of increased ligament model fidelity on bone strain energy were moderate and the effects on disc pressure were slight, and do not justify a change in modeling strategy for most clinical applications. There were significant effects on the ligament stresses of the ligaments that were directly modified, suggesting that these phenomenon should be included in FE models where ligament stresses are the desired metric.
Fatores de escolha da carreira de administração e da instituição de ensino

The intensification of competition and the growth of unoccupied positions characterize the situation of the institutions offering business administration degree. This condition is aggravated by the lack of information on students' motivation to choose such career and find the best relevant educational institution. This work purposes to develop a research considering the competitive scenario by mapping the aspectual issues regarding such choice, with focus on the research held in ABC Paulista region. Initially, in an exploratory approach, experts were interviewed and the reasons of their options were pointed . In a second and descriptive phase, 1635 students were interviewed and the variables indicated by the experts were assessed. Making use of a multivariate tool, five factors were found to explain the choice for the Business Administration career: (potentiality, affinity, continuity, accessibility and familiarity with the career) and four factors were found to the choice of the school: Infrastructure, Image, Recommendation and Institution Accessibility, offering relevant data for operating decisions, provision of services and communication to the institutions.
Development plan for research on omni-channel shopping to purchase intention

The new concept of omni-channel has inspired researchers to develop a model of consumer confusion to increase purchase intention. Previous studies were tested that the omni-channel integration quality can improve customer satisfaction. As a novelty, we introduced omni-channel integration as a moderating variable that influence consumer confusion to the intention of purchase. This paper constituted a hypothetical development about the proposed omni-channel integration as a part of the e-quality service. This proposed research aimed to explore the effect of consumer confusion towards purchase intention moderated by omni-channel integration. In addition, this study discussed about the antecedent of consumer confusion to the intention of purchase, namely e-WOM. Three hypotheses were modeled in this research proposal. The future results of this research were expected to be a significant contribution towards business, science, and society.
Segmentation of Moving Objects by Long Term Video Analysis

Motion is a strong cue for unsupervised object-level grouping. In this paper, we demonstrate that motion will be exploited most effectively, if it is regarded over larger time windows. Opposed to classical two-frame optical flow, point trajectories that span hundreds of frames are less susceptible to short-term variations that hinder separating different objects. As a positive side effect, the resulting groupings are temporally consistent over a whole video shot, a property that requires tedious post-processing in the vast majority of existing approaches. We suggest working with a paradigm that starts with semi-dense motion cues first and that fills up textureless areas afterwards based on color. This paper also contributes the Freiburg-Berkeley motion segmentation (FBMS) dataset, a large, heterogeneous benchmark with 59 sequences and pixel-accurate ground truth annotation of moving objects.
Detection of Driver Drowsiness Using Wavelet Analysis of Heart Rate Variability and a Support Vector Machine Classifier

Driving while fatigued is just as dangerous as drunk driving and may result in car accidents. Heart rate variability (HRV) analysis has been studied recently for the detection of driver drowsiness. However, the detection reliability has been lower than anticipated, because the HRV signals of drivers were always regarded as stationary signals. The wavelet transform method is a method for analyzing non-stationary signals. The aim of this study is to classify alert and drowsy driving events using the wavelet transform of HRV signals over short time periods and to compare the classification performance of this method with the conventional method that uses fast Fourier transform (FFT)-based features. Based on the standard shortest duration for FFT-based short-term HRV evaluation, the wavelet decomposition is performed on 2-min HRV samples, as well as 1-min and 3-min samples for reference purposes. A receiver operation curve (ROC) analysis and a support vector machine (SVM) classifier are used for feature selection and classification, respectively. The ROC analysis results show that the wavelet-based method performs better than the FFT-based method regardless of the duration of the HRV sample that is used. Finally, based on the real-time requirements for driver drowsiness detection, the SVM classifier is trained using eighty FFT and wavelet-based features that are extracted from 1-min HRV signals from four subjects. The averaged leave-one-out (LOO) classification performance using wavelet-based feature is 95% accuracy, 95% sensitivity, and 95% specificity. This is better than the FFT-based results that have 68.8% accuracy, 62.5% sensitivity, and 75% specificity. In addition, the proposed hardware platform is inexpensive and easy-to-use.