Miracle-dz/UniFAR-FTUs huggingface dataset:
Pseudotime estimation: deconfounding single cell time series

Cross-sectional time series single cell data confound several sources of variation, with contributions from measurement noise, stochastic cell to cell variation and cell progression at different rates. Time series from single cell assays are particularly susceptible to confounding as the measurements are not averaged over populations of cells. When several genes are assayed in parallel these effects can be estimated and corrected for under certain smoothness assumptions on cell progression. We present a principled probabilistic model with a Bayesian inference scheme to analyse such data. We demonstrate our method’s utility on public microarray, nCounter and RNA-seq data sets from three organisms. Our method almost perfectly recovers withheld capture times in an Arabidopsis data set, it accurately estimates cell cycle peak times in a human prostate cancer cell line and it correctly identifies two precocious cells in a study of paracrine signalling in mouse dendritic cells. Furthermore, our method compares favourably with Monocle, a state-of-the-art technique. We also show using held out data that uncertainty in the temporal dimension is a common confounder and should be accounted for in analyses of cross-sectional time series.
Health and Quality of Life Outcomes

Background: Research has indicated that stable individual differences in personality exist among persons with schizophrenia spectrum disorders predating illness onset that are linked to symptoms and self appraised quality of life. Less is known about how closely individual differences in personality are uniquely related to levels of social relationships, a domain of dysfunction in schizophrenia more often linked in the literature with symptoms and neurocognitive deficits. This study tested the hypothesis that trait levels of personality as defined using the five-factor model of personality would be linked to social function in schizophrenia. Methods: A self-report measure of the five factor model of personality was gathered along with ratings of social function, symptoms and assessments of neurocognition for 65 participants with schizophrenia or schizoaffective disorder. Results: Univariate correlations and stepwise multiple regression indicated that frequency of social interaction was predicted by higher levels of the trait of Agreeableness, fewer negative symptoms, better verbal memory and at the trend level, lesser Neuroticism (R2 = .42, p < .0001). In contrast, capacity for intimacy was predicted by fewer negative symptoms, higher levels of Agreeableness, Openness, and Conscientiousness and at the trend level, fewer positive symptoms (R2 = .67, p < .0001). Conclusions: Taken together, the findings of this study suggest that person-centered variables such as personality, may account for some of the broad differences seen in outcome in schizophrenia spectrum disorders, including social outcomes. One interpretation of the results of this study is that differences in personality combine with symptoms and neurocognitive deficits to affect how persons with schizophrenia are able to form and sustain social connections with others. Background Interest has increasingly grown in understanding how differences in personality may affect outcome in schizophrenia [1,2]. Just as in a wide range of other severe and debilitating medical conditions [3-7], the manner in which people interpret and respond to a life touched by schizophrenia may deeply impact upon the recovery process [8-11]. Published: 16 March 2004 Health and Quality of Life Outcomes 2004, 2:15 Received: 22 December 2003 Accepted: 16 March 2004 This article is available from: http://www.hqlo. com/content/2/1/15 © 2004 Lysaker and Davis; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL.
GIS Database Development and Exchange: Interaction Mechanisms and Motivations

The idea of sharing geographic data both within and between organizations remains largely resisted despite the obvious benefits that can be derived from data sharing activities and federal initiatives that promote them. The research presented in this paper examines the various properties of data sharing activities, as well as related motivations cited by members of organizations as reasons for entering into cooperative relationships. The findings suggest that organizational members have a number of different reasons for engaging in data sharing relationships, with common missions/goals and saving of resources being the most frequently cited motivations. Financial resources are the more important reasons for external than for internal interactions. Further, both interand intraorganizational activities are guided with formalized mechanisms, the former predominantly in the form of legal contracts and agreements, CONTENTS 4.
Discovery of Specific Inhibitors for Intestinal E. coli   β-Glucuronidase through In Silico Virtual Screening

Glucuronidation is a major metabolism process of detoxification for carcinogens, 4-(methylnitrosamino)-1-(3-pyridy)-1-butanone (NNK) and 1,2-dimethylhydrazine (DMH), of reactive oxygen species (ROS). However, intestinal E. coli β-glucuronidase (eβG) has been considered pivotal to colorectal carcinogenesis. Specific inhibition of eβG may prevent reactivating the glucuronide-carcinogen and protect the intestine from ROS-mediated carcinogenesis. In order to develop specific eβG inhibitors, we found that 59 candidate compounds obtained from the initial virtual screening had high inhibition specificity against eβG but not human βG. In particular, we found that compounds 7145 and 4041 with naphthalenylidene-benzenesulfonamide (NYBS) are highly effective and selective to inhibit eβG activity. Compound 4041 (IC50 = 2.8 μM) shows a higher inhibiting ability than compound 7145 (IC50 = 31.6 μM) against eβG. Furthermore, the molecular docking analysis indicates that compound 4041 has two hydrophobic contacts to residues L361 and I363 in the bacterial loop, but 7145 has one contact to L361. Only compound 4041 can bind to key residue (E413) at active site of eβG via hydrogen-bonding interactions. These novel NYBS-based eβG specific inhibitors may provide as novel candidate compounds, which specifically inhibit eβG to reduce eβG-based carcinogenesis and intestinal injury.
A measure of stages of change in fruit and vegetable consumption among fourth- and fifth-grade school children: reliability and validity.

OBJECTIVE We developed, pilot-tested, and field-applied a stages of change questionnaire regarding fruit and vegetable (F&V) consumption among fourth- and fifth-grade students. METHODS The design included cross-sectional assessment of internal consistency and construct validity, and 2-week and 7-week longitudinal assessment of test-retest reliability. Subjects included 134 students from one school for pilot-testing and 252 from two schools for field application. Thirty-two questions from McConnaughy et al's stages of change questionnaire were adapted and pilot-tested; minor revisions were made for field application. Statistical analyses included principal components analysis to identify subscales; cluster analysis to identify subgroups within students; Cronbach's alpha coefficient to assess internal consistencies; Pearson product-moment correlations to assess test-retest reliabilities; and oneway ANOVA's by F&V stages of change clusters with actual F&V consumption, F&V self-efficacy subscales, F&V preferences, and F&V outcome expectations subscales to determine construct validity. RESULTS Principal components analysis from the field application indicated two subscales (precontemplation and beyond precontemplation) accounting for 39.5% of variance. Cluster analysis indicated 6 interpretable clusters; 2 (n = 63) provided responses inconsistent with the stages of change theory and 4 (n = 189) provided responses consistent with the theory. Internal consistencies and test-retest reliabilities were acceptable. Students in the "beyond precontemplation" clusters had higher levels of self-efficacy and outcome expectations regarding eating F&V. CONCLUSIONS Measuring stages of change other than the precontemplation stage in F&V consumption among elementary school children is problematic. Perhaps the theoretical concept does not apply to children, or elementary school children lack the ability to comprehend the questions measuring the concept, or the approach used was not entirely appropriate.
Improved Training of Wasserstein GANs

Generative Adversarial Networks (GANs) are powerful generative models, but suffer from training instability. The recently proposed Wasserstein GAN (WGAN) makes progress toward stable training of GANs, but sometimes can still generate only low-quality samples or fail to converge. We find that these problems are often due to the use of weight clipping in WGAN to enforce a Lipschitz constraint on the critic, which can lead to undesired behavior. We propose an alternative to clipping weights: penalize the norm of gradient of the critic with respect to its input. Our proposed method performs better than standard WGAN and enables stable training of a wide variety of GAN architectures with almost no hyperparameter tuning, including 101-layer ResNets and language models over discrete data. We also achieve high quality generations on CIFAR-10 and LSUN bedrooms.
Solving Large-Margin Hidden Markov Model Estimation via Semidefinite Programming

In this paper, we propose to use a new optimization method, i.e., semidefinite programming (SDP), to solve the large-margin estimation (LME) problem of continuous-density hidden Markov model (CDHMM) in speech recognition. First, we introduce a new constraint for LME to guarantee the boundedness of the margin of CDHMM. Second, we show that the LME problem subject to this new constraint can be formulated as an SDP problem under some relaxation conditions. Therefore, it can be solved using many efficient optimization algorithms specially designed for SDP. The new LME/SDP method has been evaluated on a speaker independent E-set speech recognition task using the ISOLET database and a connected digit string recognition task using the TIDIGITS database. Experimental results clearly demonstrate that large-margin estimation via semidefinite programing (LME/SDP) can significantly reduce word error rate (WER) over other existing CDHMM training methods, such as MLE and MCE. It has also been shown that the new SDP-based method largely outperforms the previously proposed LME optimization methods using gradient descent search.
Antipsicóticos, anticonvulsivantes, antiadrenérgicos e outras drogas: o que fazer quando o transtorno do estresse pós-traumático não responde aos inibidores seletivos da recaptação da serotonina?

OBJECTIVES: In this narrative review, we aimed to describe different pharmacological strategies for the treatment of patients with post-traumatic stress disorder who display different levels of intolerance, resistance, refractoriness, or who are unable to take to antidepressants, especially serotonin reuptake inhibitors. METHOD: We searched the ISI web of science and the PubMed for original studies focusing in the treatment of PTSD in different clinical scenarios. RESULTS: Preliminary evidence pointed towards the efficacy of drugs such as risperidone, olanzapine, lamotrigine and prazosin as strategies to be employed in the above mentioned clinical scenarios. The choice of a specific "second line" drug should take into account not only symptoms, but also pattern of comorbidities, previous response to other treatments, pharmacological interactions, side-effects, and patient's physical conditions. CONCLUSIONS: Future randomized controlled trials should be performed in order to unveil which drugs should be prescribed in the absence of adequate treatment and response to serotonin reuptake inhibitors.
Recurrent Neural Networks for Computing Pseudoinverses of Rank-Deficient Matrices

Three recurrent neural networks are presented for computing the pseudoinverses of rank-deficient matrices. The first recurrent neural network has the dynamical equation similar to the one proposed earlier for matrix inversion and is capable of Moore--Penrose inversion under the condition of zero initial states. The second recurrent neural network consists of an array of neurons corresponding to a pseudoinverse matrix with decaying self-connections and constant connections in each row or column. The third recurrent neural network consists of two layers of neuron arrays corresponding, respectively, to a pseudoinverse matrix and a Lagrangian matrix with constant connections. All three recurrent neural networks are also composed of a number of independent subnetworks corresponding to the rows or columns of a pseudoinverse. The proposed recurrent neural networks are shown to be capable of computing the pseudoinverses of rank-deficient matrices.
In-Group Identification, Social Dominance Orientation, and Differential Intergroup Social Allocation

Abstract Three varieties of differential intergroup social allocation were examined in a sample of American students as a function of degree of in-group legitimacy, self-esteem, sex, and social dominance orientation within a standard minimal-groups experimental paradigm. The results are consistent with both social identity theory and much previous research in this area: The greater the in-group identification, the greater the allocation of social value in favor of the in-group. The results are also consistent with the expectations of social dominance theory and show that, even after the effects of gender, self-esteem, and in-group identification were considered, the greater the social dominance orientation, the greater the allocation of social value in favor of the in-group. For two of the three indexes of social value, there was a statistically significant interaction between in-group identification and social dominance orientation. Subjects showing strong acceptance of their in-group classification and .
Fragile X Syndrome, Autism and Autistic Features

The relationship between fragile X syndrome and autism is reviewed. Results from a semi-structured questionnaire survey of development and behaviour in boys with fragile X syndrome, Down's syndrome and learning disability of unknown aetiology are presented. A behavioural profile characteristic of many boys with fragile X syndrome was identified which distinguished them from both other groups. Fragile X boys did not show more autism than boys with idiopathic learning disability but they did have a common autistic-like profile of communicatory and stereotypic disturbances, most notably delayed echolalia, repetitive speech and hand flapping. Boys with idiopathic learning disability showed difficulties more in areas of social functioning. Boys with Down's syndrome were characterized by fewer difficulties in social functioning and ritualistic/stereotypic tendencies but this might have been explained by subject ascertainment bias. Behavioural items distinguishing boys with fragile X significantly from both other groups retained their significance even when individuals with autism were excluded from statistical analysis. The findings provide further support for the notion of a behavioural phenotype in boys with fragile X syndrome.
A New Dataset and Method for Automatically Grading ESOL Texts

We demonstrate how supervised discriminative machine learning techniques can be used to automate the assessment of 'English as a Second or Other Language' (ESOL) examination scripts. In particular, we use rank preference learning to explicitly model the grade relationships between scripts. A number of different features are extracted and ablation tests are used to investigate their contribution to overall performance. A comparison between regression and rank preference models further supports our method. Experimental results on the first publically available dataset show that our system can achieve levels of performance close to the upper bound for the task, as defined by the agreement between human examiners on the same corpus. Finally, using a set of 'outlier' texts, we test the validity of our model and identify cases where the model's scores diverge from that of a human examiner.
Notes from the Back of the Room: Problems and Paradoxes in the Schooling of Young Black Students .

This article examines common teacher practices and black elementary-age students' responses to these practices in considering processes of social reproduction in schools. In an ethnographic study of two all-black schools, the author found that both schools expressed a strong commitment to creating a positive and self-affirming learning environment for black students, with an explicit emphasis on building self-esteem as a means of enhancing academic performance. However, both schools also unwittingly undermined that commitment by suppressing what were deemed inappropriate behaviors and conveying messages of black cultural deviance to students in the interest of discipline and conformity to particular mainstream cultural norms
Indoctrination U.? Faculty Ideology and Changes in Student Political Orientation

In the provocatively titled Indoctrination U. , David Horowitz argues that radical members of college faculties have “intruded a political agenda into the academic curriculum,” engaging in propaganda rather than scholarship and indoctrinating students rather than teaching them (Horowitz 2007, xi). Although allegations of liberal bias in academia are nothing new, the issue has gained increased attention as the result of efforts by Horowitz and the Center for the Study of the Popular Culture (CSPC) to promote the Academic Bill of Rights for American colleges and universities.
Cutting edge or cut loose? An exploration of apprentices’ experiences of workplace e-learning

There is an assumption that e-learning is considered as a valued resource with great potential. This research explores how hairdressing apprentices experience vocational e-learning and makes recommendations on how good practice can be shared. An estimated 35,000 hairdressing and barber salons account for a quarter of a million UK workers and training is predominantly work-based. This small-scale, collaborative, practitioner-based research took place in a medium-sized salon network based in the East Midlands of England and employed a cross-sectional design. Salons were equipped with and use information and communication technology. Data collection included focus groups and participant diaries. Participation was voluntary and confidentiality maintained. Participants were allocated to form three focus groups differentiated by role and location. Participants kept a two week diary. Thematic, substantive, cross-sectional analysis was used to elicit data from the focus group transcripts and diaries. Findings, authenticated and validated by participants, indicated that e-learning was perceived as an overall positive resource in supporting workplace learning. It provided a means of ‘building bridges’ with senior staff and accessing expansive learning opportunities. Where accessibility was limited and production values dominated learning, apprentices experienced difficulties.
Development of a high-resolution melting genotyping assay for the angiotensin I converting enzyme insertion/deletion polymorphism and establishment of genotype-specific reference intervals in a Danish population

Background: The serum-angiotensin I converting enzyme (s-ACE) activity is influenced by a genetic insertion/deletion (I/D) polymorphism in the ACE gene, and the resulting large interindividual variation in s-ACE limits the use of normal reference intervals in the evaluation of sarcoidosis. In this study, we developed a new method for genotyping the I/D polymorphism in ACE and established genotype-specific reference intervals in order to improve the diagnostic accuracy and the value for treatment of sarcoidosis. Methods: The new genotyping assay is based on high-resolution melting (HRM) using LCGreen + and was used to genotype 400 healthy Danish individuals. The assay was compared to a real-time polymerase chain reaction (RT-PCR) assay in a validation set of 86 samples. Enzyme activity in serum was measured using the Infinity™ ACE Liquid Stable Reagent from Thermo adapted for the ABX Pentra analyzer. Results: There was full concordance between genotyping assays. The three genotypes II, ID and DD were present with a frequency of 0.23, 0.51 and 0.26. The distribution of s-ACE values in the total population was non-Gaussian (non-parametric 95% reference interval 12.0–60.0 U/L). The median activities of the genotypes differed significantly (P<0.0001). Ninety-five per cent non-parametric reference intervals for the subpopulations were determined to 6.3–38.5, 14.0–56.0 and 23.3–71.2 U/L for II, ID and DD, respectively. Conclusion: We have developed a simple and robust method for ACE genotyping and determined genotype-specific reference intervals for s-ACE concentrations in the Danish population. The new reference intervals may increase the value of s-ACE measurements.
Modular Concurrency - A New Approach to Manageable Software

Software systems bridge the gap between the information processing needs of the world and computer hardware. As system requirements grow in complexity and hardware evolves, the gap does not necessarily widen, but it undoubtedly changes. Although today’s applications require concurrency and today’s hardware provides concurrency, programming languages remain predominantly sequential. Concurrent programming is considered too difficult and too risky to be practiced by “ordinary programmers”. Software development is moving towards a paradigm shift, following which concurrency will play a fundamental role in programming. In this paper, we introduce an approach that we believe will reduce the difficulties of developing and maintaining certain kinds of concurrent software. Building on earlier work but applying modern insights, we propose a programming paradigm based on processes that exchange messages. Innovative features include scale-free program structure, extensible modular components with multiple interfaces, protocols that specify the form of messages, and separation of semantics and deployment. We suggest that it may be possible to provide the flexibility and expressiveness of programming with processes while bounding the complexity caused by
Impact of fasting time on hepatic lipid metabolism in nutritional animal studies

Many animal studies on improvement of lipid metabolism, using dietary components, fast the animals on the final day of the feeding. Although fasting has a significant impact on lipid metabolism, its time-dependent influence is not fully understood. We examined the effects of several fasting times on lipid metabolism. Rats fed with a semisynthetic diet for 2 wk were killed after 0 (9:00 am), 6 (7:00 am–1:00 pm), 9 (0:00 am–9:00 am), and 13 h (8:00 pm–9:00 am) of fasting. Compared to the 0 h group, marked reduction of liver weight and hepatic triacylglycerol content was observed in the 9 and 13 h groups. Activities of hepatic enzymes involved in fatty acid synthesis gradually decreased during fasting. In contrast, drastic time-dependent reduction of gene expression, of the enzymes, was observed. Expression of carnitine palmitoyltransferase mRNA was higher in the fasting groups than in the 0 h group. Our study showed that fasting has a significant impact on several parameters related to lipid metabolism in rat liver. Graphical Abstract Fasting dramatically reduced mRNA expressions of enzymes and proteins related to lipogenesis in rat liver.