Recovering Multiple Nonnegative Time Series From a Few Temporal Aggregates

Motivated by electricity consumption metering, we extend existing nonnegative matrix factorization (NMF) algorithms to use linear measurements as observations, instead of matrix entries. The objective is to estimate multiple time series at a fine temporal scale from temporal aggregates measured on each individual series. Furthermore, our algorithm is extended to take into account individual autocorrelation to provide better estimation, using a recent convex relaxation of quadratically constrained quadratic program. Extensive experiments on synthetic and real-world electricity consumption datasets illustrate the effectiveness of our matrix recovery algorithms

Do Not Think Carefully? Re-examining the Effect of Unconscious Thought on Deception Detection

Several recent studies have examined the effect of unconscious thinking on deception detection with the hypothesis that unconscious thought increases the ability to discriminate between truth and deception, but these studies yielded conflicting results. The present study aimed to re-examine the effect of unconscious thinking and extend it by adopting both verbal and non-verbal/paraverbal stimuli. We hypothesized that unconscious thought leads to a higher accuracy rate than immediate decision and conscious thought when judging non-verbal/paraverbal stimuli, but not when judging verbal stimuli. In Study 1, we compared unconscious thought with immediate decision by using both video and audio stimuli. In Study 2, we compared unconscious thought with conscious thought by using both video and text stimuli. The results showed that when detecting deception vs. truth, (1) unconscious thought was not better than immediate decision on deception detection in both audio and video conditions (Study 1), and (2) unconscious thought was not better than conscious thought in both video and text conditions (Study 2). The Bayes factor of both studies also showed substantial evidence for null hypothesis (H0) relative to alternative hypothesis (H1). The implications and limitations of the present study are discussed

Finite-time synchronization of drive-response systems via periodically intermittent adaptive control

In this paper, the finite-time synchronization between two complex dynamical networks via the periodically intermittent adaptive control and periodically intermittent feedback control is studied. The finite-time synchronization criteria are derived based on finite-time stability theory, the differential inequality and the analysis technique. Since the traditional synchronization criteria for some models are improved in the convergence time by using the novel periodically intermittent adaptive control and periodically intermittent feedback control , the results of this paper are important. Numerical examples are finally presented to illustrate the effectiveness and correctness of the theoretical results.National Natural Science Foundation of China (Grant No.61174216, No. 61273183, No.6134028 and No. 61374085) and the Doctoral Scientific Foundation of China Three Gorges University (Grant No. 0620120132).http://www.elsevier.com/locate/jfranklinhb201

Demineralized Bone Matrix Combined Bone Marrow Mesenchymal Stem Cells, Bone Morphogenetic Protein-2 and Transforming Growth Factor-β3 Gene Promoted Pig Cartilage Defect Repair

Objectives To investigate whether a combination of demineralized bone matrix (DBM) and bone marrow mesenchymal stem cells (BMSCs) infected with adenovirus-mediated- bone morphogenetic protein (Ad-BMP-2) and transforming growth factor-β3 (Ad-TGF-β3) promotes the repair of the full-thickness cartilage lesions in pig model. Methods BMSCs isolated from pig were cultured and infected with Ad-BMP-2(B group), Ad-TGF-β3 (T group), Ad-BMP-2 + Ad-TGF-β3(BT group), cells infected with empty Ad served as a negative group(N group), the expression of the BMP-2 and TGF-β3 were confirmed by immunofluorescence, PCR, and ELISA, the expression of SOX-9, type II collagen(COL-2A), aggrecan (ACAN) in each group were evaluated by real-time PCR at 1w, 2w, 3w, respectively. The chondrogenic differentiation of BMSCs was evaluated by type II collagen at 21d with immunohistochemical staining. The third-passage BMSCs infected with Ad-BMP-2 and Ad-TGF-β3 were suspended and cultured with DBM for 6 days to construct a new type of tissue engineering scaffold to repair full-thickness cartilage lesions in the femur condyles of pig knee, the regenerated tissue was evaluated at 1,2 and 3 months after surgery by gross appearance, H&E, safranin O staining and O\u27driscoll score. Results Ad-BMP-2 and Ad-TGF-β3 (BT group) infected cells acquired strong type II collagen staining compared with Ad-BMP-2 (B group) and Ad-TGF-β3 (T group) along. The Ad-BMP-2 and Ad-TGF-β3 infected BMSCs adhered and propagated well in DBM and the new type of tissue engineering scaffold produced hyaline cartilage morphology containing a stronger type II collagen and safranin O staining, the O\u27driscoll score was higher than other groups. Conclusions The DBM compound with Ad-BMP-2 and Ad-TGF-β3 infected BMSCs scaffold has a good biocompatibility and could well induce cartilage regeneration to repair the defects of joint cartilage. This technology may be efficiently employed for cartilage lesions repair in vivo

Expression of autophagy and apoptosis-related factors in the periodontal tissue of experimental diabetic rats: a histomorphometric, microtomographic and immunohistochemical study

Objective This study aimed to investigate the expression of autophagy-related factors microtubule-associated protein l light chain 3 (LC3) and the apoptosis-related factors BCL2-associated X protein (Bax) and B cell lymphoma-2 (Bcl-2) in the periodontal tissue of experimental diabetic rats. These data were used to explore the potential mechanism in diabetes-induced periodontal tissue lesions. Methods A total of 32 Sprague Dawley (SD) rats were randomly assigned into diabetes (group D, n = 16) and control groups (group N, n = 16). The diabetic group was induced by intraperitoneal injection of 1% streptozotocin (STZ, 60 mg/kg) and the control group was injected with citrate buffer (0.1mol/L). Rats were sacrificed after 4 and 8 weeks of feeding and collected as D1, N1 groups and D2, N2 groups, and the maxilla were retained for analysis. The changes in periodontal tissue structure were observed by hematoxylin-eosin (HE) staining. The expression and distribution of LC3, Bax and Bcl-2 in the periodontium of the rats was detected by immunohistochemical (SP) staining. Results Diabetic rats showed several changes compared to control animals including sparse alveolar bone trabecular structure, loss of the lamina dura and absorption of the local alveolar bone. The positive expression level of LC3 in the gingival epithelial, periodontal ligament and alveolar bone of group D1 was significantly higher than in the N1, N2 and D2 groups (P < 0.05). The level of Bax expression in the group D2 rats was significantly higher than those in the N1, N2 and D1 groups (P < 0.05), while the positive degree of Bcl-2 was significantly lower than those of other groups (P < 0.001). LC3 was negatively correlated with Bax and was irrelevant with Bcl-2; Bcl-2 was not correlated with Bax. Conclusions The expression of LC3, Bax and Bcl-2 changes in the periodontal tissue of diabetic rats may indicate that autophagy and apoptotic are involved in the process of periodontal tissue damage in diabetic rats. These changes may be one of the mechanisms of periodontal tissue lesions

Lineage-specific accelerated sequences underlying primate evolution

Understanding the mechanisms underlying phenotypic innovation is a key goal of comparative genomic studies. Here, we investigated the evolutionary landscape of lineage-specific accelerated regions (LinARs) across 49 primate species. Genomic comparison with dense taxa sampling of primate species significantly improved LinAR detection accuracy and revealed many novel human LinARs associated with brain development or disease. Our study also yielded detailed maps of LinARs in other primate lineages that may have influenced lineage-specific phenotypic innovation and adaptation. Functional experimentation identified gibbon LinARs, which could have participated in the developmental regulation of their unique limb structures, whereas some LinARs in the Colobinae were associated with metabolite detoxification which may have been adaptive in relation to their leaf-eating diet. Overall, our study broadens knowledge of the functional roles of LinARs in primate evolution

Diagnostic Yields of Trio-WES Accompanied by CNVseq for Rare Neurodevelopmental Disorders

ObjectiveThis study is to investigate the diagnostic yield of the combination of trio whole exome sequencing (Trio-WES) and copy number variation sequencing (CNVseq) for rare neurodevelopmental disorders (NDDs).MethodsClinical data from consecutive pediatric patients who were diagnosed with rare NDDs that were suspected to be monogenic disorders, who were admitted to our hospital from April 2017 to March 2019, and who underwent next generation sequencing (NGS) were extracted from the medical records. Patients for whom Trio-WES and CNVseq data were available were enrolled in this study. Sanger sequencing was applied for the validation of the variants identified by Trio-WES. Sequence alignment and structural modeling were conducted for analyzing the possibility of the variants in the onset of the NDDs.ResultsIn total, 54 patients were enrolled in this study, with the median age of 15 (8–26) months. A total of 242 phenotypic abnormalities belonging to 20 different systems were identified in the cohort. Twenty-four patients were diagnosed by Trio-WES, eight patients were diagnosed by CNVseq, and one case was identified by both WES and CNVseq. Compared with Trio-WES, the diagnosis rate of Trio-WES accompanied by CNVseq was significantly higher (P = 0.016). Trio-WES identified 36 variants in 26 different genes, among which 27 variants were novel. CNVseq detected four duplications and eight deletions, ranging from 310 kb to 23.27 Mb. Our case examples demonstrated the high heterogeneity of NDDs and showed the challenges of rare NDDs for physicians.ConclusionThe significantly higher diagnosis rate of Trio-WES accompanied by CNVseq makes this strategy a potential alternative to the most widely used approaches for pediatric children with rare and undiagnosed NDDs

Association between XPF Polymorphisms and Cancer Risk: A Meta-Analysis

Background: Xeroderma pigmentosum complementation group F (XPF or ERCC4) plays a key role in DNA repair that protects against genetic instability and carcinogenesis. A series of epidemiological studies have examined associations between XPF polymorphisms and cancer risk, but the findings remain inconclusive. Methodology/Principal Findings: In this meta-analysis of 47,639 cancer cases and 51,915 controls, by searching three electronic databases (i.e., MEDLINE, EMBASE and CNKI), we summarized 43 case-control studies from 29 publications on four commonly studied polymorphisms of XPF (i.e., rs1800067, rs1799801, rs2020955 and rs744154), and we did not find statistical evidence of any significant association with overall cancer risk. However, in stratification analyses, we found a significant association of XPF-rs1799801 with a reduced cancer risk in Caucasian populations (4,845 cases and 5,556 controls; recessive model: OR = 0.87, 95% CI = 0.76–1.00, P = 0.049, P = 0.723 for heterogeneity test, I2 = 0). Further genotype-phenotype correlation analysis showed that the homozygous variant CC genotype carriers had higher XPF expression levels than that of the TT genotype carriers (Student’s t test for a recessive model: P = 0.046). No publication bias was found by using the funnel plot and Egger’s test. Conclusion: This meta-analysis suggests a lack of statistical evidence for the association between the four XPF SNPs and overall risk of cancers. However, XPF-rs1799801 may be associated with cancer risk in Caucasian populations, which needs to be further validated in single large, well-designed prospective studies

Reconstitution et prédiction de séries temporelles avec la factorisation de matrice nonnégative augmentée de régression appliquée à la consommation électrique

We are interested in the recovery and prediction of multiple time series from partially observed and/or aggregate data.Motivated by applications in electricity network management, we investigate tools from multiple fields that are able to deal with such data issues.After examining kriging from spatio-temporal statistics and a hybrid method based on the clustering of individuals, we propose a general framework based on nonnegative matrix factorization.This frameworks takes advantage of the intrisic correlation between the multivariate time series to greatly reduce the dimension of the parameter space.Once the estimation problem is formalized in the nonnegative matrix factorization framework, two extensions are proposed to improve the standard approach.The first extension takes into account the individual temporal autocorrelation of each of the time series.This increases the precision of the time series recovery.The second extension adds a regression layer into nonnegative matrix factorization.This allows exogenous variables that are known to be linked with electricity consumption to be used in estimation, hence makes the factors obtained by the method to be more interpretable, and also increases the recovery precision.Moreover, this method makes the method applicable to prediction.We produce a theoretical analysis on the framework which concerns the identifiability of the model and the convergence of the algorithms that are proposed.The performance of proposed methods to recover and forecast time series is tested on several multivariate electricity consumption datasets at different aggregation level.Nous sommes intéressé par la reconstitution et la prédiction des séries temporelles multivariées à partir des données partiellement observées et/ou agrégées.La motivation du problème vient des applications dans la gestion du réseau électrique.Nous envisageons des outils capables de résoudre le problème d'estimation de plusieurs domaines.Après investiguer le krigeage, qui est une méthode de la litérature de la statistique spatio-temporelle, et une méthode hybride basée sur le clustering des individus, nous proposons un cadre général de reconstitution et de prédiction basé sur la factorisation de matrice nonnégative.Ce cadre prend en compte de manière intrinsèque la corrélation entre les séries temporelles pour réduire drastiquement la dimension de l'espace de paramètres.Une fois que le problématique est formalisé dans ce cadre, nous proposons deux extensions par rapport à l'approche standard.La première extension prend en compte l'autocorrélation temporelle des individus.Cette information supplémentaire permet d'améliorer la précision de la reconstitution.La deuxième extension ajoute une composante de régression dans la factorisation de matrice nonnégative.Celle-ci nous permet d'utiliser dans l'estimation du modèle des variables exogènes liées avec la consommation électrique, ainsi de produire des facteurs plus interprétatbles, et aussi améliorer la reconstitution.De plus, cette méthod nous donne la possibilité d'utiliser la factorisation de matrice nonnégative pour produire des prédictions.Sur le côté théorique, nous nous intéressons à l'identifiabilité du modèle, ainsi qu'à la propriété de la convergence des algorithmes que nous proposons.La performance des méthodes proposées en reconstitution et en prédiction est testé sur plusieurs jeux de données de consommation électrique à niveaux d'agrégation différents