Miracle-dz/UniFAR-FTUs huggingface dataset:
A Clustering Method for Discovering Patterns Using Gene Regulatory Processes

Clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes (dimensions). The k-means and hierarchical as well as self-organizing maps have all been used for clustering expression profiles and a number of algorithms have been developed for expression data and applied to analyze it. These Clustering methods usually use metric distance for similarity measure. Correlation coefficient is also used but has a problem that it removes difference attributable to both the mean and the dispersion of the observations. Moreover, it may be unreasonable that every observation is assigned to one of clusters when the purpose is to find groups with similar pattern. Alter et al. [1] show that several significant eigengenes and the corresponding eigenarrays capture most of the expression information in field of genetics and some of the eigengenes represent independent regulatory programs or processes from its expression pattern across all arrays. Normalizing the data by filtering out the eigengenes (and the corresponding eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different expression. Such normalization may improve any further analysis of the expression data. Q-mode factor analysis has been used to find groups like clustering analysis and could be a good method to find patterns. However, this approach to clustering is plagued with a number of problems [3]. Genes with similar expression profiles may have something in common in their regulatory mechanisms. In this study, Q-mode factor analysis is used to model the gene regulatory processes which control genes and gene products and we modify the Q-mode factor analysis for discovering useful patterns in gene expression data. As a result of the factor modeling of gene expression data, our method can improve the result of clustering by removing noises and produce characteristic values of expression data.
SAMD9 Is an Innate Antiviral Host Factor with Stress Response Properties That Can Be Antagonized by Poxviruses

ABSTRACT We show that SAMD9 is an innate host antiviral stress response element that participates in the formation of antiviral granules. Poxviruses, myxoma virus and vaccinia virus specifically, utilize a virus-encoded host range factor(s), such as a member of the C7L superfamily, to antagonize SAMD9 to prevent granule formation in a eukaryotic initiation factor 2α (eIF2α)-independent manner. When SAMD9 is stimulated due to failure of the viral antagonism during infection, the resulting antiviral granules exhibit properties different from those of the canonical stress granules.
Customer Intentions Analysis of Twitter Based on Semantic Patterns

Intention analysis over Twitter offer organisations a fast and effective way to monitor the publics’ desires towards their brand, business, directors,etc. A wide range of features and methods for user intention analysis have been researched in recent years. Due to the nature of micro blogs posts, mining user intentions is still a challenging task. In this paper, we introduce a novel method of using semantic patterns and ontologies. Our approach combines natural language syntax and semantics analysis to identify user intention. We conduct a case study of user intentions in the commercial field. Our experimental results show the importance and effectiveness of our proposed approach for detecting customer intentions.
The AQ21 Natural Induction Program for Pattern Discovery: Initial Version and its Novel Features

The AQ21 program aims to perform natural induction, a process of generating inductive hypotheses in human-oriented forms that are easy to interpret and understand. This is achieved by employing a highly expressive representation language, attributional calculus, whose statements resemble natural language descriptions. This paper focuses on the pattern discovery mode of AQ21, which produces attributional rules that capture strong regularities in the data, but may not be fully consistent or complete with regard to the training data. AQ21 integrates several novel features, such as optimizing patterns according to multiple criteria, learning attributional rules with exceptions, generating optimized sets of alternative hypotheses, and handling data with unknown, irrelevant and/or non-applicable meta-values
Gold Doping of Silver Nanoclusters: A 26-Fold Enhancement in the Luminescence Quantum Yield.

A high quantum yield (QY) of photoluminescence (PL) in nanomaterials is necessary for a wide range of applications. Unfortunately, the weak PL and moderate stability of atomically precise silver nanoclusters (NCs) suppress their utility. Herein, we accomplished a ≥26-fold PL QY enhancement of the Ag29 (BDT)12 (TPP)4 cluster (BDT: 1,3-benzenedithiol; TPP: triphenylphosphine) by doping with a discrete number of Au atoms, producing Ag29-x Aux (BDT)12 (TPP)4 , x=1-5. The Au-doped clusters exhibit an enhanced stability and an intense red emission around 660 nm. Single-crystal XRD, mass spectrometry, optical, and NMR spectroscopy shed light on the PL enhancement mechanism and the probable locations of the Au dopants within the cluster.
Preparation and Mechanical Properties of Lignocellulosic Composite Films Based on Poplar Wood Flour and Waste Filter Paper

Novel lignocellulosic composite films (LCFs) based on poplar wood flour (PWF) and waste filter paper (WFP) were developed with 1-allyl-3-methylimidazolium chloride ([Amim]Cl) as green solvent. Scanning electron microscopy revealed that the dissolved part acted as the matrix that combined with the insoluble part and reinforced the LCFs. Under the same preparation conditions, there was an increased amount of the insoluble part with an increased amount of PWF. The PWF and WFP mass ratio was a key parameter that influenced the solubility of the raw materials. The differences in the grammage, thickness, and mechanical properties among the groups were related to the dissolution extent of the raw materials. Group A (100 wt% WFP) had the best mechanical properties because of the highest dissolution of cellulose. When the PWF and WFP mass ratio increased, the mechanical properties of the samples decreased and surface bonding became poor. Consequently, the TS of group F (100 wt% PWF) was the lowest. The elongation and elastic modulus showed the same trend as that of the TS.
Inflammatory Biomarkers in Patients with Posttraumatic Stress Disorder Caused by Myocardial Infarction and the Role of Depressive Symptoms

Objective: Inflammation might link posttraumatic stress disorder (PTSD) with an increased risk of cardiovascular events. We explored the association between PTSD and inflammatory biomarkers related to cardiovascular morbidity and the role of co-morbid depressive symptoms in this relationship. Methods: We investigated 15 patients with interviewer-rated PTSD caused by myocardial infarction (MI) and 29 post-MI patients with no PTSD. All patients completed the depression subscale of the Hospital Anxiety and Depression Scale and had blood collected to determine inflammatory markers of increased cardiovascular risk. Results: Controlling for demographic and medical covariates, patients with PTSD had higher leptin levels than patients with no PTSD (p = 0.038, explained variance 10.4%); this difference became nonsignificant when controlling for depressive symptoms. After controlling for depressive symptoms, PTSD patients had higher interleukin-6 (p = 0.041; explained variance 10%), lower C-reactive protein (p = 0.022, explained variance 12.1%), and lower soluble CD40 ligand (p = 0.016, explained variance 13.4%) than patients without PTSD. After controlling for PTSD status, depressive symptoms correlated with soluble CD40 ligand (r = 0.45, p = 0.002) and with C-reactive protein (r = 0.29, p < 0.07). Conclusions: The findings provide further evidence for altered inflammation in PTSD. Comorbid depressive symptoms ought to be considered to disentangle the unique associations of PTSD caused by MI and systemic inflammation.
Aerobic and Anaerobic Power in Relation to Age and Physical Activity in 354 Men Aged 20–88 Years

We examined simultaneously the influence of age as well as both current and historical habitual physical activity (PA) on aerobic (physical working capacity - PWC) and anaerobic (Pmax) power in 354 men aged 20.2-87.6 yrs. All the participants performed the graded aerobic exercise test and 8-second explosive power tests on a bicycle ergometer. Current leisure time physical activity (LTPA) and lifetime historical LTPA were assessed. The decline in Pmax/kg (10.3% per decade) was higher than in PWC/kg (7.5% per decade). Correlation coefficients for current LTPA and aerobic indices were higher than for current LTPA and anaerobic indices. In a multiple stepwise regression, current LTPA had the main effect on PWC/kg, whereas age had the main effect on Pmax/kg. Aerobic power was related to all measures of historical PA questionnaire, while anaerobic power - only to those historical measures which pertained to adolescence and younger years of adulthood. We conclude that the age-associated decline in anaerobic power is steeper than that of aerobic power. Habitual endurance-type LTPA increases aerobic but not anaerobic fitness throughout the adult lifespan. Anaerobic fitness indices are higher in young active vs sedentary men but this difference is not discernible as early as in the middle age.
Assessing Perceived Stress in Medical Personnel: In Search of an Appropriate Scale for the Bengali Population

Background: The occurrence of stress and stress related anxiety and depression in medical personnel are being increasingly reported in literature. The perceived stress scale (PSS) is the most widely used psychological instrument for measuring the perception of stress. It is needed to assess perceived stress in our population using appropriately translated version of PSS. The objectives of study were to prepare a Bengali version of PSS-10 and to establish its psychometric properties in the study population. Materials and Methods: The study was conducted in a teaching hospital among medical students and interns (N=37). The translated Bengali version and the original English version of PSS-10 were separately handed over to the individual subjects. The scores were compared across different subgroups and psychometric properties of the translated version were assessed using SPSS 16. Results: Internal consistency of PSS English (α=0.79) and Bengali (α=0.80) was satisfactory. Intra-rater reliability was adequate (κ>0.5) for most of the items, but showed an inadequate value (κ<0.5) for four items on the scale. After deleting these four items from the Bengali version, a new six-item PSS in Bengali was derived that showed good internal consistency (α=0.699). Conclusion: This new version needs to be validated in a larger study population. Perceived stress score using PSS-10 was considerably high in our study population, although there was no significant difference between the subgroups (male/female, intern/student).
Fabrication et caractérisation des matériaux composites lamellaires à matrice Ti et TA6V

Apprenant de la nature, les architectures specifiques de certains organismes vivants sont devenues l'une des idees dominantes dans le developpement de nouvelles generations de materiaux synthetiques. Dans cette optique, la structure lamellaire de la nacre peut servir de modele pour la fabrication de nouveaux materiaux composites a matrices metalliques. Un nouveau procede de metallurgie des poudres, appelee metallurgie des poudres « plaquettes » (FPM), a ainsi ete developpee pour fabriquer des materiaux composites a matrice metallique a structure lamellaire.L’objectif de ce travail de these est l'utilisation du procede FPM (en utilisant le broyage mecanique (BM) et le frittage SPS), pour la fabrication de materiaux architectures lamellaires et bioinspires de structure nacre. Nous avons montre la possibilite de fabriquer, a partir de poudre plaquettes, des materiaux lamellaires anisotropes monolithiques a base de titane et d’alliages de titane ainsi que des materiaux composites Ti/C. Nous avons egalement montre les avantages de l'architecture multicouches sur l'amelioration des proprietes mecaniques (durete) du Ti et de TA6V avec une anisotropie de la durete entre les sections transversale et longitudinale. L’augmentation de la durete de ces materiaux lamellaires, par rapport aux materiaux non-lamellaire, est liee principalement a l'epaisseur des "plaquettes" qui est controlee par le temps de BM, ainsi que par l’effet de la microstructure affinee et de l’ecrouissage du materiau lamellaire.Nous avons egalement montre la possibilite de fabriquer des materiaux composites lamellaires in-situ Ti/TiC par BM (en presence d'acide stearique) et frittage SPS, avec la possibilite de controler la teneur en TiC en jouant sur les conditions de BM (temps BM et taux d’acide stearique). Ce materiau composite permet une amelioration de la durete et du module de Young attribuee a la phase de TiC formee.
G-Images: Towards Multilevel Unsupervised Image Segmentation

We present two novel approaches to initiating unsupervised segmentation of digital images using an algorithm that utilises the concept of information theory. The first approach uses Information Gain and the second is based on the Gini Index. In the two approaches, Information Gain and the Gini Index are calculated locally, at a pixel level, resulting in a G-image where high G value occurs at contrasting boundaries and zero G value within homogeneous regions. Subsequently, a multi-level thresholding approach based on the G-image is used to obtain the optimal segmentation results. The segmentation is guided by both local and global parametric constraints. Comparative, visual, evaluation on real and artificial images shows promising results.
Liver dysfunction after intestinal bypass.

To the Editor. — The article by Dr Ames et al on liver dysfunction (235:1249, 1976) points up a problem in the long-term postoperative follow-up of intestinal bypass patients, which is, at best, poorly understood and often ignored, sometimes with serious consequences. Thus, hepatic failure is considered a serious risk to intestinal bypass for morbid obesity. There is reason to believe that hepatic steatosis is a consequence of carbohydrate-protein imbalance, not a simple protein deficiency, probably exactly like the changes seen in the early stages of kwashiorkor disease. Simple starvation does not produce these changes. The morbidly obese already have some degree of hepatic steatosis at the time of their bypass, and this, in my experience, is not directly related to the degree of obesity but, I suspect, is related to the ratio of carbohydrate to protein these people have eaten to become so obese and to maintain their obesity. Carbohydrates
Delay Discrete Dynamical Models for Genetic Regulatory Networks

In this paper, we study the problem of constructing a regulatory network of yeast in oxidative stress process. Discrete Dynamic System (DDS) model has been introduced in describing Gene Regulatory Networks (GRNs). However, delay effect was not taken into consideration within the model. A Time-delay DDS model composed of linear difference equations is developed to represent temporal interactions among significantly expressed genes. Interpolation and re-sampling are imposed to equalize the non-uniformity of sampling time points. Statistical significance plays an active role in obtaining the optimal interaction matrix of GRNs. The constructed gene network using linear multiple regression has a very good match with the original data. Simulation results are given to demonstrate the effectiveness of our proposed model.
Heteroatom-doped carbonaceous electrode materials for high performance energy storage devices

The development of cost affordable and efficient catalysts for speeding up electrode reactions is key for boosting up the commercial viability of fuel cells, metal air batteries and other energy production and storage devices. Although state-of-the-art platinum demonstrates excellent performance as an electrode material, its susceptibility to poisoning, high cost and limited availability have blocked the road for large scale commercialization of Pt based energy conversion/storage devices. In this connection carbon nanomaterials are attractive choices on account of their corrosion resistant properties, affordable cost, widespread availability, unique surface features, environmentally acceptable nature and practical capability for addressing the global energy challenge. Moreover, the catalytic role of carbon nanomaterials is expected to be further upgraded by the incorporation of dopants into their framework. Hence, the current review article is at the heart of underlining the recent progress achieved under the umbrella of heteroatom-doped carbons to accelerate reactions in advanced energy generation devices.
A review of the biomedical innovations for healthy longevity

Keywords: longevity ; aging ; biomarkers ; geroprotectors ; epigenetics ; transcriptomics Reference EPFL-ARTICLE-227576doi:10.18632/aging.101163View record in Web of Science Record created on 2017-05-01, modified on 2017-05-26
Efficacy of Vonoprazan for Proton Pump Inhibitor-Resistant Reflux Esophagitis

Background: Vonoprazan (VPZ) is a novel potassium-competitive acid blocker that may be clinically beneficial for proton pump inhibitor (PPI)-resistant reflux esophagitis (RE). The aim of this study was to investigate the efficacies of VPZ therapy at 20 mg for 4 weeks in patients with PPI-resistant RE and VPZ maintenance therapy at 10 mg for 8 weeks in patients who have been successfully treated. Methods: Subjects comprised 24 patients with PPI-resistant RE (Los Angeles classification grade A/B/C/D: 3/7/11/3). After confirming PPI-resistant RE by endoscopy, 20 mg VPZ was administered. Endoscopy was performed 4 weeks after the initiation of VPZ. Symptoms were evaluated using the frequency scale for the symptoms of gastroesophageal reflux disease (FSSG). Maintenance therapy with 10 mg VPZ was performed and endoscopy was conducted after 8 weeks. Results: In 21 (87.5%) out of 24 patients, esophageal mucosal breaks were successfully treated by 20 mg VPZ. The median FSSG score was significantly lower on days 1-7, 14, and 28 after the initiation of VPZ than before its administration. Maintenance therapy with 10 mg VPZ prevented the relapse of esophageal mucosal breaks in 16 (76.2%) out of 21 patients. Conclusion: VPZ was effective for most patients with PPI-resistant RE.
Less Is More: Burkholderia pseudomallei and Chronic Melioidosis

ABSTRACT The Gram-negative bacterium Burkholderia pseudomallei is the causative agent of melioidosis, a serious infectious disease of humans and animals. Once considered an esoteric tropical disease confined to Southeast Asia and northern Australia, research on B. pseudomallei has recently gained global prominence due to its classification as a potential bioterrorism agent by countries such as the United States and also by increasing numbers of case reports from regions where it is not endemic. An environmental bacterium typically found in soil and water, assessing the true global prevalence of melioidosis is challenged by the fact that clinical symptoms associated with B. pseudomallei infection are extremely varied and may be confused with diverse conditions such as lung cancer, tuberculosis, or Staphyloccocus aureus infection. These diagnostic challenges, coupled with lack of awareness among clinicians, have likely contributed to underdiagnosis and the high mortality rate of melioidosis, as initial treatment is often either inappropriate or delayed. Even after antibiotic treatment, relapses are frequent, and after resolution of acute symptoms, chronic melioidosis can also occur, and the symptoms can persist for months to years. In a recent article, Price et al. [mBio 4(4):e00388-13, 2013, doi:10.1128/mBio.00388-13] demonstrate how comparative genomic sequencing can reveal the repertoire of genetic changes incurred by B. pseudomallei during chronic human infection. Their results have significant clinical ramifications and highlight B. pseudomallei’s ability to survive in a wide range of potential niches within hosts, through the acquisition of genetic adaptations that optimize fitness and resource utilization.
Applied Functional Data Analysis

Chapter 17, “Bootstrapping,” provides an overview of the nonparametric bootstrap method as a way to obtain precision and the distribution (and thus the signi cance point of a test statistic), under the assumptions of independence of observation vectors and continuity of cumulative distribution function. Bootstrapping from residuals, con dence intervals for parametric functions, bootstrapping in the multiple regression model, and testing about the variance are discussed for the univariate case. Testing for the mean vector, testing for equality of two mean vectors, bootstrapping in multivariate regression, testing that the covariance is a speci ed matrix, and testing the equality of two covariance matrices are discussed for the multivariate case. Chapter 18, “Imputing Missing Data,” proposes single stochastic imputation for missing data and use of the “completed” dataset for inference. Cases of the multiple regression model and multivariate data are considered. For multivariate data, imputed values are obtained by  rst obtaining the best linear predictors of the missing observations, then adding random errors to them to obtain imputed values. Estimates of the mean vector and covariance matrix are obtained from the “completed” dataset, which has imputed values in place of missing observations. Bootstrap methods are given to obtain the estimate of the covariances of these estimators. Signi cance levels from the bootstrap distribution are suggested for improving inference about the mean. The author does not discuss multiple imputation, which has the advantages of single imputation, attains large-sample optimality of ML estimation, and is robust to model misspeci cation (Rubin 2002). I would have liked to see (a) a more detailed discussion on transformations to achieve normality for multivariate data, and more on graphical methods for assessing multivariate normality and detecting multivariate outliers; (b) in-depth discussion on the interpretation of test results other than signi cance levels, including adjustment of signi cance levels in the case of multiple tests (Hsu 1996); and (c) comparisons on the performance of proposed tests and methodologies with other existing ones. In conclusion, this is a great book for a  rst graduate course in multivariate analysis, because it covers the standard topics in “classical” normal theory approach to multivariate analysis. The “customized” SAS codes provide nice support for the implementation of the suggested methods and make this book a great reference for practitioners. This is a book with a data analytic approach and one of the best references for its level.