Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution of Archaea in a Black Smoker Chimney Structure

ABSTRACT Archaeal community structures in microhabitats in a deep-sea hydrothermal vent chimney structure were evaluated through the combined use of culture-independent molecular analyses and enrichment culture methods. A black smoker chimney was obtained from the PACMANUS site in the Manus Basin near Papua New Guinea, and subsamples were obtained from vertical and horizontal sections. The elemental composition of the chimney was analyzed in different subsamples by scanning electron microscopy and energy-dispersive X-ray spectroscopy, indicating that zinc and sulfur were major components while an increased amount of elemental oxygen in exterior materials represented the presence of oxidized materials on the outer surface of the chimney. Terminal restriction fragment length polymorphism analysis revealed that a shift in archaeal ribotype structure occurred in the chimney structure. Through sequencing of ribosomal DNA (rDNA) clones from archaeal rDNA clone libraries, it was demonstrated that the archaeal communities in the chimney structure consisted for the most part of hyperthermophilic members and extreme halophiles and that the distribution of such extremophiles in different microhabitats of the chimney varied. The results of the culture-dependent analysis supported in part the view that changes in archaeal community structures in these microhabitats are associated with the geochemical and physical dynamics in the black smoker chimney.
Interaction association analysis of imputed SNPs in case control and longitudinal studies

A new method is described to assess the interactions of imputed SNPs (single nucleotide polymorphisms) in case-control and cohort studies, properly incorporating SNP imputation uncertainty in the likelihood model. Using simulation studies and analysis of real data obtained from the Framingham study cohort, we compare the performance of this new method to the DOSAGE and NAIVE (also known as Best-Guess) methods, developed in the context of single SNP and extended to SNP-by-SNP interaction. The results show that only our new method is unbiased under all examined scenarios regarding allele frequencies, imputation uncertainty degree and interaction effect size. In addition, our method achieves at least as much power as the other two, and exceeds their statistical power in certain cohort analysis situations. This method has been implemented in C-code and integrated into R software, and is fast enough to perform Genome Wide Interaction Studies (GWIS) with hundreds of thousand of interactions. Introduction Genome-wide association studies (GWAS) have become very popular in the last decade as the power of genotyping technology has increased. It is now feasible to conduct studies with a million Single Nucleotide Polymorphisms (SNP), spread throughout the whole genome. However, to date, GWAS have identified only a small proportion of heritability in most of the common complex diseases [1]. For example, it has been
Predicting the effects of common levels of variability on flow processing systems

The implementation of flow processing is essential to the successful application of lean manufacturing practices since it provides the infrastructure for pull production to take place and the focused elimination of waste. With the adoption of lean practices into a broader range of production environments there is an increasing need for flow processing to operate under a wider range of conditions particularly with respect to the sources and levels of variability that exist. In order to ensure efficient flow processing under such conditions a range of methods has been developed for both reducing levels of variability and for managing the effects of variability. However, ensuring the effective use of each of these methods requires detailed knowledge of the effects this variability has on the resource requirements of individual workstations. The current paper presents a methodology for developing predictive models that can be used to quantitatively estimate the levels of blocking and waiting that occur on individual workstations along a flow processing line. The methodology presented makes use of discrete event simulation to generate data from which estimating models are derived that relate %blocking and %waiting arising at individual workstations with the coefficient of variation of their job cycle time distributions.
Does the patient's position influence the detection of detrusor overactivity?

The demonstration of preoperative detrusor overactivity (DO) with associated overactive bladder symptoms (OAB) is known to have an adverse effect on surgery performed for stress incontinence or for prostatic obstruction. The purpose of this review is to examine the best position, when filling the bladder during urodynamics, to demonstrate detrusor overactivity and reproduce the OAB symptoms, when the demonstration of DO might be important.
Domain compliance and elastic power transmission in rotary FOF1-ATPase

The 2 nanomotors of rotary ATP synthase, ionmotive FO and chemically active F1, are mechanically coupled by a central rotor and an eccentric bearing. Both motors rotate, with 3 steps in F1 and 10–15 in FO. Simulation by statistical mechanics has revealed that an elastic power transmission is required for a high rate of coupled turnover. Here, we investigate the distribution in the FOF1 structure of compliant and stiff domains. The compliance of certain domains was restricted by engineered disulfide bridges between rotor and stator, and the torsional stiffness (κ) of unrestricted domains was determined by analyzing their thermal rotary fluctuations. A fluorescent magnetic bead was attached to single molecules of F1 and a fluorescent actin filament to FOF1, respectively. They served to probe first the functional rotation and, after formation of the given disulfide bridge, the stochastic rotational motion. Most parts of the enzyme, in particular the central shaft in F1, and the long eccentric bearing were rather stiff (torsional stiffness κ > 750 pNnm). One domain of the rotor, namely where the globular portions of subunits γ and ε of F1 contact the c-ring of FO, was more compliant (κ ≅ 68 pNnm). This elastic buffer smoothes the cooperation of the 2 stepping motors. It is located were needed, between the 2 sites where the power strokes in FO and F1 are generated and consumed.
Towards efficient hierarchical designs by ratio cut partitioning

A partitioning approach called ratio cut is proposed. The authors demonstrate that the ratio cut algorithm can locate the clustering structures in the circuit. Finding the optimal ratio cut is NP-complete. However, in certain cases the ratio cut can be solved by linear programming techniques via the multicommodity flow problem. They also propose a fast heuristic algorithm running in linear time with respect to the number of pins in the circuit. Experiments show good results in all tested cases, and as much as 70% improvement over the Kernighan-Lin algorithm in terms of the proposed ratio metric. <<ETX>>
Prediction of Suspect Location Based on Spatiotemporal Semantics

The prediction of suspect location enables proactive experiences for crime investigations and offers essential intelligence for crime prevention. However, existing studies have failed to capture the complex social location transition patterns of suspects and lack the capacity to address the issue of data sparsity. This paper proposes a novel location prediction model called CMoB (Crime Multi-order Bayes model) based on the spatiotemporal semantics to enhance the prediction performance. In particular, the model groups suspects with similar spatiotemporal semantics as one target suspect. Then, their mobility data are applied to estimate Markov transition probabilities of unobserved locations based on a KDE (kernel density estimating) smoothing method. Finally, by integrating the total transition probabilities, which are derived from the multi-order property of the Markov transition matrix, into a Bayesian-based formula, it is able to realize multi-step location prediction for the individual suspect. Experiments with the mobility dataset covering 210 suspects and their 18,754 location records from January to June 2012 in Wuhan City show that the proposed CMoB model significantly outperforms state-of-the-art algorithms for suspect location prediction in the context of data sparsity.
Noninvasive Corneal Image-Based Gaze Measurement System

Gaze tracking is an important technology as the system can give information about a person from what and where the person is seeing. There have been many attempts to make robust and accurate gaze trackers using either monitor or wearable devices. However, those contraptions often require fine individual calibration per session and/or require a person wearing a device, which may not be suitable for certain situations. In this paper, we propose a robust and a completely noninvasive gaze tracking system that involves neither complex calibrations nor the use of wearable devices. We achieve this via direct eye reflection analysis by building a real-time system that effectively enables it. We also show several interesting applications for our system including experiments with young children.
Veiled, voluminous, and devalued: Narrative stories about low‐income women from Brazil, Egypt, and Colombia

The first purpose of this article is to argue the significance of using international and culturally diverse exemplars in developing nursing knowledge. The second is to identify some urgent priorities in the developmnt of nursing knowledge, particularly as related to women's health. The lived experiences of three women from Brazil, Egypt, and Colombia who are in low-income, devalued, but important jobs are presented through their voices. These storied accounts highlight nursing's mission in dealing with the marginalized client as a human being whose context is historical and sociocultural. The implications for knowledge development as driven by international exemplars, diverse experiences, and narration of stories are discussed.
Clinical significance of minimal residual disease in patients with acute leukaemia undergoing haematopoietic stem cell transplantation

In patients with acute leukaemia, the relative risk of relapse influences the choice between chemotherapy and haematopoietic stem cell transplantation (HSCT). The demonstration that minimal residual disease (MRD) is the strongest overall prognostic indicator and can identify patients who are unlikely to be cured by standard chemotherapy has added a powerful new factor to consider when making this decision. There is substantial data indicating that the likelihood of relapse after transplant is directly correlated with levels of MRD before transplant. This knowledge can be used to adjust the timing of HSCT, and guide the selection of donor, conditioning regimen, and post‐HSCT strategies to maximize the graft‐versus‐leukaemia effect. Because MRD emerging post‐transplant carries a dire prognosis, its detection can trigger withdrawal of immunosuppression, additional cellular and molecular therapies, or preparations for a second HSCT. Although it is not yet clear whether any of these actions will significantly improve outcome, it is likely that they will be most effective for patients with a relatively low tumour burden, who can be identified only through MRD testing. In this article, we review the clinical significance of MRD in the context of autologous and allogeneic HSCT.
Understanding climate change projections for precipitation over western Europe with a weather typing approach

Precipitation over western Europe (WE) is projected to increase (decrease) roughly northward (equatorward) of 50°N during the 21st century. These changes are generally attributed to alterations in the regional large‐scale circulation, e.g., jet stream, cyclone activity, and blocking frequencies. A novel weather typing within the sector (30°W–10°E, 25–70°N) is used for a more comprehensive dynamical interpretation of precipitation changes. A k‐means clustering on daily mean sea level pressure was undertaken for ERA‐Interim reanalysis (1979–2014). Eight weather types are identified: S1, S2, S3 (summertime types), W1, W2, W3 (wintertime types), B1, and B2 (blocking‐like types). Their distinctive dynamical characteristics allow identifying the main large‐scale precipitation‐driving mechanisms. Simulations with 22 Coupled Model Intercomparison Project 5 models for recent climate conditions show biases in reproducing the observed seasonality of weather types. In particular, an overestimation of weather type frequencies associated with zonal airflow is identified. Considering projections following the (Representative Concentration Pathways) RCP8.5 scenario over 2071–2100, the frequencies of the three driest types (S1, B2, and W3) are projected to increase (mainly S1, +4%) in detriment of the rainiest types, particularly W1 (−3%). These changes explain most of the precipitation projections over WE. However, a weather type‐independent background signal is identified (increase/decrease in precipitation over northern/southern WE), suggesting modifications in precipitation‐generating processes and/or model inability to accurately simulate these processes. Despite these caveats in the precipitation scenarios for WE, which must be duly taken into account, our approach permits a better understanding of the projected trends for precipitation over WE.
Comparison Between High-Pressure Processing and Chemical Extraction: Astaxanthin Yield From Six Species of Shrimp Carapace

ABSTRACT Astaxanthin is one of the main carotenoid pigments. It has beneficial effects on the immune system of the human body due to its powerful antioxidant properties. The application of this bioactive compound can be found to be significant in the food, pharmaceutical, and cosmetics industries. The aim of this research was to investigate astaxanthin yield from six species of Malaysian shrimp carapace. Six types of shrimp species—Parapenaeopsis sculptili, Metapenaeus lysianassa, Macrobrachium rosenbergii, Metapenaeopsis hardwickii, Penaeus merguiensis, and Penaeus monodon—were used to investigate total carotenoid content and astaxanthin yield. The investigation was carried out using chemical extraction and high-pressure processing (HPP) methods at 210 MPa, for a period of 10 min with a solvent mixture of acetone and methanol (7:3, v/v). HPP was proven to have a significant impact in increasing the total carotenoid content and astaxanthin yield. The highest total carotenoid content and astaxanthin yield is shown to be contained in the Penaeus monodon species. Total carotenoid was increased from 46.95 µg/ml using chemical extraction to 68.26 µg/ml using HPP; yield of astaxanthin was increased from 29.44 µg/gdw using chemical extraction to 59.9744 µg/gdw using HPP. Therefore, comparison between the HPP and chemical extraction methods showed that HPP is more advantageous with higher astaxanthin yield, higher quality, and shorter extraction time.
Mining Functional Modules by Multiview-NMF of Phenome-Genome Association

Background: Mining gene modules from genomic data is an important step to detect gene members of pathways or other relations such as protein-protein interactions. In this work, we explore the plausibility of detecting gene modules by factorizing gene-phenotype associations from a phenotype ontology rather than the conventionally used gene expression data. In particular, the hierarchical structure of ontology has not been sufficiently utilized in clustering genes while functionally related genes are consistently associated with phenotypes on the same path in the phenotype ontology. Results: We propose a hierarchal Nonnegative Matrix Factorization (NMF)-based method, called Consistent Multiple Nonnegative Matrix Factorization (CMNMF), to factorize genome-phenome association matrix at two levels of the hierarchical structure in phenotype ontology for mining gene functional modules. CMNMF constrains the gene clusters from the association matrices at two consecutive levels to be consistent since the genes are annotated with both the child phenotype and the parent phenotype in the consecutive levels. CMNMF also restricts the identified phenotype clusters to be densely connected in the phenotype ontology hierarchy. In the experiments on mining functionally related genes from mouse phenotype ontology and human phenotype ontology, CMNMF effectively improved clustering performance over the baseline methods. Gene ontology enrichment analysis was also conducted to reveal interesting gene modules. Conclusions: Utilizing the information in the hierarchical structure of phenotype ontology, CMNMF can identify functional gene modules with more biological significance than the conventional methods. CMNMF could also be a better tool for predicting members of gene pathways and protein-protein interactions. Availability: this https URL
Simultaneous segmentation and approximation of complex patterns

Deformable model have been widely used to approximate objects from collected data points, but most algorithms based on the deformable model can only handle geometrically and topologically simple objects. They are inadequate for objects with deep cavities or multi-part objects. Furthermore, they always assume there is only one underlying object for the collected data, which means the segmentation has been done ahead of time. Unlike most deformable algorithms which approximate one object at a time, our proposed approach can apply simultaneously more than one curve to approximate multiple objects. Using (1) the residual data points, (2) the bad parts of the fitting curve, and (3) appropriate Boolean operations, our approach is able to detect patterns with holes or cavities, and can perform segmentation by itself for more than one underlying object. We currently present experiments mainly on 2D data. These 2D algorithms can be extended to 3D without theoretical difficulties. An experiment on 3D data, composed of two genus I toruses, is also presented. Also, a new method for defining the external energy is presented, which helps capture the shape more accurately with low time and reasonable space complexities, and a method to prevent self-intersection of the curve during evolution is also introduced. <<ETX>>
Dynamic monitoring of cerebral metabolites during and after transient global ischemia in rats by quantitative proton NMR spectroscopy in vivo

Localized proton NMR spectroscopy was used to dynamically monitor alterations of cerebral metabolites before, during, and after a 10 min period of global forebrain ischemia in anesthetized rats. Metabolic assessment was based on user‐independent determination of absolute brain concentrations at a nominal temporal resolution of 1.6 min. While the concentrations of N‐acetyl aspartate (neuronal marker), creatines, cholines, and myo‐inositol (glial marker) remained constant, ischemia induced a rapid decline of brain glucose. One hour after reperfusion, glucose recovered to 4.1± 2.2 mmol/kg wet weight significantly above the basal value of 2.3± 1.3 mmol/kg wet weight. Mirroring glucose depletion, lactate increased from 1.0±0.6 to 13.5±1.5 mmol/kg wet weight 10‐15 min after the onset of ischemia. During reperfusion lactate clearance was characterized by a first‐order rate constant of 0.03/min. The time courses of glucose and lactate reflect the rapid onset of anaerobic glycolysis during states of critically diminished blood flow. Assuming complete ischemia the production of lactate from glucose and cerebral glycogen stores yields a brain glycogen concentration of 4.7±0.9 mmol glycosyl unit/kg wet weight. Elevation of brain glucose during early reperfusion suggests a transient mismatch of glucose uptake and consumption during the first 1‐2 hours post ischemia.
Antibacterial property of allopathic medicine versus phyto medicine: An in-vitro study

A successful endodontic treatment depends on appropriate instrumentation, irrigation, decontamination and obturation. Decontamination of root canal plays a crucial role in the success of endodontic treatment. Therefore, a suitable medicament is essential which can effectively eliminate bacterial contamination. To investigate and compare the antibacterial property of 2% povidone iodine, chlorhexidine, 10% Curcumin longa, 50% Syzygium cumini and GAM (Gentamycin, amoxicillin and metronidazole) antibiotic against Enterococcus fecalis. The inoculae of E. fecalis was used to make lawn culture on Mueller- Hinton agar media. Wells were prepared for each sample separately and the plates were then incubated at 37 0 C overnight. Zone of inhibition for each medicament was measured after 48 hours. The GAM antibiotic demonstrated strongest antibacterial activity, producing the largest zones of inhibition compared with other medicaments, followed by 2% povidone-iodine. There was no statistical difference in the activity of chlorhexidine and Syzygium cumini. Distilled water showed no activity. The GAM-antibiotic can be used as an alternative intra-canal medicament which has proved to be the most effective antibacterial agent amongst the various test medicaments used in the present study. K e y w o r d s Curcumin longa, E. fecalis, GAM antibiotic, Syzygium cumini, zone of inhibition
MIMO underwater acoustic channel characterization based on a remotely operated experimental platform

In the framework of the development of a MIMO (Multi-input Multi-output) capable underwater acoustic modem, this paper describes on the one hand a remotely operated experimental platform at sea in real conditions able to transmit and receive real-time multi-streams signals and the other hand an analysis of the experimental channel capacity gain brought by the MIMO approach with respect to traditional single transmitter system. The original remotely operated generation/acquisition system provides an extensive characterization of the MIMO underwater acoustic channel for various transmission ranges and sea states. The capacity analysis extracted from real conditions channel estimates confirm that MIMO approach in experimental scenario leads to a substantial capacity gain with respect to single transmitter even by taking account signal overhead. As foreseen by theory, the MIMO capacity gain is also shown to be dependent from transmission range and transducers arrays configuration.
The superposition of two identical states: The empty state

In this paper we define and study a new class of states (the empty states). These states are the superposition of two identical states (self-superposition state). We defined three different representations of theses states, namely, the source, the operator, and the self-superposition representations. Then, we apply the empty state to an elementary example state and find its three different representations. We apply the empty state to Fockstates and find an undetermined state. Then, we apply the empty state to the coherent state to produce the empty state of the coherent state (the EC state), and determine some of its mathematical, statistical and nonclassical properties.
DhITACT: DNA Hydrogel Formation by Isothermal Amplification of Complementary Target in Fluidic Channels

DNA hydrogel formation by isothermal amplification of complementary targets in microfluidic channels (DhITACT) is a new platform for rapid and accurate detection of infectious pathogens. DNA hydrogel is formed in situ within microfluidic channels by the isothermal rolling circle amplification process upon the selective binding of target strands from the biological fluid. Once the volume of DNA hydrogel sufficiently enlarges, it can selectively block the matching channels with target pathogens.