Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Swab Composition and Use of Swabs versus Swab-Containing Skim Milk-Tryptone-Glucose-Glycerol (STGG) on Culture- or PCR-Based Detection of Streptococcus pneumoniae in Simulated and Clinical Respiratory Specimens in STGG Transport Medium

ABSTRACT To detect Streptococcus pneumoniae colonization, the nasopharynx is sampled using a swab placed in skim milk-tryptone-glucose-glycerol (STGG) transport medium, and then the swab specimen or STGG medium is cultured or subjected to PCR. We evaluated the effect of swab composition and compared the sensitivities of detection of culture and PCR using swabs and swab-containing medium. Calcium alginate, Dacron polyester, or rayon-tipped swabs were inoculated with pneumococci or were immersed in nasal wash specimens from children and then placed in STGG medium. Swabs and medium inoculated with pneumococci were cultured. Swabs grew significantly more colonies than medium. The number of colonies cultured from rayon swabs or medium was significantly higher than the number cultured from the calcium alginate swab or medium. The number of colonies from both the Dacron polyester swabs and medium were significantly lower than with either calcium alginate or rayon swabs. When DNA was separately extracted from the calcium alginate swab and medium and subjected to PCR for pneumococcal detection from either S. pneumoniae-inoculated swabs or clinical specimens that grew S. pneumoniae, the sensitivity was at least 10 times higher using the swab. With Dacron polyester or rayon-tipped swabs, there was no consistent difference between the sensitivity of PCR using swabs and that of PCR using medium. Thus, calcium alginate swabs may be superior to STGG medium for the culture and PCR-based detection of S. pneumoniae. For culture, rayon swabs are superior and Dacron polyester swabs are inferior. The sensitivity of the swab and swab-containing medium for culture or PCR detection of S. pneumoniae varies with swab composition.
An Analysis of Action Recognition Datasets for Language and Vision Tasks

A large amount of recent research has focused on tasks that combine language and vision, resulting in a proliferation of datasets and methods. One such task is action recognition, whose applications include image annotation, scene understanding and image retrieval. In this survey, we categorize the existing approaches based on how they conceptualize this problem and provide a detailed review of existing datasets, highlighting their diversity as well as advantages and disadvantages. We focus on recently developed datasets which link visual information with linguistic resources and provide a fine-grained syntactic and semantic analysis of actions in images.
Urinary proteomics analysis for renal injury in hypertensive disorders of pregnancy with iTRAQ labeling and LC‐MS/MS

Purpose: As a noninvasive examination, urinary proteomics is a very useful tool to identify renal disease. The purpose of the present study was to find differential proteins among women with preeclampsia, gestational hypertension and normal pregnancy, and to screen potential biomarkers for the early diagnosis of preeclampsia.
Good gay females and babies' daddies: Black lesbian community norms and the acceptability of pregnancy

Communities have different norms and expectations regarding pregnancy and parenting and these norms affect individual reproductive behaviour. Using grounded theory, this paper examines sexual and gender norms that have implications for pregnancy, mothering and parenting within a community of young Black lesbians. In this community, pregnancy and parenting experiences affect participants' sexual and gender identities through the community discourse on appropriate motherhood. Identity is negotiated and contested vis-à-vis pregnancy and parenting. Using social categorisation theory as a lens into participants' pregnancy and parenting experiences, we show how normative discourse in this community ties appropriate reproductive behaviour to gendered bodies and, by extension, how pregnancy and parenting have implications for participants' developing gender identities.
De Bruijn graph based 3D Network on Chip architecture design

Network on Chip (NoC) is an on-chip communication methodology proposed to resolve the increased interconnection problem in System in Chip (SoC). Since the three dimensional (3D) integrated circuit (IC) can offer shorter interconnection wire for Network on Chip, 3D NoC becomes an emerging research area in recent years. The architecture of 3D NoC is one of the most important and fundamental issues in 3D NoC research area, since it plays an important roll in network latency, throughput, power consumption, application mapping, and chip complexity. In this paper, we propose a new architecture based on De Bruijn graph for 3D NoC, since De Bruijn graph is a topology with small diameter, simple routing and high reliability. We evaluate this architecture with two Mesh based architectures. The simulation result shows that the De Bruijn graph based architecture can achieve smaller network latency than Mesh based architectures.
Ensemble Committees for Stock Return Classification and Prediction

This paper considers a portfolio trading strategy formulated by algorithms in the field of machine learning. The profitability of the strategy is measured by the algorithm's capability to consistently and accurately identify stock indices with positive or negative returns, and to generate a preferred portfolio allocation on the basis of a learned model. Stocks are characterized by time series data sets consisting of technical variables that reflect market conditions in a previous time interval, which are utilized produce binary classification decisions in subsequent intervals. The learned model is constructed as a committee of random forest classifiers, a non-linear support vector machine classifier, a relevance vector machine classifier, and a constituent ensemble of k-nearest neighbors classifiers. The Global Industry Classification Standard (GICS) is used to explore the ensemble model's efficacy within the context of various fields of investment including Energy, Materials, Financials, and Information Technology. Data from 2006 to 2012, inclusive, are considered, which are chosen for providing a range of market circumstances for evaluating the model. The model is observed to achieve an accuracy of approximately 70% when predicting stock price returns three months in advance.
Host Plant Phenology Affects Performance of an Invasive Weevil, Phyllobius oblongus (Coleoptera: Curculionidae), in a Northern Hardwood Forest

ABSTRACT We investigated how host plant phenology and plant species affected longevity, reproduction, and feeding behavior of an invasive weevil. Phyllobius oblongus L. (Coleoptera: Curculionidae) is common in northern hardwood forests of the Great Lakes Region. Adults emerge in spring, feed on foliage of woody understory plants, and oviposit in the soil. Preliminary data indicate that adults often feed on sugar maple, Acer saccharum Marshall, foliage early in the season, then feed on other species such as raspberry, Rubus spp. Whether this behavior reflects temporal changes in the quality of A. saccharum tissue or merely subsequent availability of later-season plants is unknown. We tested adult P. oblongus in laboratory assays using young (newly flushed) sugar maple foliage, old (2–3 wk postflush) sugar maple foliage, and raspberry foliage. Raspberry has indeterminate growth, thus always has young foliage available for herbivores. Survival, oviposition, and leaf consumption were recorded. In performance assays under no-choice conditions, mated pairs were provided one type of host foliage for the duration of their lives. In behavioral choice tests, all three host plants were provided simultaneously and leaf area consumption was compared. Adults survived longer on and consumed greater amounts of young maple and raspberry foliage than old maple foliage. P. oblongus preferred young maple foliage to old maple foliage early in the season, however, later in the growing season weevils showed less pronounced feeding preferences. These results suggest how leaf phenology, plant species composition, and feeding plasticity in host utilization may interact to affect P. oblongus population dynamics.
Maximizing Recovery of Native Protein from Aggregates by Optimizing Pressure Treatment

Recovering native protein from aggregates is a common obstacle in the production of recombinant proteins. Recent reports have shown that hydrostatic pressure is an attractive alternative to traditional denature‐and‐dilute techniques, both in terms of yield and process simplicity. To determine the effect of process variables, we subjected tailspike aggregates to a variety of pressure‐treatment conditions. Maximum native tailspike yields were obtained with only short pressure incubations (<5 min) at 240 MPa. However, some tailspike aggregates were resistant to pressure, despite multiple cycles of pressure. Extending the postpressure incubation time to 4 days improved the yield of native protein from aggregates from 19.4 ± 0.9 to 47.4 ± 19.6 μg/mL (approximately 78% yield of native trimer from nonaggregate material). The nearly exclusive conversion of monomer to trimer over the time scale of days, when combined with previous kinetic data, allows for the identification of three postpressure kinetic phases: a rapid phase consisting of structured dimer conversion to trimer (30 min), an intermediate phase consisting of monomer conversion to aggregate (100 min), and a slow phase consisting of conversion of monomer to trimer (days). Optimizing the production of structured dimer can yield the highest level of folded protein. Typical refolding additives, such as glycerol, or low‐temperature incubation did not improve yields.
XR-tree: indexing XML data for efficient structural joins

XML documents are typically queried with a combination of value search and structure search. While querying by values can leverage traditional database technologies, evaluating structural relationship, specifically parent-child or ancestor-descendant relationship, between XML element sets has imposed a great challenge on efficient XML query processing. We propose XR-tree, namely, XML region tree, which is a dynamic external memory index structure specially designed for strictly nested XML data. The unique feature of XR-tree is that, for a given element, all its ancestors (or descendants) in an element set indexed by an XR-tree can be identified with optimal worst case I/O cost. We then propose a new structural join algorithm that can evaluate the structural relationship between two XR-tree indexed element sets by effectively skipping ancestors and descendants that do not participate in the join. Our extensive performance study shows that the XR-tree based join algorithm significantly outperforms previous algorithms.
Purification and culture of adult rat dorsal root ganglia neurons

To study the trophic requirements of adult rat dorsal root ganglia neurons (DRG) in vitro, we developed a purification procedure that yields highly enriched neuronal cultures. Forty to fifty ganglia are dissected from the spinal column of an adult rat. After enzymatic and mechanical dissociation of the ganglia, myelin debris are eliminated by centrifugation on a Percoll gradient. The resulting cell suspension is layered onto a nylon mesh with a pore size of 10 μm. Most of the neurons, the diameter of which ranged from 17 μm to > 100 μm, are retained on the upper surface of the sieve; most of the non‐neuronal cells with a caliber of < 10 μm after trypsinization go through it. Recovery of neurons is achieved by reversing the mesh onto a Petri dish containing culture medium. Neurons to non‐neurons ratio is 1 to 10 in the initial cell suspension and 1 to 1 after separation. When these purified neurons are seeded at a density of 3, 000 neurons/cm2 in 6 mm polyornithine–‐laminin (PORN‐LAM) coated wells, neuronal survival (assessed by the ability to extend neurites), measured after 48 hr of culture, is very low (from 0 to 16%). Addition of nerve growth factor (NGF) does not improve neuronal survival. However, when neurons are cultured in the presence of medium conditioned (CM) by astrocytes or Schwann cells, 60–80% of the seeded, dye‐excluding neurons survive. So, purified adult DRG neurons require for their short‐term survival and regeneration in culture, a trophic support that is present in conditioned medium from PNS or CNS glia. As NGF has no survival‐promoting effect on these purified adult neurons, the trophic effect of CMs is likely to be mediated by non‐NGF molecule(s).
Intimate partner abuse of educated, employed black South African women: sociocultural factors

This study aimed to explore the influence of African culture and tradition on the abuse experiences of Black South African women who are educated and employed. Interviews were conducted with seven Black South African women (age range 38 to 47) who are college educated and employed. All participants were married for seven or more years and self-reporting to be in an abusive relationship. Interviews were transcribed verbatim and analysed using thematic content analysis. The results indicate sociocultural factors such as patriarchal values within their culture as an underlying reason for their husbands’ abusive behaviour. Abuse seemed likely when the women perceived gender roles that were in conflict with their husband's gender role expectations of them. The cultural expectation that women should not leave a marriage appeared to play an implicit role in their staying in an abusive relationship.
PpiA, a Surface PPIase of the Cyclophilin Family in Lactococcus lactis

Background Protein folding in the envelope is a crucial limiting step of protein export and secretion. In order to better understand this process in Lactococcus lactis, a lactic acid bacterium, genes encoding putative exported folding factors like Peptidyl Prolyl Isomerases (PPIases) were searched for in lactococcal genomes. Results In L. lactis, a new putative membrane PPIase of the cyclophilin subfamily, PpiA, was identified and characterized. ppiA gene was found to be constitutively expressed under normal and stress (heat shock, H2O2) conditions. Under normal conditions, PpiA protein was synthesized and released from intact cells by an exogenously added protease, showing that it was exposed at the cell surface. No obvious phenotype could be associated to a ppiA mutant strain under several laboratory conditions including stress conditions, except a very low sensitivity to H2O2. Induction of a ppiA copy provided in trans had no effect i) on the thermosensitivity of an mutant strain deficient for the lactococcal surface protease HtrA and ii) on the secretion and stability on four exported proteins (a highly degraded hybrid protein and three heterologous secreted proteins) in an otherwise wild-type strain background. However, a recombinant soluble form of PpiA that had been produced and secreted in L. lactis and purified from a culture supernatant displayed both PPIase and chaperone activities. Conclusions Although L. lactis PpiA, a protein produced and exposed at the cell surface under normal conditions, displayed a very moderate role in vivo, it was found, as a recombinant soluble form, to be endowed with folding activities in vitro.
Ordinal Text Quantification

In recent years there has been a growing interest in text quantification, a supervised learning task where the goal is to accurately estimate, in an unlabelled set of items, the prevalence (or "relative frequency") of each class c in a predefined set C. Text quantification has several applications, and is a dominant concern in fields such as market research, the social sciences, political science, and epidemiology. In this paper we tackle, for the first time, the problem of ordinal text quantification, defined as the task of performing text quantification when a total order is defined on the set of classes; estimating the prevalence of "five stars" reviews in a set of reviews of a given product, and monitoring this prevalence across time, is an example application. We present OQT, a novel tree-based OQ algorithm, and discuss experimental results obtained on a dataset of tweets classified according to sentiment strength.
Self-adaptive Gaussian mixture models for real-time video segmentation and background subtraction

The usage of Gaussian mixture models for video segmentation has been widely adopted. However, the main difficulty arises in choosing the best model complexity. High complex models can describe the scene accurately, but they come with a high computational requirements, too. Low complex models promote segmentation speed, with the drawback of a less exhaustive description. In this paper we propose an algorithm that first learns a description mixture for the first video frames, and then it uses these results as a starting point for the analysis of the further frames. Then, we apply it to a video sequence and show its effectiveness for real-time tracking multiple moving objects. Moreover, we integrated this procedure into a foreground/background subtraction statistical framework. We compare our procedure against the state-of-the-art alternatives, and we show both its initialization efficacy and its improved segmentation performance.
International Journal of Forecasting In-play Forecasting of Win Probability in One-day International Cricket: a Dynamic Logistic Regression Model

The paper presents a model for forecasting the outcomes of One-Day International cricket matches whilst the game is in progress. Our 'in-play' model is dynamic, in the sense that the parameters of the underlying logistic regression model are allowed to evolve smoothly as the match progresses. The use of this dynamic logistic regression approach reduces the number of parameters required dramatically, produces stable and intuitive forecast probabilities, and has a minimal effect on the explanatory power. Cross-validation techniques are used to identify the variables to be included in the model. We demonstrate the use of our model using two matches as examples, and compare the match result probabilities generated using our model with those from the betting market. The forecasts are similar quantitatively, a result that we take to be evidence that our modelling approach is appropriate.
RETURN TO AND DEPARTURE FROM SOCIAL ORIGIN: TRENDS IN SOCIAL FLUIDITY IN THE CZECH REPUBLIC BETWEEN 1990 AND 2011

The authors analyse trends in social fluidity between 1990 and 2011 in Czech society and examine how the transition from socialism to capitalism has affected these trends. The data consist of 28 annual surveys conducted in the Czech Republic between 1990 and 2011 (N=28,726). The results show that social fluidity decreases in Czech society between 1989 and 2000. This is the result of social change (the period effect), namely, intragenerational changes that the authors conceptualise as a return to social origin, which are related to the re-stratification of Czech society after 1989. The period of return to social origin finishes sometime around the year 2000. After that, the trend reverses and social fluidity slowly increases. The authors argue that the period of return to social origin is replaced by a period of departure from social origin. This shift is the effect of the educational expansion that occurs after 1989 in Czech society and cohort replacement.
Grasp analysis and synthesis based on a new quantitative measure

In this paper, we present a quantitative measure of multifingered grasps. The measure quantifies the capability of a grasp in firmly holding an object while resisting external loads and/or disturbances. It can also be used for qualitative test of closure properties (form closure and force closure). For planar grasps and frictionless three-dimensional (3-D) grasps, the quantitative measure can be computed efficiently by solving a set of linear programs, while for frictional 3-D grasps, it can be computed by solving nonlinear programs without linearization of the friction cone. By using the proposed quantitative measure, an algorithm for grasp synthesis on polygonal objects is developed. Rather than producing a single grasp configuration, the algorithm computes all grasps on a polygon that satisfy quantitative constraints, i.e., the value of the quantitative measure is greater than a predetermined positive constant. The approach has potential application in grasp planning with multiple optimality criteria.
When do redundant requests reduce latency ?

Several systems possess the flexibility to serve requests in more than one way. For instance, a distributed storage system storing multiple replicas of the data can serve a request from any of the multiple servers that store the requested data, or a computational task may be performed in a compute-cluster by any one of multiple processors. In such systems, the latency of serving the requests may potentially be reduced by sending redundant requests: a request may be sent to an excess number of servers, and it is deemed served when the requisite number of servers complete service. Such a mechanism trades off the possibility of faster execution of at least one copy of the request with the increase in the delay due to an increased load on the system. Due to this tradeoff, it is unclear when redundant requests may actually help. Several recent works empirically evaluate the latency performance of redundant requests in diverse settings. This work aims at a rigorous analytical study of the latency performance of redundant requests, with the primary goals of characterizing the situations when sending redundant requests will help (and when not), and designing optimal redundant-requesting policies. We first present a model that captures the key features of such systems. We show that when service times are i.i. d. memoryless or “heavy”, and when the additional copies of already-completed jobs can be removed with negligible costs, redundant requests reduce the average latency. On the other hand, when service times are “light” or when service times are memoryless and removal of jobs results in a non-negligible penalty, not having any redundancy in the request is optimal under high loads. Our results hold for arbitrary arrival processes.
Information Bottleneck for Non Co-Occurrence Data

We present a general model-independent approach to the analysis of data in cases when these data do not appear in the form of co-occurrence of two variables X, Y, but rather as a sample of values of an unknown (stochastic) function Z(X, Y). For example, in gene expression data, the expression level Z is a function of gene X and condition Y; or in movie ratings data the rating Z is a function of viewer X and movie Y. The approach represents a consistent extension of the Information Bottleneck method that has previously relied on the availability of co-occurrence statistics. By altering the relevance variable we eliminate the need in the sample of joint distribution of all input variables. This new formulation also enables simple MDL-like model complexity control and prediction of missing values of Z. The approach is analyzed and shown to be on a par with the best known clustering algorithms for a wide range of domains. For the prediction of missing values (collaborative filtering) it improves the currently best known results.
Incremental Variational Inference applied to Latent Dirichlet Allocation

We introduce incremental variational inference, which generalizes incremental EM and provides an alternative to stochastic variational inference. It also naturally extends to the distributed setting. We apply incremental variational inference to LDA and show that there is a benefit to do multiple passes over the data in the large-scale setting. Incremental inference does not require to set a learning rate, converges faster to a local optimum of the variational bound and enjoys the attractive property of monotonically increasing it like its batch counterpart.