bluuebunny/crossref_metadata_2025_split huggingface dataset:
Profile of Acute Lymphoblastic Leukemia in Children Under 2 Years of Age
Authors: Cherungonath Anoop , Appaji L , Padma M , Arunakumari BS , Arunkumar AR , Avinash T , Vijay CR , Madhumati DS 
Published: August 2018

Abstract
Context: Acute lymphoblastic leukemia (ALL) shows substantial differences in clinical and laboratory features and treatment responsiveness in different subgroups. Pediatric ALL <2 years is associated with worse outcome. Infantile ALL is characterized by high white blood cell (WBC) counts, bulky extramedullary disease, translocations of 11q23 locus. There is paucity of data on ALL under 2 years of age. Aims: This study aims to analyze clinical, hematological, biochemical, immunophenotypical parameters, and treatment responsiveness of ALL under 2 years. Settings and Designs: It is a retrospective data analysis conducted at a Tertiary Care Cancer Centre in South India. The study population includes all pediatric ALL, registered at this institute during January 2009 to December 2013, who were under 2 years at the time of presentation. Materials and Methods: There were 122 cases of ALL under 2 years of age of whom 48 refused treatment, and four were lost to follow-up. Thus, 70 cases are eligible for analysis. Details on clinical, hematological, biochemical, radiological, immunophenotypical, and cytogenetic features were collected from case records, hospital cancer registry, and analysis done using SPSS version 20. Kaplan–Meier curves plotted for survival analysis. Results:: Male:female ratio was 1.26:1 (infants - 1:1; 1–2 years group - 1.3:1). The most common clinical features were hepatomegaly (95%) and fever (89%). Hemoglobin level >11 gm% was seen in 12%, WBC counts above 50,000 in 26% and platelets below 20,000 in 20%. Elevated lactate dehydrogenase presents in 64% and uric acid in 12%. Immunophenotype done in 44 children; precursor-B ALL-41, precursor-T ALL-3. Central nervous system -positive disease and 11q23 translocation were noted in one infant each. Conclusions: Infants with ALL are associated with poor prognosis. Children in the 1–2 years are associated with significantly better outcome. WBC counts >50,000 are associated with poor prognosis among infants. Treatment refusal/abandonment rate is 43% in the study population which is comparable to that in literature.
A Case of Synchronous Primary Gastric Cancer and Primary Hepatocellular Carcinoma
Authors: Pandiaraja Jayabal 
Published: August 2018

AbstractSynchronous occurrence of primary gastric cancer and hepatocelluar carcinoma is very rare. It is mandatory to differentiate synchronous two primary lesions from metastatic lesion, because treatment modality is different for each disease. We report an interesting case of double malignancy, synchronous primary gastric cancer, and primary hepatocelluar carcinoma, who never had a cirrhosis, family history of cancer as well as hepatitis B or hepatitis C infection. Our patient managed with palliative chemotherapy due to multicentric hepatocelluar carcinoma with primary gastric cancer.
Erythema Multiforme: A Mysterious Lesion!
Authors: Shrihari TG , Shetty Shishir Ram 
Published: August 2018

AbstractThe term “erythema multiforme (EM)” includes a wide and controversial variety of clinical expressions at the present time. This study revises the EM minor characteristics according to the most important publications found in literature. EM is a distinct dermatologic hypersensitivity pathology characterized by cutaneous or mucous lesions, and eventually, it can also involve both. In the EM minor, only one mucous membrane is affected and usually is the oral mucosa. When occur in the skin, the lesions usually appear symmetrically in the extremities and may exhibit several forms; hence, the name EM, in a target form, could be continuous or recurrent and none additional systemic involvement is present for both cases. Nowadays, many authors separate etiologically the several manifestations of the EM spectrum. However, no clinical definition is still accepted thoroughly, making more difficult the comparisons of etiological and clinical aspects, histopathological studies, and therapeutic protocols. For the present work, we tried to elucidate through an extensive literature revision, some historical and current aspects of EM, focusing mainly the EM minor and its frequent association to herpes simplex virus, with their diagnostic characteristics and current therapeutics, to facilitate the physician understanding, and to favor future researches about this mysterious disease.
“Soon It Would Be Too Hot”: Revisiting The Drowned World
Authors: Clement Tracey 
Published: August 2018

Abstract
We have entered an era in which we are threatened simultaneously by a revivified cold war and the ongoing calamity of climate change. I argue in this article that now is a good time to revisit J. G. Ballard’s 1962 novel The Drowned World. In its intertextual landscape, we find two real ruined cities (Hiroshima and New Orleans) that symbolize our two concurrent human-made eschatological threats. And revisiting The Drowned World now offers a timely reminder of the dangers of an anthropocentric worldview. Furthermore, this postapocalyptic story presents at least two ethically sound responses to the human-made crises we are complicit in creating. The Drowned World remains as relevant now as when it was written more than half a century ago.
Glitch_gli._ltc._
Authors: Colless Edward 
Published: August 2018

Abstract
The 2017 live-action remake of the 1995 anime Ghost in the Shell has attracted a storm of criticism over Hollywood whitewashing the original Japanese production as well as trivializing the original’s probing investigation of cyborg sentience. This essay explores a particular aspect of the breakdown of the human-cyborg interface in the remake: the protagonist’s subjective experience of unaccounted memories as a series of glitches in her digital vision. It does so by inducing glitches—as intensive surges or noisy interruptions—in the essay’s own critical vision.
Validation and expression analysis of predicted miRNAs in Phytophthora infestans and Phytophthora sojae
Authors: Madison Cassidy , Ospina-Giraldo Manuel 
Published: August 2018

Abstract
The post-transcriptional regulatory environment in oomycetes, especially in the economically important Phytophthora infestans and P. sojae, is poorly understood. In particular, the expression of microRNAs (miRNAs) and their potential roles in infection are a topic of increasing interest. In this study, we attempted to experimentally verify the existence of five miRNAs from both P. infestans and P. sojae, which had been predicted using in silico approaches. In addition, we investigated the possibility of these miRNAs playing a role in Phytophthora pathogenicity. The presence of two of the five miRNAs, namely miR8788, predicted in P. sojae, and miRNA3, predicted in P. infestans, was confirmed in vivo by amplification using specific stem-loop primers and subsequent cloning and sequencing. Analysis of miR8788 expression during pathogenesis revealed that the transcriptional activity of this miRNA increases considerably over the first 24 h postinoculation, suggesting potential involvement of miRNA in infection development by P. sojae.
Manures Effectivity to Enhanced the Availability of Phosphorus, Crops Growth and Yield of Rice and Corn in Acid Upland Soil
Authors: Sulaiman Yoyo 
Published: August 2018

The research was conducted in Tamanbogo Station Research in the 2007 Rainy Season in upland rice-corn intercropping farming. The research design used Randomized Complete Block Design with 3 replications. The treatments were 1). 15 t ha-1 manures + Residues of rock phosphate (RRP), 2). Without manures + RRP, 3). 15 t ha-1 manures + 150 kg ha-1 SP 36 and 4). Without manures + 150 kg ha-1 SP 36. The upland rice was seeded in planting space of 25 cm x 25 cm, 2-3 seeds/hill. The land was treated with 1 t ha-1 of RP in the last farming year while SP36 was applicated each season. Urea and KCl fertilizers that were used on upland rice were 300 kg ha-1 and 100 kg ha-1, respectively while corns were fertilized with 250 kg ha-1 urea and 100 kg KCl ha-1. The research results showed that the availability of N and K nutrients in the soil at the time of before planting was low but the availability P was high. Application of manures and RRP increased C-organic, availability of P , Ca and Cation Exchangeable Capacity in the soil. Application of 15 t ha-1 of manures with RRP increased dry biomass weight of rice and corn, there were 45.17 % and 49.23 %, respectively. The grain yield of rice and corn on the treatment of manures and RRP were not gave significant different compare to the yield was gained with SP 36 fertilizer.
Relationship between Organic-C and Available-P Due to Tidal Fluctuation in South Kalimantan
Authors: Yusran Fadly Hairannoor 
Published: August 2018

Tidal fluctuation creates different soil chemical properties which is totally deviate from normal circumstances. Organic matter decomposition occurs with limited O2 supply, hence disturbing Carbon cycle which has a central role in the process and nutrient mineralisation. The research aimed was to describe the relationship between organic-C and available-P due to tidal fluctuation in South Kalimantan. Ten undisturbed composite samples were collected in top-soil and sub-soil. Results showed that there was no direct effect from organic-C in P availability as in other mineral soils. However, there was an indication that the relationship was influenced by maturing process of the soil. In other words, the relationship between organic-C and available-P was typical for every type of swampland and was not related to the tidal fluctuationKeywords: Available-P, organic-C, P-transformation, tidal water fluctuation [How to Cite: Yusran FH. 2012. Relationship between Organic-C and Available-P Due to Tidal Fluctuation in South Kalimantan. J Trop Soils 17 (3) : 253-257. doi: 10.5400/jts.2012.17.3.253] [Permalink/DOI: www.dx.doi.org/10.5400/jts.2012.17.3.253]
Characterization of Surface Runoff, Soil Erosion and Nutrient Loss on Forest-Agriculture Landscape
Authors: Hidayat Yayat , Murtilaksono Kukuh , Sinukaban Naik 
Published: August 2018

The study was aimed to quantify volume of surface runoff, soil erosion and nutrient loss from the forest-agriculture landscape (forest margins) in Lore Lindu National Park Central Sulawesi. Surface runoff volume and soil erosion were measured daily on erosion plots. It was installed on several land use types i.e. forest land, maize, young cocoa, medium cocoa, old cocoa, vanilla, shrub and bush and bareland, on the soil Typic Dystrudepts with slope ± 40%. The nutrient content in surface runoff and sediments were analyzed from selected surface runoff and sediment samples. Surface runoff and soil erosion from agriculture land were respectively 2.1 to 3.4 and 3.6 to 5.8 times higher than from forest lands. Meanwhile, surface runoff and soil erosion from bareland were respectively 7.0 and 23.7 times greater than forest land respectively. Sediment nutrient contents from forest land were higher than agriculture land. In the contrary, total nutrient lost from agriculture land were higher than forest land ones. Nutrient losses carried by surface runoff were larger than those losses carried by sediments. Dissolved organic carbon (DOC) loss in surface runoff was 6,1 to 8,0 times higher than total organic carbon (TOC) loss in sediments. Likewise, nitrate (NO3-) loss in surface runoff was 1.9 to 12.1 times higher than total nitrogen (TN) in sediments as well as potassium, calcium, magnesium and sodium losses. Potassium is dominant cation loss carried by the surface runoff, while calcium is mainly carried by sediment.Keywords: Dissolve organic carbon; forest-agriculture landscape; nutrient loss; soil erosion; surface runoff[How to Cite: Hidayat Y, K Murtilaksono and N Sinukaban. 2012. Characterization of Surface Runoff, Soil Erosion and Nutrient Loss on Forest-agriculture Landscape. J Trop Soils, 17 (3): 259-266. doi: 10.5400/jts.2012.17.3.259][Permalink/DOI: www.dx.doi.org/10.5400/jts.2012.17.3.259]
Exosomal microRNAs as tumor markers in epithelial ovarian cancer
Authors: Pan Chi , Stevic Ines , Müller Volkmar , Ni Qingtao , Oliveira‐Ferrer Leticia , Pantel Klaus , Schwarzenbach Heidi 
Published: August 2018

Specific microRNAs (miRNAs) are packaged in exosomes that regulate processes in tumor development and progression. The current study focuses on the influence of exosomal miRNAs in the pathogenesis of epithelial ovarian cancer (EOC). MiRNA profiles were determined in exosomes from plasma of 106 EOC patients, eight ovarian cystadenoma patients, and 29 healthy women by TaqMan real‐time PCR‐based miRNA array cards containing 48 different miRNAs. In cell culture experiments, the impact of miR‐200b and miR‐320 was determined on proliferation and apoptosis of ovarian cancer cell lines. We report that miR‐21 (P = 0.0001), miR‐100 (P = 0.034), miR‐200b (P = 0.008), and miR‐320 (P = 0.034) are significantly enriched, whereas miR‐16 (P = 0.009), miR‐93 (P = 0.014), miR‐126 (P = 0.012), and miR‐223 (P = 0.029) are underrepresented in exosomes from plasma of EOC patients as compared to those of healthy women. The levels of exosomal miR‐23a (P = 0.009, 0.008) and miR‐92a (P = 009, 0.034) were lower in ovarian cystadenoma patients than in EOC patients and healthy women, respectively. The exosomal levels of miR‐200b correlated with the tumor marker CA125 (P = 0.002) and patient overall survival (P = 0.019). MiR‐200b influenced cell proliferation (P = 0.0001) and apoptosis (P < 0.008). Our findings reveal specific exosomal miRNA patterns in EOC and ovarian cystadenoma patients, which are indicative of a role of these miRNAs in the pathogenesis of EOC.
Circular Data Models
Authors: Pewsey Arthur 
Published: August 2018

AbstractIn contrast to linear data, for which the support is the real line, circular data are those for which the natural support is the unit circle. Examples include angles measured using a compass or weather vane expressed in degrees or radians and measured either clockwise or anticlockwise from some previously specified origin. Times of the day, week, month, or year can also be treated as circular data after conversion to angles. Cyber attacks recorded on a 24‐h clock provide an example. Circular data arise in animal movement and wind‐power generation studies, geology, astronomy, meteorology, oceanography, psychology, medicine, and the health sciences.As extensions of circular data, toroidal (circular–circular) data are obtained when the values of two circular random variables are observed simultaneously, and cylindrical (circular–linear) data when those of one circular and one linear random variable are jointly observed. In this article, we review probability models for circular data as well as their toroidal and cylindrical extensions.
Application of Model‐Based Designs in PhaseITrials
Authors: Garrett‐Mayer Elizabeth 
Published: August 2018

AbstractIn recent years, model‐based designs have gained popularity for dose‐finding studies in phase I clinical trials. Most of these are based on mathematical models of the relationship between dose and toxicity. Although these may appear more technical than more commonly used algorithmic designs, the model‐based designs tend to be better for many reasons including a more precise and accurate estimate of the desired dose, fewer patients treated at unsafe levels, and more patients treated at efficacious dose levels. Several of these model‐based designs are discussed, including those for combinations and late‐onset toxicities. The continual reassessment method is an adaptive approach that uses the information gathered on early patients in the trial to make decisions about the dose for patients treated later in the trial. Adaptive Bayesian designs behave in a similar way, but the framework in which they are developed differs. Designs in which efficacy and toxicity are both used to determine an optimum dose are also discussed.
Statistical Emulation
Authors: Grow André , Hilton Jason 
Published: August 2018

AbstractStatistical emulation is a technique for studying the behavior of computational simulation models. With this approach, a statistical function is fitted to the observed relations between model inputs and outputs based on systematic experimentation with the simulation model. The resulting function provides information about the general behavior of the simulation model and can be used, for example, for model simplification, optimization, and calibration. In this article, we discuss the general principles of statistical emulation, introduce readers to regression metamodels and Gaussian process emulators as two examples of commonly used statistical functions, and point readers to experimental designs that can be used for fitting these types of functions.
Within‐Cluster Resampling/Multiple Outputation
Authors: Follmann Dean 
Published: August 2018

Abstract

Within‐cluster resampling (WCR), also known as
multiple outputation
, was originally developed to address informative cluster size, but can easily be applied as a general tool for clustered data. WCR requires a statistical procedure for independent data that produces an asymptotically valid method for inference for a parameter , but one has clustered data with cluster size potentially related to the outcome. One replication of WCR synthetically creates independent data by randomly picking one element from within each cluster and uses the statistical procedure on this now independent data to produce an estimate and an estimated variance . WCR is applied a large number (e.g., 10 000) of times and the resulting s are averaged to obtain . A moment‐based estimator of variance is easily obtained from the s and s. This article develops the WCR estimator, describes special cases, and explores WCR applications.
Sequential Multiple Assignment Randomized Trial (SMART)
Authors: Vock David M. , Almirall Daniel 
Published: August 2018

AbstractA sequential multiple assignment randomized trial (SMART) is an experimental design that scientists can use to develop high‐quality dynamic treatment regimens (DTRs), a prespecified treatment plan in which the type(s) or dosage/intensity of an intervention, the delivery of the intervention, or the monitoring schedule is repeatedly adjusted in response to new information collected about the individual. Specifically, a SMART design is a multistage trial design in which each stage corresponds to a critical decision where there is a scientific question about how best to intervene at that stage. Each participant progresses through the stages and can be randomly assigned to one of several intervention options at each stage. SMART designs allow one to answer a variety of questions concerning the development of a DTR. We highlight some of the common research questions and hypotheses and briefly discuss the appropriate analytical approaches to test these hypotheses. We conclude by contrasting a SMART design with other experimental designs that could be used for developing or for evaluating different DTRs.
Stochastic Programming, Scenario Generation In
Authors: Römisch Werner 
Published: August 2018

AbstractStability‐based methods for scenario generation in stochastic programming are reviewed. In particular, we discuss Monte Carlo sampling, quasi‐Monte Carlo methods, and quadrature rules based on sparse grids, optimal quantization, and moment matching methods. In addition, we provide some results on convergence rates. Scenario reduction and scenario tree generation are briefly mentioned.
Machine Learning
Authors: Fattore Marco 
Published: August 2018

Abstract

Machine learning is a multidisciplinary research area, at the crossing of computer science, computational statistics, data mining, and applied mathematics. Its principal aim is to develop and implement algorithms capable of learning from data how to automatically perform various tasks, such as classification, prediction, and pattern recognition, generalizing from examples and without explicitly modeling the underlying stochastic data generation processes. Machine learning algorithms are particularly useful when dealing with high‐dimensional and complex data and when inferential models can hardly be worked out; they are being increasingly implemented in business processes, in smart devices, in decision support systems, and in other artificial intelligence applications, and are becoming a key tool of the “data revolution”. Although the conceptual premises of machine learning are quite different from those of more standard statistical modeling, the border between these two cultures is progressively fading and they are currently melting into what is now being called
data science
.
Big Data
Authors: di Bella Enrico 
Published: August 2018

Abstract

There is not a general consensus in the literature as to how to define big data, but a common framework to describe them are the so‐called three Vs or the three dimensions of big data:
volume
(the quantity of stored big data),
variety
(the variety of documents that constitute big data), and
velocity
(the speed at which new data is being generated). Big data are characterized by high values of all these three dimensions. A fourth dimension has been added later,
veracity
, which refers to the biases, noise, and abnormality in data that may make any result of their analysis completely meaningless if not properly collected and treated. Big data should be distinguished from large data sets or “lots of data” because it is not the volume of data alone that makes a set of data “big,” but their inherent complexity. The advent of big data has been hailed by some scholars as a new era for research, based on a new paradigm of science. Anyhow, another part of the scientific community expresses perplexity about the effective extent of the data revolution pointing out a number of critical points. Anyhow, without a doubt, big data analytics is a trending topic offering a large assortment of analyses designed to drive evidence‐based decision‐making both for the private business/industrial and the public/social sectors. Nevertheless, it raises some privacy issues that call for the definition of new de‐identification techniques and procedures to guarantee the individual's privacy.
Categorical Time Series Analysis
Authors: Weiß Christian H. 
Published: August 2018

AbstractCategorical time series are discrete‐valued time series having a qualitative range, which consists of a finite number of categories. As standard methods from real‐valued time series analysis cannot be applied to such a kind of data, tailor‐made tools for the visualization of the time series, characterizing the marginal distribution and measuring serial dependence are presented. Also, common stochastic models for such time series are surveyed, including types of Markov models, discrete ARMA models, Hidden‐Markov models, and regression models.
Hidden‐
M
arkov Models for Count Time Series
Authors: Weiß Christian H. 
Published: August 2018

Abstract
Hidden‐Markov models are a type of parameter‐driven state‐space model, which can be used for modeling count time series. Their observations stem from a finite mixture of count distributions and exhibit a non‐Markovian dependence structure. The likelihood function and forecasting distributions can be computed efficiently, and a simple algorithm is available for a global decoding of the hidden states.