Ensemble Sales Forecasting Study in Semiconductor Industry

Sales forecasting plays a prominent role in business planning and business strategy. The value and importance of advance information is a cornerstone of planning activity, and a well-set forecast goal can guide sale-force more efficiently. In this paper CPU sales forecasting of Intel Corporation, a multinational semiconductor industry, was considered. Past sale, future booking, exchange rates, Gross domestic product (GDP) forecasting, seasonality and other indicators were innovatively incorporated into the quantitative modeling. Benefit from the recent advances in computation power and software development, millions of models built upon multiple regressions, time series analysis, random forest and boosting tree were executed in parallel. The models with smaller validation errors were selected to form the ensemble model. To better capture the distinct characteristics, forecasting models were implemented at lead time and lines of business level. The moving windows validation process automatically selected the models which closely represent current market condition. The weekly cadence forecasting schema allowed the model to response effectively to market fluctuation. Generic variable importance analysis was also developed to increase the model interpretability. Rather than assuming fixed distribution, this non-parametric permutation variable importance analysis provided a general framework across methods to evaluate the variable importance. This variable importance framework can further extend to classification problem by modifying the mean absolute percentage error(MAPE) into misclassify error. Please find the demo code at : https://github.com/qx0731/ensemble_forecast_methodsComment: 14 pages, Industrial Conference on Data Mining 2017 (ICDM 2017

Clinical narrative analytics challenges

Precision medicine or evidence based medicine is based on the extraction of knowledge from medical records to provide individuals with the appropriate treatment in the appropriate moment according to the patient features. Despite the efforts of using clinical narratives for clinical decision support, many challenges have to be faced still today such as multilinguarity, diversity of terms and formats in different services, acronyms, negation, to name but a few. The same problems exist when one wants to analyze narratives in literature whose analysis would provide physicians and researchers with highlights. In this talk we will analyze challenges, solutions and open problems and will analyze several frameworks and tools that are able to perform NLP over free text to extract medical entities by means of Named Entity Recognition process. We will also analyze a framework we have developed to extract and validate medical terms. In particular we present two uses cases: (i) medical entities extraction of a set of infectious diseases description texts provided by MedlinePlus and (ii) scales of stroke identification in clinical narratives written in Spanish

Patients' views on responsibility for the management of musculoskeletal disorders – A qualitative study

<p>Abstract</p> <p>Background</p> <p>Musculoskeletal disorders are very common and almost inevitable in an individual's lifetime. Enabling self-management and allowing the individual to take responsibility for care is stated as desired in the management of these disorders, but this may be asking more than people can generally manage. A willingness among people to take responsibility for musculoskeletal disorders and not place responsibility out of their hands or on employers but to be shared with medical professionals has been shown. The aim of the present study was to describe how people with musculoskeletal disorders think and reason regarding responsibility for prevention, treatment and management of the disorder.</p> <p>Methods</p> <p>Individual interviews with a strategic sample of 20 individuals with musculoskeletal disorders were performed. The interviews were tape-recorded, transcribed verbatim and analysed according to qualitative content analysis.</p> <p>Results</p> <p>From the interviews an overarching theme was identified: own responsibility needs to be met. The analysis revealed six interrelated categories: Taking on responsibility, Ambiguity about responsibility, Collaborating responsibility, Complying with recommendations, Disclaiming responsibility, and Responsibility irrelevant. These categories described different thoughts and reasoning regarding the responsibility for managing musculoskeletal disorders. Generally the responsibility for prevention of musculoskeletal disorders was described to lie primarily on society/authorities as they have knowledge of what to prevent and how to prevent it. When musculoskeletal disorders have occurred, health care should provide fast accessibility, diagnosis, prognosis and support for recovery. For long-term management, the individuals themselves are responsible for making the most out of life despite disorders.</p> <p>Conclusion</p> <p>No matter what the expressions of responsibility for musculoskeletal disorders are, own responsibility needs to be met by society, health care, employers and family in an appropriate way, with as much or as little of the "right type" of support needed, based on the individual's expectations.</p

F-Theory GUT Vacua on Compact Calabi-Yau Fourfolds

We present compact three-generation F-theory GUT models meeting in particular the constraints of D3-tadpole cancellation and D-term supersymmetry. To this end we explicitly construct elliptically fibered Calabi-Yau fourfolds as complete intersections in a toric ambient space. Toric methods enable us to control the singular geometry of the SU(5) GUT model. The GUT brane wraps a non-generic del Pezzo surface admitting GUT symmetry breaking via hypercharge flux. It is contractible to a curve and we demonstrate the existence of a consistent decoupling limit. We compute the Euler characteristic of the singular Calabi-Yau fourfold to show that our three-generation flux solutions obtained via the spectral cover construction are consistent with D3-tadpole cancellation.Comment: 22+12 pages; v2: minor clarifications on decoupling limi

The endogenous caspase-8 inhibitor c-FLIPL regulates ER morphology and crosstalk with mitochondria

Components of the death receptors-mediated pathways like caspase-8 have been identified in complexes at intracellular membranes to spatially restrict the processing of local targets. In this study, we report that the long isoform of the cellular FLICE-inhibitory protein (c-FLIPL), a well- known inhibitor of the extrinsic cell death initiator caspase-8, localizes at the endoplasmic reticulum (ER) and mitochondria-associated membranes (MAMs). ER morphology was disrupted and ER Ca2+-release as well as ER-mitochondria tethering were decreased in c-FLIP-/- mouse embryonic fibroblasts (MEFs). Mechanistically, c-FLIP ablation resulted in enhanced basal caspase-8 activation and in caspase-mediated processing of the ER-shaping protein reticulon-4 (RTN4) that was corrected by re-introduction of c-FLIPL and caspase inhibition, resulting in the recovery of a normal ER morphology and ER-mitochondria juxtaposition. Thus, the caspase-8 inhibitor c-FLIPL emerges as a component of the MAMs signaling platforms, where caspases appear to regulate ER morphology and ER-mitochondria crosstalk by impinging on ER-shaping proteins like the RTN4

ExpressionPlot: a web-based framework for analysis of RNA-Seq and microarray gene expression data

RNA-Seq and microarray platforms have emerged as important tools for detecting changes in gene expression and RNA processing in biological samples. We present ExpressionPlot, a software package consisting of a default back end, which prepares raw sequencing or Affymetrix microarray data, and a web-based front end, which offers a biologically centered interface to browse, visualize, and compare different data sets. Download and installation instructions, a user's manual, discussion group, and a prototype are available at http://expressionplot.com/ webcite.ALS Therapy Allianc

Recent trends in breast cancer incidence in US white women by county-level urban/rural and poverty status

<p>Abstract</p> <p>Background</p> <p>Unprecedented declines in invasive breast cancer rates occurred in the United States between 2001 and 2004, particularly for estrogen receptor-positive tumors among non-Hispanic white women over 50 years. To understand the broader public health import of these reductions among previously unstudied populations, we utilized the largest available US cancer registry resource to describe age-adjusted invasive and <it>in situ </it>breast cancer incidence trends for non-Hispanic white women aged 50 to 74 years overall and by county-level rural/urban and poverty status.</p> <p>Methods</p> <p>We obtained invasive and <it>in situ </it>breast cancer incidence data for the years 1997 to 2004 from 29 population-based cancer registries participating in the North American Association of Central Cancer Registries resource. Annual age-adjusted rates were examined overall and by rural/urban and poverty of patients' counties of residence at diagnosis. Joinpoint regression was used to assess trends by annual quarter of diagnosis.</p> <p>Results</p> <p>Between 2001 and 2004, overall invasive breast cancer incidence fell 13.2%, with greater reductions among women living in urban (-13.8%) versus rural (-7.5%) and low- (-13.0%) or middle- (-13.8%) versus high- (-9.6%) poverty counties. Most incidence rates peaked around 1999 then declined after second quarter 2002, although in rural counties, rates decreased monotonically after 1999. Similar but more attenuated patterns were seen for <it>in situ </it>cancers.</p> <p>Conclusion</p> <p>Breast cancer rates fell more substantially in urban and low-poverty, affluent counties than in rural or high-poverty counties. These patterns likely reflect a major influence of reductions in hormone therapy use after July 2002 but cannot exclude possible effects due to screening patterns, particularly among rural populations where hormone therapy use was probably less prevalent.</p

A longitudinal study of risk factors for the occurrence, duration and severity of menstrual cramps in a cohort of college women

To describe how menstrual cramps vary from cycle to cycle within a woman over time. To examine the influence of weight and lifestyle factors on occurrence, duration, and severity of menstrual pain. Design A one-year prospective menstrual diary study. Participants One hundred and sixty-five women aged 17 to 19 years entering a local university in 1985. Main outcome measures The occurrence, length, and maximum severity of pain during a menstrual period. Results Menstrual pain occurred during 71.6% of observed menstrual bleeds, most commonly beginning the first day of menses. The median duration was two days. Sixty percent of women reported at least one episode of severe pain, while 13% reported severe pain more than half the time. Earlier age at menarche and long menstrual periods increased the occurrence, duration and severity of pain. In smokers, cramps tended to last longer. Being overweight was an important risk factor for menstrual cramps and doubled the odds of having a long pain episode. Frequent alcohol consumption decreased the probability of having menstrual cramps, but in women who had pain it increased duration and severity. Physical activity was not associated with any pain parameter. Conclusions Women who have pain lasting three days are an important target group for prophylactic therapy. The occurrence and severity of menstrual cramps is influenced by potentially modifiable characteristics including weight, smoking, and alcohol consumption. Doctors may wish to counsel women presenting with dysmenorrhoea about the importance of healthy lifestyles and about the inefficacy of alcohol consumption as a treatment for dysmenorrhoea.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73220/1/j.1471-0528.1996.tb09597.x.pd

Phenotype and Genetics of Progressive Sensorineural Hearing Loss (Snhl1) in the LXS Set of Recombinant Inbred Strains of Mice

Progressive sensorineural hearing loss is the most common form of acquired hearing impairment in the human population. It is also highly prevalent in inbred strains of mice, providing an experimental avenue to systematically map genetic risk factors and to dissect the molecular pathways that orchestrate hearing in peripheral sensory hair cells. Therefore, we ascertained hearing function in the inbred long sleep (ILS) and inbred short sleep (ISS) strains. Using auditory-evoked brain stem response (ABR) and distortion product otoacoustic emission (DPOAE) measurements, we found that ISS mice developed a high-frequency hearing loss at twelve weeks of age that progressed to lower frequencies by 26 weeks of age in the presence of normal endocochlear potentials and unremarkable inner ear histology. ILS mice exhibited milder hearing loss, showing elevated thresholds and reduced DPOAEs at the higher frequencies by 26 weeks of age. To map the genetic variants that underlie this hearing loss we computed ABR thresholds of 63 recombinant inbred stains derived from the ISS and ILS founder strains. A single locus was linked to markers associated with ISS alleles on chromosome 10 with a highly significant logarithm of odds (LOD) score of 15.8. The 2-LOD confidence interval spans ∼4 Megabases located at position 54–60 Mb. This locus, termed sensorineural hearing loss 1 (Snhl1), accounts for approximately 82% of the phenotypic variation. In summary, this study identifies a novel hearing loss locus on chromosome 10 and attests to the prevalence and genetic heterogeneity of progressive hearing loss in common mouse strains