1,013 research outputs found

    AMERICAS SUPPLY CHAIN: UNFORCASTED COMMERCE CHALLENGES OR LEADERSHIP FAILURE

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    The current supply chain disruptions are affecting commerce in some manner which leads to scarcities of products and labor globally. The research will show that supply chain issues are directly related to commerce and leadership which plays an important role in our economy. Supply chain operations are defined, and the different levels of supply chain activities are explained. Possible points of failure within the system as well as probable causes leading to empty shelves and unavailable products is explained in detail. The research describes how massive labor shortages, high petroleum prices, and shortages of essential sub-components has led to this crisis. Providing possible solutions or an insight into how leadership may be able to mitigate the supply chain issues. In summary, this project identified the many issues affecting the supply chain from pre-pandemic commerce leadership failures through current government mandates that directly affect the supply chain. Is the supply chain affecting commerce globally or is it just a local issue? What can leadership do to mitigate the effects to the supply chain both now and long term

    The Impact of Small Spinal Curves in Adolescents That Have Not Presented to Secondary Care:A Population-Based Cohort Study

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    Study Design: A prospective, population-based, birth cohort study. Objective: The aim of this study was to identify whether there is any hidden burden of disease associated with smaller spinal curves. Summary of Background Data: Adolescent idiopathic scoliosis is present in 3% to 5% of the general population. Large curves are associated with increased pain and reduced quality of life. However, no information is available on the impact of smaller curves, many of which do not reach secondary care. Methods: The Avon Longitudinal Study of Parents and Children (ALSPAC) recruited over 14,000 pregnant women from the Bristol area of South-West England between 1991 and 1992 and has followed up their offspring regularly. At age 15, presence or absence of spinal curvature ≥6 degrees in the offspring was identified using the validated dual-energy X-ray absorptiometry Scoliosis Measure on 5299 participants. At age 18, a structured pain questionnaire was administered to 4083 participants. Logistic regression was used to investigate any association between presence of a spinal curve at age 15 and self-reported outcomes at age 18 years. Results: Full data were available for 3184 participants. Two hundred two (6.3%) had a spinal curve ≥6 degrees and 125 (3.9%) had a curve ≥10 degrees (median curve size of 11 degrees). About 46.3% reported aches and pains that lasted for a day or longer in the previous month. About 16.3% reported back pain. Those with spinal curves were 42% more likely to report back pain than those without (odds ratio 1.42, 95% confidence interval 1.00–2.02, P = 0.047). Those with spinal curves had more days off school and were more likely to avoid activities that caused their pain. Conclusion Our results highlight that small scoliotic curves may be less benign than previously thought. Teenagers with small curves may not present to secondary care, but are nonetheless reporting increased pain, more days off school, and avoidance of activities. These data suggest that we should reconsider current scoliosis screening and treatment practices. Level of Evidence: 2 </p

    Dropping diversity of products of large US firms: Models and measures

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    It is widely assumed that in our lifetimes the products available in the global economy have become more diverse. This assumption is difficult to investigate directly, however, because it is difficult to collect the necessary data about every product in an economy each year. We solve this problem by mining publicly available textual descriptions of the products of every large US firms each year from 1997 to 2017. Although many aspects of economic productivity have been steadily rising during this period, our text-based measurements show that the diversity of the products of at least large US firms has steadily declined. This downward trend is visible using a variety of product diversity metrics, including some that depend on a measurement of the similarity of the products of every single pair of firms. The current state of the art in comprehensive and detailed firm-similarity measurements is a Boolean word vector model due to Hoberg and Phillips. We measure diversity using firm-similarities from this Boolean model and two more sophisticated variants, and we consistently observe a significant dropping trend in product diversity. These results make it possible to frame and start to test specific hypotheses for explaining the dropping product diversity trend

    Head motion during fMRI tasks is reduced in children and adults if participants take breaks

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    Head motion remains a challenging confound in functional magnetic resonance imaging (fMRI) studies of both children and adults. Most pediatric neuroimaging labs have developed experience-based, child-friendly standards concerning e.g. the maximum length of a session or the time between mock scanner training and actual scanning. However, it is unclear which factors of child-friendly neuroimaging approaches are effective in reducing head motion. Here, we investigate three main factors including (i) time lag of mock scanner training to the actual scan, (ii) prior scan time, and (iii) task engagement in a dataset of 77 children (aged 6-13) and 64 adults (aged 18-35) using a multilevel modeling approach. In children, distributing fMRI data acquisition across multiple same-day sessions reduces head motion. In adults, motion is reduced after inside-scanner breaks. Despite these positive effects of splitting up data acquisition, motion increases over the course of a study as well as over the course of a run in both children and adults. Our results suggest that splitting up fMRI data acquisition is an effective tool to reduce head motion in general. At the same time, different ways of splitting up data acquisition benefit children and adults

    Age at puberty and accelerometer-measured physical activity:findings from two independent UK cohorts

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    Background It is unclear if puberty timing influences future physical activity (PA). Aim To investigate the association of puberty timing with PA across adolescence and adulthood. Subjects and methods Data were from two British cohorts. Participants from an adolescent birth cohort (females = 2349, males = 1720) prospectively reported age at menarche and voice break and had PA recorded by Actigraph accelerometers at ages 14 years and 16 years. A cohort of middle-aged and older adults (40–70 years; females = 48,282; males = 36,112) recalled their age at puberty and had PA (mean acceleration; mg) measured by AxivityAX3 accelerometers. Results After adjustment for age, education, smoking and BMI, per 1-year older age at menarche was associated with higher mean counts/minute at age 14 years (0.07 SD counts/minute; 95% CI = 0.04–0.11) with associations attenuated at age 16 years (0.02; −0.03–0.07). Differences in mean acceleration per older year at menarche were close to the null in women aged 40–49 years (0.02 mg; 0.01–0.03), 50–59 years (0.01; 0.00–0.02) and 60–70 years (0.01; 0.00–0.01). Age at voice break and PA associations were close to the null in both cohorts. Conclusion We found a positive association between puberty timing and PA in females which weakened at older ages and limited evidence of an association at any age in males

    Startup Methodology for Production Flow Simulation Projects Assessing Environmental Sustainability

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    Environmental impact assessments for companies and products are important to increase sales and reduce environmental impact. To support improvements and detailed analyses, researchers have extended the use of simulation of production flows to include sustainability performance indicators. The research cases performed until recently lack standardized methodology and thus have comparability issues and an increase number of common faults. By using a common methodology and gathering best practice, future cases can gain a lot. Especially noted by the authors is that the project startup phase is critical for success. This paper proposes a methodology to support the startup phases of simulation projects with sustainability aspects in production flows. The methodology is developed and applied in an automotive industry study presented in this paper. Using a rigid project startup, such as the proposed methodology, reduces iterations during modeling and data collection and decreases time spent on modeling

    Prostate Age Gap: An MRI Surrogate Marker of Aging for Prostate Cancer Detection

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    Background Aging is the most important risk factor for prostate cancer (PC). Imaging techniques can be useful to measure age-related changes associated with the transition to diverse pathological states. However, biomarkers of aging from prostate magnetic resonance imaging (MRI) remain to be explored. Purpose To develop an aging biomarker from prostate MRI and to examine its relationship with clinically significant PC (csPC, Gleason score ≥7) risk occurrence. Study Type Retrospective. Population Four hundred and sixty-eight (65.97 ± 6.91 years) biopsied males, contributing 7243 prostate MRI slices. A deep learning (DL) model was trained on 3223 MRI slices from 81 low-grade PC (Gleason score ≤6) and 131 negative patients, defined as non-csPC. The model was tested on 90 negative, 52 low-grade (142 non-csPC), and 114 csPC patients. Field Strength/Sequence 3-T, axial T2-weighted spin sequence. Assessment Chronological age was defined as the age of the participant at the time of the visit. Prostate-specific antigen (PSA), prostate volume, Gleason, and Prostate Imaging-Reporting and Data System (PI-RADS) scores were also obtained. Manually annotated prostate masks were used to crop the MRI slices, and a DL model was trained with those from non-csPC patients to estimate the age of the patients. Following, we obtained the prostate age gap (PAG) on previously unseen csPC and non-csPC cropped MRI exams. PAG was defined as the estimated model age minus the patient's age. Finally, the relationship between PAG and csPC risk occurrence was assessed through an adjusted multivariate logistic regression by PSA levels, age, prostate volume, and PI-RADS ≥ 3 score. Statistical Tests T-test, Mann–Whitney U test, permutation test, receiver operating characteristics (ROC), area under the curve (AUC), and odds ratio (OR). A P value <0.05 was considered statistically significant. Results After adjusting, there was a significant difference in the odds of csPC (OR = 3.78, 95% confidence interval [CI]: 2.32–6.16). Further, PAG showed a significantly larger bootstrapped AUC to discriminate between csPC and non-csPC than that of adjusted PI-RADS ≥ 3 (AUC = 0.981, 95% CI: 0.975–0.987).publishedVersio
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