bluuebunny/crossref_metadata_2025 huggingface dataset:
Cross-cultural adaptions and measurement properties of the WORC (Western Ontario rotator cuff index): a systematic review
Authors: Furtado Rochelle , MacDermid Joy C. , Nazari Goris , Bryant Dianne M. , Faber Kenneth J. , Athwal George S.
Published: January 2020

Background

To evaluate the translations, cross-cultural adaptation procedures and measurement properties of the Western Ontario Rotator Cuff Index (WORC), when it is adapted for different cultures.

Methods

A systematic review was performed, considering different cultural adaptions of the WORC accessible through MEDLINE, CINAHL, EMBASE and/or Google Scholar. Included were prospective cohort studies that used an adapted version of the WORC to measure QoL in patients with rotator cuff disorders. All studies were evaluated according to the current guidelines for cross-cultural adaptations and measurement properties.

Results

The search retrieved 14 studies that met the inclusion criteria. According to the recommended guidelines for cross-cultural adaptations, 8 studies performed 100% of the steps, 2 studies performed 80% of the steps and 4 studies used previously translated measures. When evaluating the studies’ psychometric properties based on the quality criteria, none of the studies reported all recommended measurement properties. All of the studies reported the measurement property of reliability, but none of the studies reported agreement. Internal consistency was fully reported by 15% of studies. Construct validity was reported by 43% of studies. Only one study reported 100% of the cross-cultural adaption guidelines and 83% of the quality criteria.

Conclusions

Although the majority of studies demonstrated proper adaptation procedures, testing of the measurement properties were inadequate. It is recommended that the current adapted versions of the WORC undergo further testing before use in clinical practise, and researchers continue to adapt the WORC for different cultures as it proves to be an appropriate instrument for assessing rotator cuff pathology.
Serial measurement of mood via text messaging in young people
Authors: Hazell Philip , Balzer Ben , Kelly Patrick , Paxton Karen , Hawke Catherine , Ivers Rebecca , Skinner Rachel , Luscombe Georgina , Steinbeck Katharine S.
Published: January 2020

Background

To support longitudinal research into mood in adolescents we sought to assess the feasibility of collecting mood data via Short Message Service (SMS) over 3 years, and to investigate the relationship between SMS data and self-report measures of depression.

Methods

Prospective cohort study of young people aged 9 to 14 years at baseline. Participants completed Short Mood and Feelings Questionnaire (SMFQ) and the Youth Self Report Anxious/Depressed ((YSR)/AD) and Withdrawn/Depressed (YSR/WD) scales at baseline and annually for 3 years. In addition, at 3 monthly intervals they responded to an SMS asking them to rate their mood from 0 to 9 (9 highest).

Results

277 young people (43% female) completed all four waves of the survey. There was a 87% response rate to requests for SMS Mood ratings. Mean SMS Mood decreased over time for females (p = 0.006) but not males (p = 0.45). We found an inverse association between SMS Mood and the SMFQ, YSR/AD and YSR/WD, scales in females and the SMFQ and YSR/WD scales in males. 45% of participants reported at least one SMS Mood rating score below 5, while 5% reported clusters of low SMS scores. Clusters of low SMS Mood scores were associated with SMFQ scores in the clinical range at 24 (OR = 4.45) and 36 months (OR = 4.72), and YSR/WD in the clinical range at 36 months (OR = 4.61).

Conclusions

SMS Mood ratings represent a feasible means to augment but not replace assessment of mood obtained using standard instruments.
Double deletion of the active zone proteins CAST/ELKS in the mouse forebrain causes high mortality of newborn pups
Authors: Hagiwara Akari , Hamada Shun , Hida Yamato , Ohtsuka Toshihisa
Published: January 2020

Presynaptic active zone cytomatrix proteins are essential elements of neurotransmitter release machinery that govern neural transmission. Among active zone proteins, cytomatrix at the active zone-associated structural protein (CAST) is known to regulate active zone size in retinal photoreceptors and neurotransmitter release by recruiting Ca2+ channels at various synapses. However, the role of ELKS—a protein from the same family as CAST—and the synergistic roles of CAST/ELKS have not been thoroughly investigated, particularly with regard to mouse behavior. Here, we generated ELKS conditional KO in mouse forebrain synapses by crossing ELKS flox mice with a CaMKII promoter-induced Cre line. Results showed that CAST is dominant at these synapses and that ELKS can support CAST function, but is less effective in the ELKS single KO. Pups of CAST/ELKS double KO in the forebrain were born in Mendelian rations but resulted in eventual death right after the birth. Anatomically, the forebrain neuronal compositions of CAST KO and CAST/ELKS double KO mice were indistinguishable, and the sensory neural network from whiskers on the face was identified as barrelette-like patches in the spinal trigeminal nucleus. Therefore, depletion of CAST and ELKS disrupts neurotransmission from sensory to motor networks, which can lead to deficits in exploration and failure to suckle.
Protocol for the Optimune trial: a randomized controlled trial evaluating a novel Internet intervention for breast cancer survivors
Authors: Holtdirk Franziska , Mehnert Anja , Weiss Mario , Meyer Björn , Watzl Carsten
Published: January 2020

Introduction

Depression and fatigue are common in breast cancer survivors, and their presence is associated with personal suffering and worse prognosis. While many women receive short-term psychological support in the acute treatment phase, this is rarely available in subsequent phases. Internet interventions for breast cancer survivors could provide additional psychological support, as they are easily accessible and may be effective. However, no trial has yet examined the effectiveness of an Internet intervention that provides cognitive behavioural therapy techniques plus lifestyle advice for this population. This trial aims to test whetherOptimune, a novel Internet intervention we developed for that purpose, leads to improvements in quality of life and relevant lifestyle habits over the course of 3 to 6 months.

Methods

This randomized controlled trial (RCT) will include 360 female breast cancer survivors who have completed the active tumour eradication phase. Participants will be recruited from various settings, including web-based advertisements and Internet forums in German-speaking countries. The main inclusion criteria are a breast cancer diagnosis less than 5 years ago and completion of acute treatment at least 1 month ago, as verified by discharge letter from an oncology treatment centre. Participants will be randomly assigned to either (1) a control group, in which they receive care as usual (CAU) and are given access toOptimuneafter a delay of 3 months (CAU/wait list control), or (2) a treatment group that may also use CAU and will receive 12-month access toOptimuneimmediately after randomization. The three primary endpoints are quality of life, physical activity and diet quality, assessed with the World Health Organization Quality of Life Questionnaire, the International Physical Activity Questionnaire and the Food Quality Questionnaire, at 3 months post-baseline; secondary outcomes include cancer-related fatigue, emotional stress, depression, anxiety, fear of progression, insomnia, usefulness of the programme and negative treatment effects. Online assessments are conducted at baseline (T0), 3 months (T1) and 6 months (T2).

Discussion

Results of this RCT are expected to extend the body of knowledge with regard to the effectiveness of CBT-based Internet interventions for female breast cancer survivors.

Trial registration

ClinicalTrials.gov,NCT03643640. Registered on 23 August 2018.
Streamlining and cycle time reduction of the startup phase of clinical trials
Authors: Abu-Shaheen Amani , Al Badr Ahmad , Al Fayyad Isamme , Al Qutub Adel , Faqeih Eissa Ali , Al-Tannir Mohamad
Published: January 2020

Objective

The startup phase of a clinical trial (CT) plays a vital role in the execution of new drug development. Hence, the aim of this study is to identify the factors responsible for delaying the CT startup phase. Further, it focuses on streamlining and reducing the cycle time of the startup phase of newly sponsored CTs.

Methods

Thirteen sponsored CTs conducted between 2016 and 2017 at the Clinical Research Department of King Fahad Medical City, Riyadh, Saudi Arabia, were considered for this study. Eight trials were analyzed to identify the data specific to startup metrics using the FOCUS–PDCA cycle (Find an improvement area–Organize a team–Clarify current practices–Understand the source of variation/problem–Select a Strategy–Plan–Do–Check–Act). Six measures incorporated in the metrics were (1) date of initial contact with site to the signing of confidentiality agreement, (2) date of receiving questionnaire from sponsor to date of its completion, (4) time taken to review protocol and approve investigational drug service form, and (5) time taken to study protocol and approve pharmacy and pathology and clinical laboratory medicine form and date of receipt of institutional review board (IRB) submission package to final IRB approval. Fishbone analysis was used to understand the potential causes of process variation. Mean (SD) time was calculated for each metric before and after implementation of the intervention protocol to analyze and compare percentage reduction in the mean cycle time of CTs. Data were represented as mean (SD), and the P value was calculated for each metric. The significance level was set at P < 0.05.

Results

Of the various potential factors of delay identified through fishbone analysis, the two major ones were lack of a well-defined timeline for approval and review of the study protocol and inconsistent IRB meetings. After introduction of the new intervention protocol, the entire CT life cycle was reduced by 45.6% (mean [SD], 24.8 [8.2] weeks vs. 13.5 [11.6] weeks before and after the intervention, respectively).

Conclusion

Various factors are responsible for the delay of the startup phase of CTs, and understanding the impact of each element allows for optimization and faster execution of the startup phase of CTs.
A 14-year-old female with fever, rash, lymphadenopathy, and pancytopenia: a case report
Authors: Varshochi Mojtaba , Ravanbakhsh Gavgani Reyhaneh , Naghili Behrooz , Bayatmakoo Zhinus , Poorshahverdi Parinaz , Ravanbakhsh Gavgani Fatemeh
Published: January 2020

Background

Anticonvulsant hypersensitivity syndrome is a rare adverse drug reaction associated with aromatic anticonvulsant drugs. This syndrome can range from mild cutaneous rash to drug reaction with eosinophilia and systemic symptoms that include fever, rash, lymphadenopathy, pancytopenia, and involvement of multiple internal organs. We aimed to report this case in the literature and make physicians aware of the uncommon symptoms of this syndrome when they prescribe antiepileptic medications in particular.

Case presentation

A 14-year-old Middle Eastern female patient from Iran with free past medical and allergic history was admitted to hospital because of fever, rash, lymphadenopathy, and pancytopenia after taking anticonvulsants due to new-onset seizure. High fever and cutaneous rash along with lymphadenopathy following administration of anticonvulsant medications that could not be explained by other causes alerted the physician to the possibility of this syndrome. Our investigation revealed no further diagnosis and 1 week after discontinuation of the drugs, her symptoms were resolved. Anticonvulsant hypersensitivity syndrome is a diagnosis of exclusion and immediate discontinuation of the suspicious drugs is necessary. Hence, early recognition can prevent permanent multiorgan damage.

Conclusions

Chlorpheniramine as a simple treatment was provided for this syndrome.
A systematic literature review of the influence of the university’s environment and support system on the precursors of social entrepreneurial intention of students
Authors: Bazan Carlos , Gaultois Hannah , Shaikh Arifusalam , Gillespie Katie , Frederick Sean , Amjad Ali , Yap Simon , Finn Chantel , Rayner James , Belal Nafisa
Published: January 2020

This systematic literature review aims at understanding the influence of the university’s environment and support system (ESS) in shaping the social entrepreneurial intention (SEI) of post-secondary education students. Social entrepreneurs play an important role in the economic and social developments of the communities in which they operate, thus many post-secondary institutions are starting to encourage more students to engage in social entrepreneurial behaviour. Consequently, there is a need for systematic approaches to evaluate the impact of various motivational factors related to the university’s entrepreneurial ecosystem that could affect the SEI of students. Based on a systematic literature review and narrative synthesis of the antecedents of the SEI of post-secondary education students, the authors proposed a customized SEI model that modifies and extend the one proposed by Hockerts (Entrepreneurship: Theory and Practice, 2017) and Mair and Noboa (Social entrepreneurship, 2006). This study fills a gap in the literature by providing a methodology grounded in theory that can help universities to design their educational and other interventions aimed at encouraging more students to consider social entrepreneurship as a viable career choice after graduation.
Learning-based power prediction for geo-distributed Data Centers: weather parameter analysis
Authors: Taheri Somayyeh , Goudarzi Maziar , Yoshie Osamu
Published: January 2020

Nowadays, the fast rate of technological advances, such as cloud computing, has led to the rapid growth of the Data Center (DC) market as well as their power consumption. Therefore, DC power management has become increasingly important. While power forecasting can greatly help DC power management and reduce energy consumption and cost. Power forecasting predicts the potential energy failures or sudden fluctuations in power intake from utility grid. However, it is hard especially when variable renewable energies (RE) as well as free cooling such as air economizers are also used. Geo-distributed DCs face an even harder issue: since in addition to local conditions, the overall status of the entire system of collaborating DCs should also be considered. The conventional approach to forecast power consumption in such complicated cases is to construct a closed form formula for power. This is a tedious task that not only needs expert knowledge of how each single cooling or RE system works, but also needs to be done individually for each DC and repeated all over again for each new DC or change of equipment. One alternative is to use machine learning so as to learn over time how the system consumes power in varying conditions of weather, workload, and internal structure in multiple geo-distributed locations. However, due to the wide range of effective features as well as trade-off between the accuracy and processing overhead, one important issue is to obtain an optimal set of more influential features. In this study, we analyze the correlation among geo-distributed DC power patterns with their weather parameters (based on different DC situations and infrastructure) and extract a set of influential features. Afterward, we apply the obtained features to provide a power consumption forecasting model that predict the power pattern of each collaborating DC in a cloud. Our experimental results show that the proposed prediction model for geo-distributed DCs reaches the accuracy of 87.2%.
Molecular diversity of extended-spectrum β-lactamases and carbapenemases, and antimicrobial resistance
Authors: Sawa Teiji , Kooguchi Kunihiko , Moriyama Kiyoshi
Published: January 2020

Along with the recent spread of multidrug-resistant bacteria, outbreaks of extended-spectrum β-lactamase (ESBL) and carbapenemase-producing bacteria present a serious challenge to clinicians. β-lactam antibiotics are the most frequently used antibacterial agents and ESBLs, and carbapenemases confer resistance not only to carbapenem antibiotics but also to penicillin and cephem antibiotics. The mechanism of β-lactam resistance involves an efflux pump, reduced permeability, altered transpeptidases, and inactivation by β-lactamases. Horizontal gene transfer is the most common mechanism associated with the spread of extended-spectrum β-lactam- and carbapenem resistance among pathogenic bacterial species. Along with the increase in antimicrobial resistance, many different types of ESBLs and carbapenemases have emerged with different enzymatic characteristics. For example, carbapenemases are represented across classes A to D of the Ambler classification system. Because bacteria harboring different types of ESBLs and carbapenemases require specific therapeutic strategies, it is essential for clinicians to understand the characteristics of infecting pathogens. In this review, we summarize the current knowledge on carbapenem resistance by ESBLs and carbapenemases, such as class A carbapenemases, class C extended-spectrum AmpC (ESAC), carbapenem-hydrolyzing class D β-lactamases (CHDLs), and class B metallo-β-lactamases, with the aim of aiding critical care clinicians in their therapeutic decision making.
Hemodynamic effects of intravenous paracetamol in critically ill children with septic shock on inotropic support
Authors: Nahum Elhanan , Weissbach Avichai , Kaplan Eytan , Kadmon Gili
Published: January 2020

Background

Treatment with intravenous paracetamol may impair hemodynamics in critically ill adults. Few data are available in children. The aim of this study was to investigate the frequency, extent, and risk factors of hypotension following intravenous paracetamol administration in children with septic shock on inotropic support.

Methods

We retrospectively reviewed the electronic medical charts of all children aged 1 month to 18 years with septic shock who were treated with intravenous paracetamol while on inotropic support at the critical care unit of a tertiary pediatric medical center in 2013–2018. Data were collected on patient demographics, underlying disease, Pediatric Logistic Organ Dysfunction (PELOD) score, hemodynamic parameters before and up to 120 min after paracetamol administration, and need for inotropic support or intravenous fluid bolus. The main outcome measures were a change in blood pressure, hypotension, and hypotension requiring intervention.

Results

The cohort included 45 children of mean age 8.9 ± 5.1 years. The mean inotropic support score was 12.1 ± 9.5. A total of 105 doses of paracetamol were administered. The lowest mean systolic pressure (108 ± 15 mmHg) was recorded at 60 min (p = 0.002). Systolic blood pressure decreased at 30, 60, 90, and 120 min after delivery of 50, 67, 61, and 59 drug doses, respectively. There were 5 events of systolic hypotension (decrease of 1 to 16 mmHg below systolic blood pressure hypotensive value). Mean arterial pressure decreased by ≥ 15% in 8 drug doses at 30 min (7.6%, mean − 19 ± 4 mmHg), 18 doses at 60 min (17.1%, mean − 20 ± 7 mmHg), 16 doses at 90 min (15.2%, mean − 20 ± 5 mmHg), and 17 doses at 120 min (16.2%, mean − 19 ± 5 mmHg). Mean arterial hypotension occurred at the respective time points in 2, 13, 10, and 9 drug doses. After 12 drug doses (11.4%), patients required an inotropic dose increment or fluid bolus.

Conclusions

Hypotensive events are not uncommon in critically ill children on inotropic support treated with intravenous paracetamol, and physicians should be alert to their occurrence and the need for intervention.
Climatic and anthropogenic factors explain the variability of Fagus sylvatica treeline elevation in fifteen mountain groups across the Apennines
Authors: Bonanomi Giuliano , Zotti Maurizio , Mogavero Valentina , Cesarano Gaspare , Saulino Luigi , Rita Angelo , Tesei Giulio , Allegrezza Marina , Saracino Antonio , Allevato Emilia
Published: January 2020

Background

Fagus sylvatica forms the treeline across the Apennines mountain range, with an average elevation of 1589 m a.s.l. Previous studies evidenced that the current position of the treeline in the Apennines is heavily depressed as a result of a complex interaction between climatic factors and the past human pressure. In this study we correlated treeline elevation in the fifteen major mountain groups in the Apennines with selected climatic, geomorphological, and human disturbance variables in order to investigate in detail the site-specific features affecting the current treeline distribution.

Results

Treeline elevation was lowest in the North Italy (Apuan Alps), while the highest treeline was found in Central Italy (Simbruini). An absolute maximum treeline elevation of F. sylvatica exceeding 2000 m a.s.l. was found on 13 mountain peaks in Central and Southern Italy. Noteworthy, treeline elevation was largely lower on warmer south-facing slopes compared to northern slopes, with values several hundred meters lower in the Gran Sasso and Velino-Sirente. Although the causes of this pattern are still unknown, we argue that treeline elevation on south-facing slopes may be limited by the combination of climatic constraints (i.e. summer drought) and human disturbance. Evidence of a pervasive anthropogenic effect depressing treeline elevation was found in the North (Apuan Alps) Central (Gran Sasso, Velino-Sirente, Sibillini) and Southern part of Apennines (Pollino). By contrast, treeline elevation of the Laga, Simbruini, and Orsomarso mountain groups appears less affected by past anthropogenic disturbance. Finally, we recorded in the several mountain groups (i.e. Majella, Marsicani and Pollino) the coexistence of very depressed treelines just a few kilometers away from much higher treelines, among the highest ever recorded for F. sylvatica.

Conclusions

Finally, we argue that F. sylvatica treeline across the Apennines is locally shaped both by the interaction of low temperatures experienced by the species in its earliest life stages in snow-free open spaces with summer soil water depletion and human disturbance.
Automated GMP compliant production of [18F]AlF-NOTA-octreotide
Authors: Tshibangu Térence , Cawthorne Christopher , Serdons Kim , Pauwels Elin , Gsell Willy , Bormans Guy , Deroose Christophe M. , Cleeren Frederik
Published: January 2020

Background

Gallium-68 labeled synthetic somatostatin analogs for PET/CT imaging are the current gold standard for somatostatin receptor imaging in neuroendocrine tumor patients. Despite good imaging properties, their use in clinical practice is hampered by the low production levels of68Ga eluted from a68Ge/68Ga generator. In contrast,18F-tracers can be produced in large quantities allowing centralized production and distribution to distant PET centers. [18F]AlF-NOTA-octreotide is a promising tracer that combines a straightforward Al18F-based production procedure with excellent in vivo pharmacokinetics and specific tumor uptake, demonstrated in SSTR2 positive tumor mice. However, advancing towards clinical studies with [18F]AlF-NOTA-octreotide requires the development of an efficient automated GMP production process and additional preclinical studies are necessary to further evaluate the in vivo properties of [18F]AlF-NOTA-octreotide. In this study, we present the automated GMP production of [18F]AlF-NOTA-octreotide on the Trasis AllinOne® radio-synthesizer platform and quality control of the drug product in accordance with GMP. Further, radiometabolite studies were performed and the pharmacokinetics and biodistribution of [18F]AlF-NOTA-octreotide were assessed in healthy rats using μPET/MR.

Results

The production process of [18F]AlF-NOTA-octreotide has been validated by three validation production runs and the tracer was obtained with a final batch activity of 10.8 ± 1.3 GBq at end of synthesis with a radiochemical yield of 26.1 ± 3.6% (dc), high radiochemical purity and stability (96.3 ± 0.2% up to 6 h post synthesis) and an apparent molar activity of 160.5 ± 75.3 GBq/μmol. The total synthesis time was 40 ± 3 min. Further, the quality control was successfully implemented using validated analytical procedures. Finally, [18F]AlF-NOTA-octreotide showed high in vivo stability and favorable pharmacokinetics with high and specific accumulation in SSTR2-expressing organs in rats.

Conclusion

This robust and automated production process provides high batch activity of [18F]AlF-NOTA-octreotide allowing centralized production and shipment of the compound to remote PET centers. Further, the production process and quality control developed for [18F]AlF-NOTA-octreotide is easily implementable in a clinical setting and the tracer is a potential clinical alternative for somatostatin directed68Ga labeled peptides obviating the need for a68Ge/68Ga-generator. Finally, the favorable in vivo properties of [18F]AlF-NOTA-octreotide in rats, with high and specific accumulation in SSTR2 expressing organs, supports clinical translation.
High-resolution reservoir characterization using deep learning-aided elastic full-waveform inversion: The North Sea field data example
Authors: Zhang Zhen-dong , Alkhalifah Tariq
Published: January 2020

Reservoir characterization is an essential component of oil and gas production, as well as exploration. Classic reservoir characterization algorithms, deterministic and stochastic, are typically based on stacked images and rely on simplifications and approximations to the subsurface (e.g., assuming linearized reflection coefficients). Elastic full-waveform inversion (FWI), which aims to match the waveforms of prestack seismic data, potentially provides more accurate high-resolution reservoir characterization from seismic data. However, FWI can easily fail to characterize deep-buried reservoirs due to illumination limitations. We have developed a deep learning-aided elastic FWI strategy using observed seismic data and available well logs in the target area. Five facies are extracted from the well and then connected to the inverted P- and S-wave velocities using trained neural networks, which correspond to the subsurface facies distribution. Such a distribution is further converted to the desired reservoir-related parameters such as velocities and anisotropy parameters using a weighted summation. Finally, we update these estimated parameters by matching the resulting simulated wavefields to the observed seismic data, which corresponds to another round of elastic FWI aided by the a priori knowledge gained from the predictions of machine learning. A North Sea field data example, the Volve Oil Field data set, indicates that the use of facies as prior knowledge helps resolve the deep-buried reservoir target better than the use of only seismic data.
Health Insurance Literacy and Financial Hardship in Women Living With Metastatic Breast Cancer
Authors: Williams Courtney P. , Pisu Maria , Azuero Andres , Kenzik Kelly M. , Nipp Ryan D. , Aswani Monica S. , Mennemeyer Stephen T. , Pierce Jennifer Y. , Rocque Gabrielle B.
Published: January 2020

PURPOSE:

In patients with metastatic breast cancer (MBC), low health insurance literacy may be associated with adverse material conditions, psychological response, and coping behaviors because of financial hardship (FH). This study explored the relationship between health insurance literacy and FH in women with MBC.

METHODS:

This cross-sectional study used data collected from 84 women receiving MBC treatment at 2 southeastern cancer centers. Low health insurance literacy was defined as not knowing premium or deductible costs. FH was defined by lifestyle changes as a result of medical expenses, financial toxicity, and medical care modifications attributable to cost. Mean differences were calculated using Cramer’s V. Associations between health insurance literacy and FH were estimated with adjusted linear models.

RESULTS:

Half of the surveyed patients had low health insurance literacy, 26% were underinsured, 45% had private insurance, 39% had Medicare, and 15% had Medicaid. Patients with low health insurance literacy more often reported borrowing money (19% v 4%; V = 0.35); an inability to pay for basic necessities like food, heat, or rent (10% v 4%; V = 0.18); and skipping a procedure (8% v 1%; V = 0.21), medical test (7% v 0%; V = 0.30), or treatment (4% v 0%; V = 0.20) compared with patients with high health insurance literacy. Median Comprehensive Score for Financial Toxicity was 23 (interquartile range, 17-29). In adjusted models, health insurance literacy was not associated with financial toxicity.

CONCLUSION:

Low health insurance literacy was common in women receiving MBC treatment. Additional research to increase health insurance literacy could lessen undesirable material FH and unnecessary behavioral FH associated with cancer-related care.
Distribution of Tri-Ponderal Mass Index and its Relation to Body Mass Index in Children and Adolescents Aged 10 to 20 Years
Authors: Park Hong Kyu , Shim Young Suk
Published: January 2020

Context

Body mass index percentiles are widely used to determine overweight and obesity status in children and adolescents. Their limitations in clinical settings can be addressed.

Objective

Reference ranges for the tri-ponderal mass index percentiles of Korean children and adolescents are presented for a comparison of their clinical variables with those of body mass index.

Design

Cross-sectional study.

Setting

Korea National Health and Nutrition Examination Survey, 2007–2016.

Patients

Korean children and adolescents aged 10 to 20 years.

Main Outcome Measures

The age- and sex-specific least mean square parameters (skewness, median, and coefficient of variation) for the tri-ponderal mass index of 9749 subjects aged 10 to 20 years.

Results

The factors associated with metabolic syndrome, except diastolic blood pressure, were more likely to be worse in the subjects with tri-ponderal mass index values indicative of overweight status than in those with normal tri-ponderal mass index values. Body mass index tends to underestimate obesity-related comorbidities more than tri-ponderal mass index does.

Conclusion

The tri-ponderal mass index standard deviation score may be advantageous when defining overweight and obesity in children and adolescents.
Rethinking Student Resistance from a Developmental Perspective
Authors: Harrington Dana , Wheeler Anne C.
Published: January 2020

Resistance narratives in composition studies often focus on how students resist pedagogies that challenge their received values and identities. These narratives ignore the complex developmental trajectory that students face in the writing classroom. The authors apply a developmental framework to this resistance and argue that helping students work through these challenges is essential to developing complex ways of seeing themselves as writers and citizens.
The Possibilities of Uncertainty
Authors: Daniel-Wariya Joshua , Lewis Lynn C.
Published: January 2020

This article describes the rationale, development, and implementation of a digital archival curriculum within the first-year composition program at Oklahoma State University. Such a curriculum helps students engage genuine inquiry to discover arguments rather than defend their existing beliefs. Analytic complexity and hidden information are offered as potential sources of uncertainty.
From Commonplaces to Consciousness
Authors: Stinnett Jerry
Published: January 2020

In many ways, the transformative character of developing critical consciousness reflects the dynamics of acquiring threshold concepts. Drawing from research into threshold concept acquisition, the author argues that critical first-year composition instruction can more effectively scaffold students into critical perspectives by linking critical pedagogy more closely with efforts to develop students’ rhetorical meta-awareness of writing.
Experimenting with Career Concerns
Authors: Halac Marina , Kremer Ilan
Published: January 2020

A manager who learns privately about a project over time may want to delay quitting it if recognizing failure/lack of success hurts his reputation. In the banking industry, managers may want to roll over bad loans. How do distortions depend on expected project quality? What are the effects of releasing public information about quality? A key feature of banks is that managers learn about project quality from bad news, i.e., a default. We show that in such an environment, distortions tend to increase with expected quality and imperfect information about quality. Results differ if managers instead learn from good news. (JEL D82, D83, G21)
СОЗДАНИЕ ФУНКЦИОНАЛЬНОЙ МОДЕЛИ ИНФОРМАЦИОННОЙ СИСТЕМЫ УПРАВЛЕНИЯ ДЛЯ АВТОМАТИЗАЦИИ ПРОЦЕССА РАСПРЕДЕЛЕНИЯ ЗАДАЧ ПРЕДПРИЯТИЯ
Authors: Eremina Irina Ilinichna , Ishmuradova Izida Ildarovna , Lysanov Denis Mihailovich
Published: January 2020

Представленное исследование посвящено разработке автоматизированной информационной системы оценки эффективности маркетинговых мероприятий, выявлены особенностей разработки информационной системы эффективности проведения маркетинговых мероприятий, с учетом динамики влияния внешних и внутренних факторов средствами платформы 1С: Предприятие.
ПРОЕКТИРОВАНИЕ ИНФОРМАЦИОННОЙ СИСТЕМЫ УПРАВЛЕНИЯ ЭНЕРГОРЕСУРСАМИ В СФЕРЕ ЖИЛИЩНОГО ХОЗЯЙСТВА
Authors: Lysanov Denis Mihailovich , Eremina Irina Ilinichna , Ishmuradova Izida Ildarovna
Published: January 2020

В статье рассматриваются вопросы, связанные с совершенствованием сферы жилищно-коммунального хозяйства: разработка регулирующих, управляющих конфигураций оборудования, изменение параметров работы в режиме реального времени, дистанционный сбор данных с приборов учета, регулировка объемов предоставленных коммунальных услуг. Все это позволит улучшить мониторинг функционирования системы сбора данных о полученных коммунальных услугах и повысить оперативность выявления энергетических потерь в системе.
ФОРМИРОВАНИЕ СТРУКТУРНО-ЭНЕРГЕТИЧЕСКИХ ПАРАМЕТРОВ РАБОЧИХ ПОВЕРХНОСТЕЙ ВЫСОКОТОЧНЫХ ДЕТАЛЕЙ ПРИ ЭКСПЛУАТАЦИИ АВТОМОБИЛЬНОГО ТРАНСПОРТА
Authors: Tukhvatullin Bulat Talirovich , Levchenko Dmitry Vladimirovich , Stebailov Maxim Yurevich
Published: January 2020

В работе на основе анализа рассмотрен износ деталей при эксплуатации автомобильного транспорта, а именно в высокоточных деталях, сопряженных нагрузками и трением, что приводит к упругому и пластическому деформированию и как итог разрушение поверхностного слоя и образование частиц износа в результате многократного воздействия, вызывая преждевременный выход из строяя высокоточных деталей.
ОСОБЕННОСТИ АЛГОРИТМА УПРАВЛЕНИЯ СИСТЕМАМИ ПЕРЕВОЗОК
Authors: Lvovich Yakov Yevseevich , Preobrazhenskiy Andrey Petrovich , Choporov Oleg Nikolaevich
Published: January 2020

В данной статье рассматриваются вопросы, связанные с построением алгоритма, позволяющего оценить возможности развития систем перевозок. Приводится алгоритм принятия решения по выбору возможностей развития систем перевозок. Даны результаты, исходя из работы алгоритмов.
Organizational Culture and Educational Innovations in Turkish Higher Education: Perceptions and Reactions of Students
Authors: Caliskan Aysun , Zhu Chang
Published: January 2020

With the enormous scientific and technological developments, higher education institutions are facing rapid structural, social, technological changes. Because they are considered as an important center of talent development and knowledge production and sharing for countries. To fulfill their educational, social and economic needs, higher education institutions need to respond to changing education needs, to adopt the more flexible modes of organizational culture.  Organizational culture is a promotive environment which influences values, assumptions and beliefs. In an innovative culture, people can easily develop new ideas and exhibit collaboration. Therefore, this paper examines the relationship between the organizational culture features and the perceptions and student reported implementation with regard to student-centered learning, collaborative learning and use of innovative educational technologies in Turkish higher education. Four universities were involved, and 894 students responded to a questionnaire comprising three groups of questions. The three groups of questions capture (i) demographic characteristics, (ii) student perceptions of organizational culture, (iii) students’ perceptions of and responses to educational innovations comprising the following scales in a survey study. The results show that features of organizational culture affect students’ perceived need for innovation, their views about innovative approaches to instruction, responsiveness to instructional innovations and the perceived implementation level of educational innovations. In addition, differences among the institutions were examined and discussed. The study concludes that hierarchical structure, lack of open communication and autonomy, workload, lack of financial resources and support are main barriers for educational innovations in Turkish universities. It also implies to understand the link between organizational culture and educational innovations in Turkish higher education context.
Data Analysis: Strengthening Inferences in Quantitative Education Studies Conducted by Novice Researchers
Authors: Abulela Mohammed A. A. , Harwell Michael
Published: January 2020

Data analysis is a significant methodological component when conducting quantitative education studies. Guidelines for conducting data analyses in quantitative education studies are common but often underemphasize four important methodological components impacting the validity of inferences: quality of constructed measures, proper handling of missing data, proper level of measurement of a dependent variable, and model checking. This paper highlights these components for novice researchers to help ensure statistical inferences are valid. We used empirical examples involving contingency tables, group comparisons, regression analysis, and multilevel modelling to illustrate these components using the Program for International Student Assessment (PISA) data. For every example, we stated a research question and provided evidence related to the quality of constructed measures since measures with weak reliability and validity evidence can bias estimates and distort inferences. The adequate strategies for handling missing data were also illustrated. The level of measurement for the dependent variable was assessed and the proper statistical technique was utilized accordingly. Model residuals were checked for normality and homogeneity of variance. Recommendations for obtaining stronger inferences and reporting related evidence were also illustrated. This work provides an important methodological resource for novice researchers conducting data analyses by promoting improved practice and stronger inferences.
Future Expectations Modeling, Random Coefficient Forward–Backward Stochastic Differential Equations, and Stochastic Viscosity Solutions
Authors: Kartala Xanthi-Isidora , Englezos Nikolaos , Yannacopoulos Athanasios N.
Published: January 2020

In this paper we study a class of infinite horizon fully coupled forward–backward stochastic differential equations (FBSDEs) with random coefficients that are stimulated by various continuous time future expectations models. Under standard Lipschitz and monotonicity conditions and by means of the contraction mapping principle, we establish existence and uniqueness of an adapted solution, and we obtain results regarding the dependence of this solution on the data of the problem. Making further the connection with finite horizon quasilinear backward stochastic partial differential equations via a generalization of the well known four-step-scheme, we are led to the notion of stochastic viscosity solutions. As an application of this framework, we also provide a stochastic maximum principle for the optimal control problem of such FBSDEs, which in the linear-quadratic Markovian case boils down to the solvability of an infinite horizon fully coupled system of forward-backward Ricatti differential equations.
Experiencing the Detection of Radicalized Criminals on Facebook Social Network and Data-related Issues
Authors: Tundis Andrea , Böck Leon , Stanilescu Victoria , Mühlhäuser Max
Published: January 2020

Online social networks (OSNs) represent powerful digital tools to communicate and quickly disseminate information in a non-official way. As they are freely accessible and easy to use, criminals abuse of them for achieving their purposes, for example, by spreading propaganda and radicalising people. Unfortunately, due to their vast usage, it is not always trivial to identify criminals using them unlawfully. Machine learning techniques have shown benefits in problem solving belonging to different application domains, when, due to the huge dimension in terms of data and variables to consider, it is not feasible their manual assessment. However, since the OSNs domain is relatively young, a variety of issues related to data availability makes it difficult to apply and immediately benefit from such techniques, in supporting the detection of criminals on OSNs. In this perspective, this paper wants to share the experience conducted in using a public dataset containing information related to criminals in order to both (i) extract specific features and to build a model for the detection of terrorists on Facebook social network, and (ii) to highlight the current limits. The research methodology as well as the gathered results are fully presented and then the data-related issues, emerged from this experience, are discussed.

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Towards Light Weight Cryptography Schemes for Resource Constraint Devices in IoT
Authors: Jadhav Santosh Pandurang
Published: January 2020

The Internet of Things (IoT) is becoming the most relevant next Internet-related revolution in the world of Technology. It permits millions of devices to be connected and communicate with each other. Beside ensuring reliable connectivity their security is also a great challenge. Abounding IoT devices have a minimum of storage and processing capacity and they usually need to be able to operate on limited power consumption. Security paths that depend maximum on encryption are not good for these resource constrained devices, because they are not suited for performing complicated encryption and decryption tasks quickly to be able to transmit data securely in real-time. This paper contains an overview of some of the cryptographic-based schemes related to communication and computational costs for resource constrained devices and considers some approaches towards the development of highly secure and lightweight security mechanisms for IoT devices.
GREEN WATER FOOTPRINT AND SUSTAINABILITY FOR ESPIRITO SANTO STATE
Authors: Zanetti Sidney Sara , De Andrade Maria Sueliane Santos , Cecílio Roberto Avelino
Published: January 2020

Water footprint is a relatively new concept of freshwater appropriation that considers its direct and indirect use by a consumer or producer and used as a comprehensive indicator of the appropriation of water resources. The objective of this study was to estimate the green water footprint and evaluate its sustainability in the state of Espírito Santo, using the land use information and indicators of water scarcity. The total green water footprint was estimated by the sum of the green water footprints of pasture, forest, coffee cultivation, forestry, and other agricultural uses. The state’s total green footprint estimated was 47.5 billion m³/year, and the pasture class represented 48.5% of this total, followed by forest (29.8%), coffee cultivation (10.1%), forestry (6.4%), and other crops (5.2%). The ratio between the mean annual total volume of precipitated water and the green WF in the state was 80%. The environmental sustainability assessment shows that the green footprint was unsustainable for most of the year, on average, mainly in the May to September.
Proposed a self-absorption internal standard model to detect element concentrations of complex constituent material with a single emission line of element in laser plasmas
Authors: He Gui-Cang , Shi Li-Na , Hua Yi-Lei , Niu Jie-Bin , Lu Cheng , Xie Chang-Qing
Published: January 2020

Laser induced plasmas (LIPs) method is a highly regarded approach to evaluate the chemical composition of materials. But the strong self-absorption of the radiation seriously affects its accuracy. Meanwhile, the model based on self-absorption phenomenon makes its application very difficult. In this work, a self-absorption internal standard (SAIS) model is proposed for detection of the multi-element concentrations of complex constituent material with a single emission line of the element in laser plasmas. A typical LIPs experiment system is set up to generate plasmas, and the soil is selected as a test sample. The average electron temperature (0.975 eV) and electron density (1.44×1018 cm-3) are determined by the Boltzmann plot and emission lines Stark broadening, respectively. The plasmas are diagnosed as in local thermodynamic equilibrium condition. The emission lines selected to calculate the concentration of sample contain a wide set of kt values (0.575×10−30∼37.2×10−30 m3). Then, the concentrations of some elements are calculated by the model using single emission line of each element. It is found that the concentrations of the five elements (Ti, Fe, Mg, Al, Si) calculated by SAIS model are relatively consistent with the results of the traditional chemical testing methods. This indicated that the SAIS model is an effective and neat method for multi-element concentrations detection of complex constituent materials.
Data processing and performance evaluation of a tempo-spatially mixed modulation imaging Fourier transform spectrometer based on stepped micro-mirror
Authors: Zhao Baixuan , Lv Jinguang , Ren Jun , Qin Yuxin , Tao Jin , Liang Jingqiu , Wang Weibiao
Published: January 2020

A novel tempo-spatially mixed modulation imaging Fourier transform spectrometer based on a stepped micro-mirror has the advantages of high throughput, compactness, and stability. In this paper, we present a method of image- and spectrum-processing and performance evaluation, which is utilized to obtain a high-quality reconstructed image without stitching gaps and a reconstructed spectrum with significantly reduced noise and side-lobe oscillation. A theoretical model of instrument line shape and signal-to-noise ratio is established to verify the effectiveness of non-uniformity sampling correction and spectral resolution enhancement. Meanwhile, the performance of the instrument was evaluated combined with experimental results.
Compact silicon photonic hybrid ring external cavity (SHREC)/InGaSb-AlGaAsSb wavelength-tunable laser diode operating from 1881-1947 nm
Authors: Sia Jia Xu Brian , Wang Wanjun , Qiao Zhongliang , Li Xiang , Guo Xin , Zhou Jin , Littlejohns Callum G. , Zhang Zecen , Liu Chongyang , Reed Graham T. , Wang Hong
Published: January 2020

In recent years, the 2 µm waveband has been gaining significant attention due to its potential in the realization of several key technologies, specifically, future long-haul optical communications near the 1.9 µm wavelength region. In this work, we present a hybrid silicon photonic wavelength-tunable diode laser with an operating range of 1881-1947 nm (66 nm) for the first time, providing good compatibility with the hollow-core photonic bandgap fiber and thulium-doped fiber amplifier. Room-temperature continuous-wave operation was achieved with a favorable on-chip output power of 28 mW. Stable single-mode lasing was observed with side-mode suppression ratio up to 35 dB. Besides the abovementioned potential applications, the demonstrated wavelength region will find critical purpose in H2O spectroscopic sensing, optical logic, signal processing as well as enabling the strong optical Kerr effect on Si.