bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pengaruh Lama Aerasi yang Berbeda Terhadap Pertumbuhan Populasi dan Kualitas Warna dari Kutu Air Raksasa (Daphnia magna)
Authors: Gideon Pierre Charismanuel , Sucahyo Sucahyo , Hastuti Susanti Pudji 
Published: August 2022

Salah satu pakan alami yang paling baik dalam budidaya perikanan adalah D. magna yang sudah banyak dibudidayakan dan dapat diambil langsung dari alam, namun belum cukup dalam memenuhi kebutuhan. Untuk itu penelitian ini bertujuan untuk mengetahui pengaruh pertumbuhan populasi dan kualitas warna dari D. magna berdasarkan lama aerasi sehingga dapat mengetahui lama aerasi yang paling optimal untuk kultur D. magna. Penelitian ini dilaksanakan dengan membuat tiga faktor perlakuan dan satu faktor kontrol. Faktor kontrol adalah tanpa aerasi, faktor A dengan aerasi 3 jam/hari, faktor B dengan aerasi 6 jam/hari, dan faktor C dengan 24 jam aerasi. Masing – masing faktor memiliki 3 kali pengulangan. Hasil penelitian menunjukkan bahwa lama waktu aerasi 3 jam/hari adalah faktor paling optimal dalam menunjang pertumbuhan populasi D. magna dan faktor kontrol yaitu tanpa pemberian aerasi paling optimal dalam menunjang warna D. magna. Hasil analisis data dalam uji Friedman menunjukkan adanya perbedaan pengaruh pada pertumbuhan D. magna. Hasil pengukuran kualitas air menunjukan kadar DO cenderung turun bahkan melewati batas minimum, namun pada faktor C kadar DO masih dalam kadar optimal. Suhu berkisar 24.1 – 30.6 ℃ dan pH berkisar 6.3 – 7.0. Kondisi ini masih dalam kisaran optimum untuk kultur D. magna. One of the best natural feeds in aquaculture is D. magna which has been widely cultivated and can be taken directly from nature, but is not sufficient to meet the needs. For this reason, this study aims to determine the effect of population growth and color quality of D. magna based on aeration time so that can determine the most optimal aeration time for D. magna culture. This research was conducted by making three treatment factors and one control factor. The control factor was without aeration, factor A with aeration 3 hours/day, factor B with aeration 6 hours/day, and factor C with 24 hours aeration respectively. Each factor has 3 repetitions. The results showed that aeration time of 3 hours/day was the most optimal factor in supporting the growth of D. magna population and the control factor without aeration was the most optimal in supporting the color of D. magna. The results of data analysis in the Friedman test showed there were different effect on the growth of D. magna. The results of water quality measurements show that DO levels tend to fall even past the minimum limit, but in factor C, DO levels are still in optimal levels. The measurement of temperature ranges from 24.1 – 30.6 and the pH ranges from 6.3 – 7.0. This condition was still in the optimum range for D. magna culture
Khasminskii-type theorem for a class of stochastic functional differential equations
Authors: Ma Li , Wang Ru , Yan Liangqing 
Published: August 2022

Abstract
This paper is concerned with the existence and uniqueness theorems for stochastic functional differential equations with Markovian switching and jump, where the linear growth condition is replaced by more general Khasminskii-type conditions in terms of a pair of Lyapunov-type functions.
Low IGF1 and high IGFBP1 predict diabetes onset in prediabetic patients
Authors: Meyer Nina M T , Kabisch Stefan , Dambeck Ulrike , Honsek Caroline , Kemper Margrit , Gerbracht Christiana , Arafat Ayman M , Birkenfeld Andreas L , Schwarz Peter E H , Machann Jürgen , Osterhoff Martin A , Weickert Martin O , Pfeiffer Andreas F H 
Published: August 2022

Abstract

Objectives
Some individuals develop type 2 diabetes mellitus (T2DM) despite significant metabolic improvements through lifestyle intervention. We tested the hypotheses that insulin growth factor 1 (IGF1) and its binding proteins 1 and 2 predict the onset of T2DM in prediabetes patients and determine the capacity for metabolic regeneration.

Design
We measured fasting serum IGF1, insulin growth factor-binding protein 1 (IGFBP1) and IGFBP2 in three randomized controlled lifestyle intervention trials, covering at least 1 year of intervention period and 1 year of additional follow-up.

Methods
Within a sample of 414 high-risk prediabetes patients (58% women; 28–80 years), we analyzed fasting serum concentrations of IGF1, IGFBP1 and IGFBP2 in relation to diabetes incidence and metabolic parameters over 2 years. Three hundred and forty-five subjects finished the first year of intervention.

Results
The interventions significantly improved body weight (BMI: −3.24%, P &lt; 0.001), liver fat (−36.8%, P &lt; 0.001), insulin sensitivity (IS) (homeostatic model assessment-insulin resistance: −6.3%, P &lt; 0.001) and insulin secretion (disposition index: +35%, P &lt; 0.001) in the cohort. Fourteen percent developed T2DM within 2 years. Mean IGFBP1 levels at baseline were lower in prediabetes compared to a healthy population. Also, prediabetes patients with obesity and nonalcoholic fatty liver disease had lower IGFBP1. Those with impaired glucose tolerance had higher IGFBP1 compared to those with only impaired fasting glucose. Baseline IGF1 was lower (122.5 vs 146.6 µg/L) and IGFBP1 was higher (3.32 vs 2.09 µg/L) in subjects who developed T2DM (n = 57), resulting in a significant prediction of diabetes incidence (hazard ratio (HR) IGF1: 0.991 µg/L, P = 0.003; HR IGFBP1: 1.061 µg/L, P = 0.002). This translates into a 20% and 9% difference in T2DM incidence for IGF1 and IGFBP1, respectively. Despite reduced weight, visceral fat and hepatic fat in response to 1 year of lifestyle intervention, those who developed T2DM had not improved insulin sensitivity, glucose tolerance or IGFBP1.

Conclusions
Lower IGF1 and higher IGFBP1 in prediabetes predicted the incidence of T2DM, indicating an impairment of beta-cell function, which explains the unresponsiveness to lifestyle intervention.
Insurance and Health Care Outcomes in Regions Where Undocumented Children Are Medicaid-Eligible
Authors: Rosenberg Julia , Shabanova Veronika , McCollum Sarah , Sharifi Mona 
Published: August 2022

OBJECTIVES
Expansion of insurance eligibility is associated with positive health outcomes. We compared uninsurance and health care utilization for (1) all children, and (2) children in immigrant families (CIF) and non-CIF who resided inside and outside of the seven US states/territories offering public health insurance to children regardless of documentation status (“extended-eligibility states/territories”).

METHODS
Using the cross-sectional, nationally representative National Survey of Children’s Health-2019, we used survey-weighted, multivariable Poisson regression to assess the association of residence in nonextended- versus extended-eligibility states/territories with uninsurance and with health care utilization measures for (1) all children, and (2) CIF versus non-CIF, adjusting for demographic covariates.

RESULTS
Of the 29 433 respondents, the 4035 (weighted 27.2%) children in extended- versus nonextended-eligibility states/territories were more likely to be CIF (27.4% vs 20.5%, P &lt; .001), 12 to 17 years old (37.2% vs 33.2%, P = .048), non-White (60.1% vs 45.9%, P &lt; .001), and have a non-English primary language (20.6% vs 11.1%, P &lt; .001).
The relative risk of uninsurance for children in nonextended- versus extended-eligibility states/territories was 2.0 (95% confidence interval 1.4–3.0), after adjusting for covariates. Fewer children in extended- versus nonextended-eligibility states/territories were uninsured (adjusted prevalence 3.7% vs 7.5%, P &lt; .001), had forgone medical (2.2% vs 3.1%, P = .07) or dental care (17.1% vs 20.5%, P = .02), and had no preventive visit (14.3% vs 17.0%, P = .04). More CIF than non-CIF were uninsured, regardless of residence in nonextended- versus extended-eligibility states/territories: CIF 11.2% vs 5.7%, P &lt; .001; non-CIF 6.1% vs 3.1% P &lt; .001.

CONCLUSIONS
Residence in nonextended-eligibility states/territories, compared with in extended-eligibility states/territories, was associated with higher uninsurance and less preventive health care utilization.
Porosity estimation and pore structure characterization of foamed cement paste using non-specialized image digital processing
Authors: Chica Lina , Mera Carlos , Sepúlveda-Cano Lina María , Alzate Albert 
Published: August 2022

AbstractIn foamed concrete, porosity is essential because it is strongly related to other properties such as density, permeability, and strength. Porosity measurement (usually expressed as a percentage of total volume) is obtained in a laboratory using experimental water vacuum saturation and MIP methods. However, pore structure -including size, distribution, shape, and connection- is also needed to understand foamed concrete performance. Pore structure characterization is estimated through specialized digital image analysis. Micro CT, scanning electron microscopy or X-ray tomography images are frequently used to obtain pore structure on cellular concrete. However, these images are highly specialized and require equipment that is not easy to find and very expensive. Also, image processing is complex, and it includes some specialized software. This paper presents a pore structure characterization and porosity estimation using non-specialized digital images on foamed cement paste made with alternative agents. The procedure for acquiring images uses only a camera without any specialized equipment. The proposed methodology isolates the pores in the image and measures shape features such as pore diameter, eccentricity, and solidity. Acquiring and processing the images is simpler, faster, and cheaper than other specialized analyses. Results show that the volumetric porosity estimation was entirely accurate, with an estimation deviation of less than 10%. Also, the pore structure parameters such as pore size and distribution of foamed pastes can be quantified accurately.
Clinical Outcomes and Complications of Simultaneous or Sequential Bilateral Total Ankle Arthroplasty
Authors: Fletcher Amanda N. , Johnson Lindsey G. , Easley Mark E. , Nunley James A. , DeOrio James K. 
Published: August 2022

Background:
The risk-benefit profiles of simultaneous total ankle arthroplasty (TAA) compared with sequential TAA continue to be debated. There are limited case series reporting outcomes after bilateral TAA, with no previous comparison of simultaneous TAA with sequential TAA. Patients with bilateral pathology represent a unique population with an overall more debilitating condition. Thus, we aimed to compare bilateral simultaneous and sequential TAAs, including perioperative complications and patient-reported outcome measures.

Methods:
We performed a comparative cohort study of patients who underwent primary bilateral TAA, performed in a simultaneous or sequential fashion, from 2007 to 2019 at a single academic center. Data on patient demographic characteristics, comorbidities, perioperative complications, reoperations, and implant failures were collected. Patient-reported outcome measures included preoperative and postoperative visual analog scale (VAS) scores for pain, Short Form-36 Health Survey (SF-36) scores, and Short Musculoskeletal Function Assessment (SMFA) scores.

Results:
A total of 50 patients (100 ankles) were included, with 25 patients (50 ankles) each in the bilateral simultaneous and sequential cohorts. The mean follow-up was 52.2 ± 27.3 months (range, 24 to 109 months). The mean time between sequential TAAs was 17.5 ± 20.1 months (range, 3 to 74 months). The mean patient age was 64.3 ± 10.6 years (range, 21 to 76 years), and 32 (64.0%) were men. The majority of patients (28 patients [56.0%]) had primary osteoarthritis. Both cohorts had equivalent preoperative patient-reported outcome measures and experienced improvements in all measures, which were maintained at the final follow-up with no significant between-group differences (all p > 0.05). There were no differences between the simultaneous TAA group and the sequential TAA group in perioperative complication rates (22.0% compared with 24.0%; p = 0.7788), reoperations (12.0% compared with 10.0%; p = 0.7354), 5-year reoperation-free survival (88.0% compared with 90.0%; p = 0.4612), or failure-free survival (100%). One patient in the simultaneous TAA cohort required metal component revision at 8 years postoperatively.

Conclusions:
The patient-reported outcome measures, complications, and prosthesis survival of patients who underwent bilateral simultaneous TAA were comparable with those of patients who underwent bilateral sequential TAA. We advocate that simultaneous bilateral TAA is a safe and effective method for the treatment of bilateral end-stage ankle osteoarthritis.

Level of Evidence:
Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.
BULK CARBON ISOTOPIC VARIABILITY WITHIN LEAVES
Authors: ROYER DANA L. , HREN MICHAEL T. 
Published: August 2022

Abstract
The stable carbon isotopic composition (δ13C) of fossil leaves is a simple and common measurement that provides information about paleophysiology, paleoecology, and paleoclimate. Variance in δ13C is typically assessed across leaves; comparatively little is known about variance within leaves, a potential source of unquantified uncertainty. Here we systematically analyze the spatial patterns of bulk δ13C in fresh leaves of 10 tree species (two leaves per species; 21 or 22 analyses per leaf). We find that samples containing midvein tissue are markedly higher in δ13C than non-midvein tissue from the same leaf (median = +0.85‰), with samples containing only midvein tissue offset by as much as +3.01‰. The non-midvein samples are less variable—the typical range within a single leaf is &lt;1‰—and do not show any consistent spatial patterns. In cases where whole fossil leaves cannot be analyzed, we recommend sampling as many randomized areas without major veins as is feasible.
IRPDP_HT2: A Scalable Data Pre-processing Method in Web Usage Mining using Hadoop-MapReduce
Authors: Srivast Mitali , Srivast Atul 
Published: August 2022

Abstract
Data preparation is a vital step in the Web usage mining process since it provides structured data for the subsequent stages. Raw server logs should be turned into user sessions in order to generate structured data for pattern discovery phase. In recent decade, popular websites' server log production has risen to many terabytes to petabytes each day. As a result, server logs have Big Data challenges including storage and processing. Data cleaning, user identification, and session identification are data-intensive and deemed-computation-intensive operations in the data pre-processing sub phases. In recent years, Google's MapReduce parallel programming framework for data-intensive applications has grown in popularity as it provides the facility of scalable, flexible, fault-tolerant, distributed, and data-intensive processing over a cluster of nodes. In this paper, we provide IRPDP_HT2, a parallel data pre-processing algorithm using MapReduce that comprises data cleansing, user identification, and session identification approaches. The relevance and scalability of IRPDP_HT2 are also assessed using real web server logs, and it is discovered that the presented approach is both efficient and scalable.
Balance Sparse Decomposition Method with Nonconvex Regularization for Gearbox Fault Diagnosis
Authors: Huang Weiguo , Wang Jun , Du Guifu , Wu Shuyou , Zhu Zhongkui 
Published: August 2022

Abstract

As an important part of rotating machinery, gearboxes often fail due to their complex working conditions and harsh working environment. Therefore, it is very necessary to effectively extract the fault features of the gearboxes. Gearbox fault signals usually contain multiple characteristic components and are accompanied by strong noise interference. Traditional sparse modeling methods are based on synthesis models, and there are few studies on analysis and balance models. In this paper, a balance nonconvex regularized sparse decomposition method is proposed, which based on a balance model and an arctangent nonconvex penalty function. The sparse dictionary is constructed by using Tunable Q-Factor Wavelet Transform (TQWT) that satisfies the tight frame condition, which can achieve efficient and fast solution. It is optimized and solved by alternating direction method of multipliers (ADMM) algorithm, and the non-convex regularized sparse decomposition algorithm of synthetic and analytical models are given. Through simulation experiments, the determination methods of regularization parameters and balance parameters are given, and compared with the L1 norm regularization sparse decomposition method under the three models. Simulation analysis and engineering experimental signal analysis verify the effectiveness and superiority of the proposed method.
Leveraging Big Data Analytics for Intelligent Transportation Systems: Optimize the Internet of Vehicles Data Structure and Modeling
Authors: Gebremeskel Gebeyehu Belay 
Published: August 2022

Abstract
An intelligent transportation system is an efficient and modern system to deal with big data, which is pertinent for a future smart city. It is the inherent challenge of data processing in classic vehicular systems. Therefore, we proposed Big data to optimize location-based operability and safety performances using federated sensor data. The data preprocessing and feature extraction process includes vehicle mobility, multi-source data acquisition, distributed computation, and multi-path data transmission in an analytical model to enhance performance and safety. The proposed approach is capable and scalable to manage large-scale sensor data from its source and line of information flow. The findings revealed the imperfect, complex, and challenging data transformation into actionable, safe, and usable information for the intelligent transformation system modernization and healthy digital ecosystems. Big data analytics for sensor data is complete and informative for the learning process of the physical systems in various situations and localizations. The experiment showed that leveraging big data technology is a systematic approach to enhancing safe and optimal vehicular system applications. It provides access to shared resources through connected devices and reduces costs using the response time and data structuring to the system stability and to accommodate future modifications in sensor technology.
Timing of Intubation and ICU Mortality in COVID-19 Patients: A Preplanned Retrospective Analysis of 4198 Critically Ill Patients
Authors: Manrique Sara , Claverias Laura , Magret Mónica , Masclans Joan Ramon , Bodi María , Trefler Sandra , Canadell Laura , Diaz Emili , Sole-Violan Jordi , Bisbal-Andrés Elena , Gonzalez Ruth , Albaya Antonio , Vallverdu Monserrat , Ballesteros Juan Carlos , Socias Lorenzo , Gordo Federico , Sancho Susana , Loeches Ignacio Martín , Rodriguez Alejandro , group SEMICYUC Working 
Published: August 2022

Abstract
Background Optimal time to intubate patients with SARS-CoV-2 pneumonia is controversial. Whereas some authors recommend trying noninvasive respiratory support before intubate, others argue that delaying intubation can cause patient-self-induced lung injury and worsen the prognosis. We hypothesized that delayed intubation would increase the risk mortality in COVID-19 patients.Methods This preplanned retrospective observational study used prospectively collected data from adult patients with COVID-19 and respiratory failure admitted to 73 intensive care units between February 2020 and March 2021. Patients with limitations on life support and those with missing data were excluded. We collected demographic, laboratory, clinical variables and outcomes. Intubation was classified as 1) Very early: before or at ICU admission; 2) Early: < 24 hours after ICU admission; or 3) Late: ≥24 hours after ICU admission. We compared the early group versus those intubated late, using chi-square tests for categorical variables and the Mann-Whitney U for continuous variables. To assess the relationship between early versus late intubation and mortality, we used multivariable binary logistic regression. Statistical significance was set at p<0.05.Results We included 4198 patients [median age, 63 (54‒71) years; 70.8% male; median SOFA score, 4 (3‒7); median APACHE score, 13 (10‒18)], and median PaO2/FiO2, 131 (100‒190)]; intubation was very early in 2024 (48.2%) patients, early in 928 (22.1%), and late in 441 (10.5%). ICU mortality was 30.2% and median ICU stay was 14 (7‒28) days. Although patients in the late group were younger [62 vs. 64, respectively, p<0.05] and had less severe disease [APACHE II (13 vs. 14, respectively, p<0.05) and SOFA (3 vs. 4, respectively, p<0.05) scores], and higher PaO2/FiO2 at admission (116 vs. 100, respectively, p<0.05), mortality was higher in the late group than in the early group (36.9% vs. 31.6%, p<0.05). Late intubation was independently associated with mortality (OR1.83; 95%CI 1.35‒2.47).Conclusions Delaying intubation beyond the first 24 hours of admission in patients with COVID-19 pneumonia increases the risk of mortality.Trial registration: clinical-Trial.gov (NCT 04948242)
Does participation in the Reanima European Trauma Course lead to new behaviours and organizational change?
Authors: Neutel Elizabete , Kuhn Sebastian , Driscoll Peter , Gwinnutt Carl , Moreira Zélia , Veloso Ana , Manso Maria Conceição , Carneiro António 
Published: August 2022

Abstract
Background
Medical educational courses can be successful from an immediate feedback perspective but not lead to new behaviour or organizational changes in the workplace. The aim of this study was to assess the self-perceived impact of the Reanima European Trauma Course (R-ETC) on trainees’ behaviour and organizational change.
Methods
A 40-item questionnaire based on Holton's Evaluation Model was used to evaluate the candidate's perceptions. Results were analysed with descriptive and inferential statistical analysis using non-parametric tests with α = 0.05.
Results
Out of 295 participants, 126 responded to the survey. Of these, 94% affirmed that the R-ETC modified their approach to trauma patients and 71.4% described a change in their behaviour. Post-course responders changed their behaviour in their initial approach to trauma care in the non-technical skills of communication, prioritisation and teamwork. Being an R-ETC instructor strongly influenced the acquisition of new material and this group were able to implement changes in attitudes. Individuals with no previous trauma course experience identified lack of self-efficacy as a significant obstacle to introducing new work-based learning. In contrast, responders with ATLS training noted a lack of R-ETC colleagues as the main impediment for moving from conceptualisation to experimentation in the workplace.
Conclusions
Participation in the R-ETC led to behavioural changes in the workplace. However, the ability to influence others and bring about wider organizational changes was more difficult to achieve. Major factors were the status of the person, their experience and self-efficacy. National organizational impact was obtained which went far beyond our aspirations in acknowledging change in individual daily practice.