bluuebunny/crossref_metadata_2025 huggingface dataset:
Modeling language for the function-oriented development of mechatronic systems with motego
Authors: Spütz Kathrin , Jacobs Georg , Zerwas Thilo , Konrad Christian
Published: March 2023

As mechatronic products gain in popularity, methods for mastering the complexity of these systems in development become increasingly relevant, such as model-based systems engineering (MBSE). Main pillars of MBSE are method, language and tool. A method specifies procedures in product development. The application of the method is supported by a language and tool as the language specifies a system of symbols with which development artifacts can be represented in a software environment (i.e. tool). Currently, various MBSE methods exist, such as motego. Motego specifies a framework for the function-oriented seamless development of mechatronic systems from requirements to the physical realization down to mechanical and electrical contacts and the description of these via parameters and models. Central element in MBSE is the system model, which connects all relevant development artefacts. The system model is created with a language in a software environment such as Cameo Systems Modeler. In MBSE, the graphical systems modeling language SysML is widely established. The language elements in SysML are very abstract and numerous. As a result, the language is difficult to apply. However, its reasonable applicability is an essential prerequisite for the introduction of the motego methods in industrial practice. This results in the following research need: A specific modeling language for the motego method is needed that supports its reasonable application. Therefore, in this paper a modeling language is presented whose language elements are specifically adapted to the motego method. With the help of this domain specific language, the user is guided through method-compliant modeling.
Direct measurement of input loads for the wind turbine drivetrain under test on a nacelle test bench
Authors: Zhang Hongkun , Pieper Sören , Heller Marcel
Published: March 2023

Modern wind turbines have some of the highest levels of torque and non-torque loads of all industrial sectors. These high loads present a great challenge for the design of wind turbines. On a nacelle test bench, the wind turbine drivetrain can be tested and validated against the design. It is therefore important to measure the correct level of each load and all its dynamic behaviors during the test. The best way to achieve this is to measure the loads directly in front of the drivetrain. This paper presents a method of direct load measurement on the shaft adapter which connects the drivetrain to the test bench. The technical solution and some important details about the instrumentation on the adapter are also presented. Methods of signal nulling as well as signal conversion from raw signals to the loads are compared as well. The measurements obtained are then compared with the applied loads from the test bench which show good agreement. As a special case, the torque measurement is validated and calibrated up to 5 MN m by means of a state-of-the-art torque transducer.
Challenges of applying model-based predictive wind turbine control in the field
Authors: Wintermeyer-Kallen Thorben , Basler Maximilian , Konrad Thomas , Zierath János , Abel Dirk
Published: March 2023

Wind energy plays a significant role in renewable energies. The increasing demand for wind energy has caused wind turbines (WT) to grow steadily larger, which means that the control objectives are no longer solely to maximize the energy produced but to control mechanical loads, among other objectives actively. Model-based WT control, particularly model predictive control (MPC), has been the focus of research for the last decades. Nevertheless, only a few practical investigations of MPC for WTs in field tests exist.

This paper highlights some key challenges and pitfalls when applying MPC for WTs. We render these critical points based on the experience of a recently conducted field test and discuss possible solutions for these challenges. In doing so, we highlight the following three critical areas: Firstly, we show how the design and practical operation of an MPC system can take into account the nonlinear properties of the WT. In particular, we address the highly varying sensitivity to the pitch angle and the dynamic responses of the rotor speed and mechanical loads to the actuator commands over the partial and full load ranges. Secondly, we discuss the problem of having limited computational capacities on real-time platforms, restricting the possible complexity of the MPC algorithm. Lastly, we show how some safety aspects decisively influence the design and operation of the control algorithm.
Surrogate model based prediction of transmission error characteristics based on generalized topography deviations
Authors: Willecke Marius , Brimmers Jens , Brecher Christian
Published: March 2023

Simulation models of the tooth contact can provide valuable information of the gearbox operational behavior for deviated gears. It is therefore possible to gather geometry and deviation information of the two gears in contact and then estimate how they will perform in the assembled unit before even mounting them. This procedure could save time and costs used to disassemble gear boxes which fail the end of line tests because of acoustic reasons. The major challenge using sophisticated simulation models, which can describe the tooth contact is the tremendous amount of calculation time they need to produce suit-able results. In a productive gearbox manufacturing process this time is just not available. Therefore, a method to predict the operational behavior faster, than with the current used simulation models is needed. Firstly the size of the problem is downsized by introducing the sum deviation surface. It allows to reduce the number of necessary input parameters for a gear topography description to eighteen factors. With the help of that sum deviation surface, 3000 variants within a given variation space are calculated. The resulting training dataset is used to develop a deep neural network meta-model of the gear contact, which can predict the characteristics of the transmission error under load. With the help of that meta-model, the excitation of a gear pair can be predicted faster than real-time.
Traceable efficiency determination of a 2.75 MW nacelle on a test bench
Authors: Song Zihang , Weidinger Paula , Zweiffel Maximilian , Dubowik Alexander , Mester Christian , Yogal Nijan , Oliveira Rafael Soares
Published: March 2023

In this paper, the efficiency of a 2.75 MW nacelle drivetrain on a test bench was determined traceably at various load points. For this purpose, so-called transfer standards for mechanical and electrical power measurement were additionally installed and integrated into the nacelle drivetrain. As torque measurement contributes greatly to the overall uncertainty, the static torque calibration was expanded to include additional influences present under rotation. An overall system efficiency of 89% was measured in the high torque and high speed range. The relative expanded measurement uncertainty for efficiency determination was between 0.30% and 0.72% over the entire operating range. Both the efficiency and the relative expanded measurement uncertainty were calculated for each operating point.
A discussion on the characterization of grid emulators by apparent power rating and short-circuit power
Authors: Grune Rayk , Geske Martin
Published: March 2023

Wind turbines are a driving force in the change towards renewable energies today. Offshore wind turbines have reached power ratings around 15 MW, and the growth continues. Grid emulators have become inevitable for the test and validation of wind turbines and subsystems at full scale. Yet, large investments for new installations present major challenges.

Therefore, the following discussion outlines basic design aspects for the grid emulator main components: converter, transformer, and filter. The aim is to clarify the implications of requirements on the design to exhaust ratings for minimum investments, and to satisfy testing against the most recent standards and grid codes. Appropriate ratings are derived based on steady-state and transient test needs. It is shown how much overrating is specifically needed and why the converter is usually rated a multiple compared to the device under test. Further dimensioning criteria such as power quality, switching frequency, and filter size are discussed in this context.

Finally, the capacity of grid emulators is often characterized by the short-circuit power. Two essentially different variants of short-circuit power are introduced, either being dependent on the converter peak current or the passive components impedance. While the first one reveals the overload capability, the latter represents a proper measure for grid strength. However, the emulated grid strength can be adjusted in a limited bandwidth using impedance control. The concept might be confusing at first glance, but it effectively decouples the virtual short-circuit power from the ratings of the power hardware.
Prediction of progressive pulmonary fibrosis in patients with anti-synthetase syndrome-associated interstitial lung disease
Authors: Fu Hongyan , Zheng Ziyao , Zhang Zhenping , Yang Yanjuan , Cui Jieda , Wang Zhaojun , Xue Jing , Chi Shuhong , Cao Mengshu , Chen Juan
Published: March 2023

Objective

Interstitial lung disease (ILD) is a common extramuscular manifestation of the anti-synthetase syndrome (ASS). Patients with ASS-ILD are at risk in developing a progressive fibrosing phenotype despite appropriate treatments. This study investigated the risk factors and the predictive value of multiple risk factors for progressive pulmonary fibrosis (PPF) in patients with ASS-ILD.

Methods

Ninety patients with a diagnosis of ASS and evidence of ILD on high-resolution computed tomography (HRCT) were recruited. Among them, 72 participants completed follow-up for more than 12 months. These patients were further divided into a PPF-ASS group (n = 18) and a non-PPF-ASS group (n = 54). Logistic regression analysis was performed to investigate the risk factors for PPF. The predictive value of the combined risk factors for predicting PPF were analyzed by a ROC curve.

Results

The PPF-ASS group had a higher rate of positive non-Jo-1 antibodies, a significantly higher neutrophil-to-lymphocyte ratio (NLR) and serum lactate dehydrogenase (LDH), and a significantly lower PaO2/FiO2 ratio and diffusing capacity for carbon monoxide (DLCO%pred) than the non-PPF-ASS group. In addition, elevated serum Krebs von den Lungen-6 (KL-6) level and reticular opacities were significantly more common, and corticosteroid monotherapy at onset was administered more frequently in the PPF-ASS group. The median duration of follow-up was 37.4 months, survival was poorer in the PPF-ASS group, and the overall survival was 88.9%. Multivariate regression analysis further revealed that positive non-Jo-1 antibodies, NLR, and KL-6 were independent risk factors for PPF. These combined indexes had good accuracy (area under the curve = 0.874) in predicting PPF in patients with ASS-ILD.

Conclusion

Positive non-Jo-1 antibodies, NLR, and serum KL-6 are independent risk factors for PPF in patients with ASS-ILD. Monitoring these markers can potentially predict PPF in this group of patients.

Key Points

• Positive non-Jo-1 antibodies, NLR, and serum KL-6 are independent risk factors associated with PPF in patients with ASS-ILD.

• Monitoring non-Jo-1 antibodies, NLR, and serum KL-6 can potentially predict PPF in patients with ASS-ILD.
Proteomic profiling of gastric cancer with peritoneal metastasis identifies a protein signature associated with immune microenvironment and patient outcome
Authors: Chen Yanyan , Cai Guoxin , Jiang Junjie , He Chao , Chen Yiran , Ding Yongfeng , Lu Jun , Zhao Wenyi , Yang Yan , Zhang Yiqin , Wu Guanghao , Wang Haiyong , Zhou Zhan , Teng Lisong
Published: March 2023

Background

Peritoneal metastasis (PM) frequently occurs in patients with gastric cancer (GC) and is a major cause of mortality. Risk stratification for PM can optimize decision making in GC treatment.

Methods

A total of 25 GC patients (13 with synchronous, 6 with metachronous PM and 6 PM-free) were included in this study. Quantitative proteomics by high-depth tandem mass tags labeling and whole-exome sequencing were conducted in primary GC and PM samples. Proteomic signature and prognostic model were established by machine learning algorithms in PM and PM-free GC, then validated in two external cohorts. Tumor-infiltrating immune cells in GC were analyzed by CIBERSORT.

Results

Heterogeneity between paired primary and PM samples was observed at both genomic and proteomic levels. Compared to primary GC, proteome of PM samples was enriched in RNA binding and extracellular exosomes. 641 differently expressed proteins (DEPs) between primary GC of PM group and PM-free group were screened, which were enriched in extracellular exosome and cell adhesion pathways. Subsequently, a ten-protein signature was derived based on DEPs by machine learning. This signature was significantly associated with patient prognosis in internal cohort and two external proteomic datasets of diffuse and mixed type GC. Tumor-infiltrating immune cell analysis showed that the signature was associated with immune microenvironment of GC.

Conclusions

We characterized proteomic features that were informative for PM progression of GC. A protein signature associated with immune microenvironment and patient outcome was derived, and it could guide risk stratification and individualized treatment.
Lasso-based variable selection methods in text regression: the case of short texts
Authors: Freo Marzia , Luati Alessandra
Published: March 2023

Communication through websites is often characterised by short texts, made of few words, such as image captions or tweets. This paper explores the class of supervised learning methods for the analysis of short texts, as an alternative to unsupervised methods, widely employed to infer topics from structured texts. The aim is to assess the effectiveness of text data in social sciences, when they are used as explanatory variables in regression models. To this purpose, we compare different variable selection procedures when text regression models are fitted to real, short, text data. We discuss the results obtained by several variants of lasso, screening-based methods and randomisation-based models, such as sure independence screening and stability selection, in terms of number and importance of selected variables, assessed through goodness-of-fit measures, inclusion frequency and model class reliance. Latent Dirichlet allocation results are also considered as a term of comparison. Our perspective is primarily empirical and our starting point is the analysis of two real case studies, though bootstrap replications of each dataset are considered. The first case study aims at explaining price variations based on the information contained in the description of items on sale on e-commerce platforms. The second regards open questions in surveys on satisfaction ratings. The case studies are different in nature and representative of different kinds of short texts, as, in one case, a concise descriptive text is considered, whereas, in the other case, the text expresses an opinion.
Association of Behçet’s disease with the risk of metabolic syndrome and its components: a systematic review and meta-analysis
Authors: Chen Tingqiao , Shao Xinyi , Li Hao , Chen Yangmei , Liu Lin , Zhong Judan , Chen Jin
Published: March 2023

The present meta-analysis aimed to elucidate the association of Behçet’s disease (BD) with the risk of metabolic syndrome (MetS) and its components. Observational cohort studies were searched from the Embase, Web of Science, Medline, and Cochrane Library databases. The primary outcome was the association of BD with the risk of MetS and its relevant components. Effect estimates with odds ratios (ORs) were pooled using either the random-effects or fixed-effects models, according to heterogeneity. Leave-one-out sensitivity analyses were used to determine the stability of the results. Twenty-three studies, comprising 42,834 patients with BD, were included. Overall, a significant association between BD and the risk of MetS was found (pooled OR 2.26; 95% confidence interval [CI] 1.61–3.17; P < 0.0001). Among the components of MetS, significant associations were found between BD and diabetes mellitus (OR 1.21; 95% CI 1.10–1.33; P < 0.0001), BD and hypertension (OR 1.39; 95% CI 1.13–1.70; P = 0.002), and BD and dyslipidemia (OR 1.21; 95% CI 1.01–1.45; P = 0.04). Our study indicated an association between BD and the risk of MetS and some of its components (diabetes mellitus, hypertension, and dyslipidemia). Physician should consider these associations so that specific treatments are available for patients with comorbidities. Moreover, patients with BD should regularly monitor their blood pressure, fasting plasma glucose, and blood lipid levels.
About Shear Properties of Plain Weave Fabric CFRP at High Temperatures: Analytical and Experimental Approaches
Authors: Barile Claudia , Kannan Vimalathithan Paramsamy , Locasale Alessandro , Casavola Caterina
Published: March 2023

The in-plane and interlaminar characteristics of plain weave fabric Carbon Fibre Reinforced Polymer (CFRP) composites are studied. The influence of the temperature exposure, below the glass transition state of the composites, on these properties are studied. The in-plane shear properties, shear strength and shear modulus are affected by the temperature exposure. The in-plane shear strength has dropped by 44.36% for the specimens tested at 120 °C compared to the specimens tested at room temperature. The interlaminar shear strength, however, are largely unaffected by the temperature exposure. The interlaminar shear strength of the plain weave fabric CFRP largely depends on the cross-sectional area of the specimen than the temperature exposure. Finally, several prediction models are used for estimating the shear properties of the composites exposed to different temperatures. Among them, Hawileh model fits very well with the experimental data for predicting the in-plane shear strength, while Wang model fits well for the shear modulus. In addition to these, fracture surfaces of the in-plane shear and interlaminar shear specimens are characterized under optical microscopy to understand the failure modes and how they are influenced by the temperature exposures.
“No one is talking about food”: making agriculture a “business” in Ghana
Authors: Rock Joeva Sean
Published: March 2023

At the turn of the 21st century, a collection of donors created the Alliance for a Green Revolution in Africa (AGRA) to spark a “new” Green Revolution on the African continent. Since its inception, AGRA’s mission has revolved around a series of interventions designed around the idea of making agriculture a “﻿business.” In this paper, I ask how AGRA puts such discourses into practice with a particular focus in Ghana. To do so, I draw on a television show produced by AGRA called Kuapa, organizational literature, and to a lesser extent, interviews, to assess how AGRA materializes its goals in Ghana. Ultimately, I argue that a focus on discourse not only provides insight into how AGRA conceptualizes agricultural transformation, but also how AGRA pursues agronomic, political, and social changes in the countries in which it intervenes.
Examining the relationship between blockchain capabilities and organizational performance in the Indian banking sector
Authors: Garg Poonam , Gupta Bhumika , Kapil Kanwal Nayan , Sivarajah Uthayasankar , Gupta Shivam
Published: March 2023

Blockchain has enormous capabilities to transform the traditional business models in countless ways. Banks in India are building collaborative blockchain ecosystems to create an innovative business model and disrupt the traditional one to create further competitive advantages. The purpose of this study is to examine the relationship between blockchain capabilities (BCC), competitive advantages (CA) and organizational performance (OP). Further, to evaluate the mediating role of CA on the relationship between BCC and OP. In this context, scientific research model consisting of a hypothesis has been developed from the existing literature. The proposed model was tested using statistical data collected from Blockchain specialists, blockchain product marketing managers, experts of future and emergent technology and VP/AVP/Chief Manager/Branch head of banks/ financial Analyst/divisional Managers who are involved in planning and deployment of practical blockchain in banking/financial sector. Data was analyzed and tested through AMOS 22.0 and process macro using a sample of 289 responses. Our empirical result indicated that there is a significant positive relationship between BCC, CA and OP. Furthermore, relationship of BCC and OP partially mediated CA. This paper presents originality and contributes towards the body of knowledge on this subject to understand the relationship and mediation role of CA on the relationship between BCC and OP in Indian banking sector.
Removal of wood dyes from aqueous solutions by sorption on untreated pine (Pinus radiata) sawdust
Authors: Pimentel Catarina H. , Freire M. Sonia , Gómez-Díaz Diego , González-Álvarez Julia
Published: March 2023

In this work, the possibility of using un-treated pine (Pinus radiata) sawdust as biosorbent for the removal of three wood dyes (blue, red and black) from aqueous solutions was investigated. The BET surface area of the material was 1.55 ± 0.81 m2 g−1 using N2 at − 196 °C and 17.83 ± 0.032 m2 g−1 using CO2 at 0 °C. The point of zero charge was 4.8. In addition, the material was characterized before and after adsorption by surface analytical techniques. Assays were performed to analize the stability of wood dyes with time and pH and also to estimate the pKa values. Batch adsorption experiments were performed and the influence of experimental parameters such as contact time (up to equilibrium), stirring rate (100 and 210 rpm), adsorbent dose (2–10 g L−1), pH (2–9) and initial dye concentration (5 and 300 mg L−1) were studied. The optimum conditions were pH 2 and adsorbent dose of 6 g L−1 and the highest adsorption percentages achieved at 5 mg L−1 were: 100.0% for the blue, 99.7% for the black and 92.4% for the red. For 300 mg L−1 adsorption efficiency decreased to 85.6, 57.0 and 63.8% for the blue, black and red ones, respectively. Kinetic data were best fitted to the pseudo-second order model, suggesting a chemisorption process. Freundlich and Dubidin-Radushkevich were the best isotherm models. Regeneration study showed that un-treated pine sawdust could be reused efficiently for red dye removal at least in up to four repeated adsorption–desorption cycles using NaOH as desorption agent.
Urinary BLACAT1 as a non-invasive biomarker for bladder cancer
Authors: El Sharkawi Fathia Z. , El Sabah Mahmoud , Atya Hanaa B. , Khaled Hussein M.
Published: March 2023

Background

Bladder cancer (BC) is recorded as the fifth most common cancer worldwide with high morbidity and mortality. The most urgent problem in BCs is the high recurrence rate as two-thirds of non-muscle-invasive bladder cancer (NMIBC) will develop into muscle-invasive bladder cancer (MIBC), which retains a feature of rapid progress and metastasis. In addition, only a limited number of biomarkers are available for diagnosing BC compared to other cancers. Hence, finding sensitive and specific biomarkers for predicting the diagnosis and prognosis of patients with BC is critically needed. Therefore, this study aimed to determine the expression and clinical significance of urinary lncRNA BLACAT1 as a non-invasively diagnostic and prognostic biomarker to detect and differentiate BCs stages.

Methods and results

The expression levels of urinary BLACAT1 were detected by qRT-PCR assay in seventy (70) BC patients with different TNM grades (T0-T3) and twelve (12) healthy subjects as control. BLACAT1 was downregulated in superficial stages (T0 = 0.09 ± 0.02 and T1 = 0.5 ± 0.1) compared to healthy control. Furthermore, in the invasive stages, its levels started to elevate in the T2 stage (1.2 ± 0. 2), and higher levels were detected in the T3 stage with a mean value of (5.2 ± 0.6). This elevation was positively correlated with disease progression. Therefore, BLACAT1 can differentiate between metastatic and non-metastatic stages of BCs. Furthermore, its predictive values are not like to be influenced by schistosomal infection.

Conclusions

Upregulation of BLACAT1 in invasive stages predicted an unfavorable prognosis for patients with BCs, as it contributes to the migration and metastasis of BCs. Therefore, we can conclude that urinary BLACAT1 may be considered a non-invasive promising metastatic biomarker for BCs.
Heart disease risk prediction using deep learning techniques with feature augmentation
Authors: García-Ordás María Teresa , Bayón-Gutiérrez Martín , Benavides Carmen , Aveleira-Mata Jose , Benítez-Andrades José Alberto
Published: March 2023

Cardiovascular diseases state as one of the greatest risks of death for the general population. Late detection in heart diseases highly conditions the chances of survival for patients. Age, sex, cholesterol level, sugar level, heart rate, among other factors, are known to have an influence on life-threatening heart problems, but, due to the high amount of variables, it is often difficult for an expert to evaluate each patient taking this information into account. In this manuscript, the authors propose using deep learning methods, combined with feature augmentation techniques for evaluating whether patients are at risk of suffering cardiovascular disease. The results of the proposed methods outperform other state of the art methods by 4.4%, leading to a precision of a 90%, which presents a significant improvement, even more so when it comes to an affliction that affects a large population.
Clinical and financial impact of sleep disordered breathing on heart failure admissions
Authors: Khayat Rami N. , Porter Kyle , Germany Robin E. , McKane Scott W. , Healy William , Randerath Winfried
Published: March 2023

Background

The impact of sleep disordered breathing (SDB) on heart failure (HF) is increasingly recognized. However, limited data exist in support of quantification of the clinical and financial impact of SDB on HF hospitalizations.

Methods

A sleep-heart registry included all patients who underwent inpatient sleep testing during hospitalization for HF at a single cardiac center. Readmission data and actual costs of readmissions were obtained from the institutional honest broker. Patients were classified based on the inpatient sleep study as having no SDB, obstructive sleep apnea (OSA), or central sleep apnea (CSA). Cumulative cardiac readmission rates and costs through 3 and 6 months post-discharge were calculated. Unadjusted and adjusted (age, sex, body mass index, and left ventricular ejection fraction) modeling of cost was performed.

Results

The cohort consisted of 1547 patients, 393 (25%) had no SDB, 438 (28%) had CSA, and 716 (46%) had OSA. Within 6 months of discharge, 195 CSA patients (45%), 264 OSA patients (37%), and 109 no SDB patients (28%) required cardiovascular readmissions. Similarly, 3- and 6-month mortality rates were higher in both SDB groups than those with no SDB. Both unadjusted and adjusted readmission costs were higher in the OSA and CSA groups compared to no SDB group at 3 and 6 months post-discharge with the CSA and OSA group costs nearly double (~ $16,000) the no SDB group (~ $9000) through 6 months.

Interpretation

Previously undiagnosed OSA and CSA are common in patients hospitalized with HF and are associated with increased readmissions rate and mortality.
Association between cardiovascular health metrics and retinal ageing
Authors: Chen Ruiye , Xu Jinyi , Shang Xianwen , Bulloch Gabriella , He Mingguang , Wang Wei , Zhu Zhuoting
Published: March 2023

The study aims to investigate associations between cardiovascular health (CVH) metrics and retinal ageing indexed by retinal age gap. A total of 26,354 participants from the UK Biobank study with available CVH metrics and qualified retinal imaging were included in the present analysis. CVH included 7 metrics (smoking, physical activity, diet, body mass index [BMI], total cholesterol, blood pressure [BP], blood glucose). These were summarized to classify the overall CVH as poor (0–7), intermediate (8–10) or ideal (11–14). Retinal age gap was defined as the difference between biological age predicted by fundus images and chronological age. Accelerated and non-accelerated retinal ageing was defined if retinal age gap was in the upper or lower 50% quantiles of the study population, respectively. Linear and logistic regression models estimated the association of overall CVH and each metric of CVH with retinal age gap respectively. Our results showed that in the fully adjusted model, each one-unit score increase in overall CVH was negatively associated with retinal age gap (odds ratio [OR] = 0.89, 95% confidence interval [CI]: 0.87-0.92, P < 0.001). Compared with poor overall CVH, people with intermediate and ideal overall CVH had significantly lower retinal age gap (OR = 0.76, 95%CI: 0.67–0.85, P < 0.001; OR = 0.58, 95%CI: 0.50–0.67, P < 0.001). Similar associations were found between overall CVH and accelerated retinal ageing. CVH metrics including smoking, BMI, BP, and blood glucose were also significantly associated with higher retinal age gap. Taken together, we found a significant and inverse dose-response association between CVH metrics and retinal age gap, indicating that maintaining healthy metrics especially smoking, BMI, BP, and blood glucose may be crucial to slow down biological ageing.
Ireland DXA-FRAX may differ significantly and substantially to Web-FRAX
Authors: Yang Lan , Dempsey Mary , Brennan Attracta , Whelan Bryan , Erjiang E. , Wang Tingyan , Egan Rebecca , Gorham Kelly , Heaney Fiona , Armstrong Catherine , Ibarrola Guadalupe Morote , Gsel Amina , Yu Ming , Carey John J. ,   the DXA MAP Group
Published: March 2023

Summary

Appropriate use of FRAX reduces the number of people requiring DXA scans, while contemporaneously determining those most at risk. We compared the results of FRAX with and without inclusion of BMD. It suggests clinicians to carefully consider the importance of BMD inclusion in fracture risk estimation or interpretation in individual patients.

Purpose

FRAX is a widely accepted tool to estimate the 10-year risk of hip and major osteoporotic fracture in adults. Prior calibration studies suggest this works similarly with or without the inclusion of bone mineral density (BMD). The purpose of the study is to compare within-subject differences between FRAX estimations derived using DXA and Web software with and without the inclusion of BMD.

Method

A convenience cohort was used for this cross-sectional study, consisting of 1254 men and women aged between 40 and 90 years who had a DXA scan and complete validated data available for analysis. FRAX 10-year estimations for hip and major osteoporotic fracture were calculated using DXA software (DXA-FRAX) and the Web tool (Web-FRAX), with and without BMD. Agreements between estimates within each individual subject were examined using Bland–Altman plots. We performed exploratory analyses of the characteristics of those with very discordant results.

Results

Overall median DXA-FRAX and Web-FRAX 10-year hip and major osteoporotic fracture risk estimations which include BMD are very similar: 2.9% vs. 2.8% and 11.0% vs. 11% respectively. However, both are significantly lower than those obtained without BMD: 4.9% and 14% respectively, P < 0.001. Within-subject differences between hip fracture estimates with and without BMD were < 3% in 57% of cases, between 3 and 6% in 19% of cases, and > 6% in 24% of cases, while for major osteoporotic fractures such differences are < 10% in 82% of cases, between 10 and 20% in 15% of cases, and > 20% in 3% of cases.

Conclusions

Although there is excellent agreement between the Web-FRAX and DXA-FRAX tools when BMD is incorporated, sometimes there are very large differences for individuals between results obtained with and without BMD. Clinicians should carefully consider the importance of BMD inclusion in FRAX estimations when assessing individual patients.
Stagnating blood flow related to thrombus formation in pulmonary vein stump after left upper lobectomy
Authors: Nakano Takahito , Kaneda Hiroyuki , Murakawa Tomohiro
Published: March 2023

Objectives

A thrombus can occur in the stump of the pulmonary vein after left upper lobectomy, potentially causing postoperative cerebral infarction. This study aimed to verify the hypothesis that stagnation of blood flow inside the pulmonary vein stump causes thrombus formation.

Methods

The three-dimensional geometry of the pulmonary vein stump after left upper lobectomy was recreated using contrast-enhanced computed tomography. Blood flow velocity and wall shear stress (WSS) inside the pulmonary vein stump were analysed using the computational fluid dynamics (CFD) method and compared between the two groups (those with or without thrombus).

Results

The volumes of average flow velocity per heartbeat < 10 mm/s, 3 mm/s, 1 mm/s (p-values 0.0096, 0.0016, 0.0014, respectively) and the volumes where flow velocity was always below the three cut-off values (p-values 0.019, 0.015, 0.017, respectively) were significantly larger in patients with a thrombus than in those without thrombus. The areas of average WSS per heartbeat < 0.1 Pa, 0.03 Pa, 0.01 Pa (p-values 0.0002, < 0.0001, 0.0002, respectively), and the areas where WSS was always below the three cut-off values (p-values 0.0088, 0.0041, 0.0014, respectively) were significantly larger in patients with thrombus than in those without thrombus.

Conclusions

The area of blood flow stagnation in the stump calculated by CFD method was significantly larger in patients with than in those without thrombus. This result elucidates that stagnation of blood flow promotes thrombus formation in the pulmonary vein stump in patients who undergo left upper lobectomy.
Environmental Factors Affecting Training Transfer Among the Instructors
Authors: Bhurtel Anup , Bhattarai Prakash C.
Published: March 2023

This study explores the environmental factors that affect the transfer of training among technical education instructors in Nepal. In the exploration, a scale with 40 items was constructed by utilizing Delphi technique. Then, a survey was carried out on 251 instructors who completed instructional skills-related training. The result of Exploratory Factor Analysis (EFA) retained 26 items and showed six factors affecting the perceived transfer of training accounting for 58.8% of the total variance explained which are: (i) organizational transfer intervention, (ii) external monitoring and evaluation (M&E), (iii) local school governance, (iv) management support, (v) social support and, (vi) curriculum standard. Further using Confirmatory Factor Analysis (CFA), the study confirmed the model-fit of three constructs that affect training transfer: organizational transfer intervention, external M&E, and social support. The study concluded that the training transfer is affected by internal and external environmental factors, which are represented by two major driving forces of support and control.
Hydrothermal alteration of surficial rocks at Los Humeros geothermal field, Mexico: a magnetic susceptibility approach
Authors: Pandarinath Kailasa , Rivas-Hernández Jessica Liliana , Arriaga-Fuentes José Alberto , Yáñez-Dávila David , González-Partida Eduardo , Santoyo E.
Published: March 2023

Utility of the geothermal surface manifestations (GSMs; thermal springs, geysers, fumaroles, and zones of hydrothermal alteration) in the studies related to the geothermal exploration is widely recognized. The identification of hydrothermally altered rocks and zones of alteration is very important because their presence indicates the type and size of the geothermal reservoir and existing thermal conditions. The use of traditional methods (i.e., geochemistry, mineralogy, and petrography) requires expensive equipment, time-consuming, and laborious sample preparation methods. Some of the rock magnetic parameters, like magnetic susceptibility (χlf) and percentage of frequency-dependent magnetic susceptibility (χfd%), are potential to become effective additional tools in identification of the hydrothermal rocks during the initial stages of geothermal exploration. Three chemical methods, Chemical Index of Alteration (CIA), loss-on-ignition (LOI), and the binary plot (CaO + Na2O + K2O) vs. (Fe2O3 + MnO + MgO), along with two rock magnetic methods, χlf and the binary plot (χlf vs. χfd%), are applied to nine intensively altered andesite reference rocks. All the five methods have correctly identified that 99 out of the total 350 studied rocks are altered. More altered rocks are distributed surrounding the several faults in the study area. Various faults (e.g., Los Humeros fault and the Loma Blanca fault) favor fluid flow and present strong hydrothermal alteration at the surface. However, there are no altered rocks on the surface region between the E-W trending Las Papas and Las Viboras faults. The presence of only the deeper fluid pathway toward the east in the surroundings of these two faults result into the almost absence of hydrothermal alteration along their strike at the surface. Consequently, there are not many altered rocks observed surroundings these two faults at the surface. These features suggest that the surface hydrothermal alteration at Los Humeros Geothermal Field (LHGF) is controlled by faults. χlf and χfd% are reliable, simple to measure, fast, cost-effective, and have the potential to become reliable additional tools for future exploration studies.
Using machine learning with case studies to identify practices that reduce greenhouse gas emissions across Australian grain production regions
Authors: Meier Elizabeth , Thorburn Peter , Biggs Jody , Palmer Jeda , Dumbrell Nikki , Kragt Marit
Published: March 2023

It is difficult to identify farm management practices that consistently provide greenhouse gas (GHG) abatement at different locations because effectiveness of practices is greatly influenced by climates and soils. We address this knowledge gap by identifying practices that provide abatement in eight case studies located across diverse conditions in Australian’s grain-producing areas. The case studies focus on soil-based emissions of nitrous oxide (N2O) and changes in soil organic carbon (SOC), simulated over 100 years for 15 cropping management scenarios. Average changes in the balance of GHG from both N2O emissions and SOC sequestration (∆GHG balance) and gross margins compared to a high emissions baseline were determined over 25 and 100 simulated years. Because scenarios providing the greatest abatement varied across individual case studies, we aggregated the data over all case studies and analysed them with a random forest data mining approach to build models for predicting ∆GHG balance. Increased cropping intensity, achieved by including cover crops, additional grains crops, or crops with larger biomass in the rotation, was the leading predictor of ∆GHG balance across the scenarios and sites. Abatement from increased cropping intensity averaged 774 CO2-e ha−1 year−1 (25 years) and 444 kg CO2-e ha−1 year−1 (100 years) compared to the baseline, with reduced emissions from SOC sequestration offsetting increased N2O emissions for both time frames. Increased cropping intensity decreased average gross margins, indicating that a carbon price would likely be needed to maximise GHG abatement from this management. To our knowledge, this is the first time that the random forest approach has been applied to assess management practice effectiveness for achieving GHG abatement over diverse environments. Doing so provided us with more general information about practices that provide GHG abatement than would have come from qualitative comparison of the variable results from the case studies.
Industrial policy matters: the co-evolution of economic structure, trade, and FDI in Brazil and Mexico, 2000–2015
Authors: Pineli André , Narula Rajneesh
Published: March 2023

The early work by Kuznets and Chenery originally developed the theme that economic development was not simply a synonym for aggregate GDP growth, but entailed qualitative changes in the structures of production, employment, and consumption. Later work in international business and economics explored the co-evolution between FDI and economic structure. We investigate the co-evolution between FDI, economic structure and export structures in the two largest Latin American economies, Brazil and Mexico, over the period 2000–2015. Both initially followed similar development strategies during the import-substitution era. During the liberalization era they followed somewhat different strategies towards maintaining the competitiveness of domestic actors. In addition to the analysis of key indicators, we discuss the role played by industrial policies—or their absence—within Brazil’s and Mexico’s development strategies. Industrial policy instruments, such as infant industry protection, subsidies, tax and financial incentives, as well as performance requirements may be crucial to shift the economic structure in the direction of the desired industries. Tracing the co-evolution between FDI and economic structures, even in the absence of statistical rigour to support causal claims, provides interesting insights for industrial policy in the twenty-first century.
Presence of boulders associated with an extreme wave event in the western Mediterranean (Cape Cope, Murcia, Spain): possible evidence of a tsunami
Authors: Lario Javier , Spencer Chris , Bardají Teresa
Published: March 2023

The region of Murcia, in the southeast of the Iberian Peninsula, experiences moderate tectonic activity, with earthquakes of up to 6.2–6.9 Mw recorded. Even with seismic activity of this scale there is no geological or instrumental record of tsunamis affecting the area. The presence at Cape Cope, Murcia of a ridge of metre-sized imbricated boulders (comprised of Upper Pleistocene sediments) reaching a height of up to 4 m above sea level, indicates that there has been an extreme wave event in the area during the Holocene. Through studying the wave conditions generated during large storms in this area, the boulder ridges appear to have been caused by extreme waves associated with a seismic event, as a tsunami.
Epigenetic regulation of plant immunity: from chromatin codes to plant disease resistance
Authors: Xie Si-Si , Duan Cheng-Guo
Published: March 2023

Facing a deteriorating natural environment and an increasing serious food crisis, bioengineering-based breeding is increasing in importance. To defend against pathogen infection, plants have evolved multiple defense mechanisms, including pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) and effector-triggered immunity (ETI). A complex regulatory network acts downstream of these PTI and ETI pathways, including hormone signal transduction and transcriptional reprogramming. In recent years, increasing lines of evidence show that epigenetic factors act, as key regulators involved in the transcriptional reprogramming, to modulate plant immune responses. Here, we summarize current progress on the regulatory mechanism of DNA methylation and histone modifications in plant defense responses. In addition, we also discuss the application of epigenetic mechanism-based resistance strategies in plant disease breeding.
Early Life Programming of Vascular Aging and Cardiometabolic Events: The McDonald Lecture 2022
Authors: Nilsson Peter M.
Published: March 2023

The early life programming of adult health and disease (Developmental Origins of Adult Health and Disease; DOHaD) concept has attracted increased attention during recent years. In this review evidence is presented for epidemiological associations between early life factors (birth weight, prematurity) and cardiometabolic traits and risk of disease in adult life. Even if not all studies concur, the evidence in general is supporting such links. This could be due to either nature or nurture. There is evidence to state that genetic markers influencing birth weight could also be of importance for offspring hypertension or risk of coronary heart disease, this supporting the nature argument. On the other hand, several studies, both historical and experimental, have found that the change of maternal dietary intake or famine in pregnancy may cause permanent changes in offspring body composition as well as in hemodynamic regulation. Taken together, this also supports the strategy of preventive maternal and child health care, starting already during the preconception period, for lowering the risk of adult cardiometabolic disease in the affected offspring. Further studies are needed to better understand the mediating mechanisms, for example concerning arterial function, hemodynamic regulation, renal function, and neuroendocrine influences, related to the development of early vascular aging (EVA) and cardiovascular disease manifestations.
FSL: federated sequential learning-based cyberattack detection for Industrial Internet of Things
Authors: Li Fangyu , Lin Junnuo , Han Honggui
Published: March 2023

Industrial Internet of Things (IIoT) brings revolutionary technical supports to modern industries. However, today’s IIoT still faces the challenges of modeling varying time-series in common data isolation while considering data security. To accurately characterize industrial dynamics, we propose a possible solution based on federated sequence learning (FSL) with cyber attack detection capabilities. Under a federated framework, FSL constructs a collaborative global model without violating local data integrity. Taking advantages of the locally sequential modeling, FSL captures the intrinsic industrial time-series responses. Furthermore, data heterogeneity among distributed clients is also considered, which is important to maintenance a robust but sensitive attack detection. Experiments on classic distributed datasets demonstrate that FSL is capable to accurately model data heterogeneity caused by data isolation and dynamics of time-series. Real IIoT attack detection experiments using a distributed testbed show that our FSL provides better detection performances for industrial time-series sensory data compared to existing methods. Therefore, the proposed attack detection approach FSL is promising in real IIoT scenarios in terms of feasibility, robustness and accuracy.
Marriage of Convenience
Authors: Birn Anne-Emanuelle
Published: March 2023

Offers a nuanced analysis of the interaction between the Rockefeller Foundation's International Health Division and Mexico's Departamento de Salubridad Pública as they jointly promoted public health through campaigns against yellow fever and hookworm disease, organized cooperative rural health units, and educated public health professionals in North American universities and Mexican training stations.
Restoration Scotland, 1660-1690
Authors: Jackson Clare
Published: March 2023

The first modern account of the advancement of political and religious ideas in Scotland in the years between the Restoration of Charles II and the collapse of royal authority under James VII and II.