bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adherence to healthy lifestyle behaviors as a preventable risk factor for severe hypoglycemia in people with type 2 diabetes: A longitudinal nationwide cohort study
Authors: Yun Jae‐Seung , Han Kyungdo , Park Yong‐Moon , Han Eugene , Lee Yong‐ho , Ko Seung‐Hyun 
Published: April 2022

AbstractAims/IntroductionWe investigated the associations between a combination of lifestyle factors and changes to these factors and the subsequent risk of severe hypoglycemia (SH) in type 2 diabetes patients.Materials and MethodsIndividuals with adult type 2 diabetes who underwent consecutive 2‐year interval health screening programs from 2009 to 2012 from the Korean National Health Insurance Service database were included and followed up until 2018. Information on history of smoking status, alcohol consumption and physical activity, as well as changes to these factors, was obtained. The primary outcome was incident SH.ResultsOf the 1,490,233 type 2 diabetes patients, 30,539 (2.1%) patients developed SH. Current smokers and heavy drinkers had increased risk of SH, compared with non‐smokers and non‐drinkers, respectively (hazard ratio 1.28, 95% confidence interval 1.23–1.34; hazard ratio 1.22, 95% confidence interval 1.15–1.30). However, regular physical activity was associated with reduced SH risk (hazard ratio 0.79, 95% confidence interval 0.77–0.82). A combination of unhealthy lifestyle habits was associated with increased SH risk in a dose‐dependent fashion (P for trend <0.001). Compared with participants without changes in their unhealthy lifestyles, participants who improved lifestyles had decreased risk of SH.ConclusionsGreater adherence to healthy lifestyle factors and any improvement in unhealthy lifestyle habits were associated with a substantially lower risk of SH in individuals with type 2 diabetes.
Resting energy expenditure of a diverse group of South African men and women
Authors: Pretorius Adeline , Piderit Monique , Becker Piet , Wenhold Friede 
Published: April 2022

AbstractBackgroundIn South Africa, overweight/obesity is a public health concern, disproportionally affecting Black females. A contributory role of a lower resting energy expenditure (REE) is suggested for African Americans. The present study assessed the REE of Black and White South African adults aiming to better understand the underlying predictors to overweight/obesity and transform this into locally appropriate recommendations.MethodsIn 328 (63% female; 39% Black) healthy South African adults, REE was measured with indirect calorimetry and body composition with multifrequency bioelectrical impedance analysis. The REE was estimated with 30 sets of published equations. Black–White differences in REE, as measured and adjusted (analysis of covariance), were determined with quantile regression. Reliability/agreement of estimated (against measured) REE was determined with intra‐class correlations (ICCs) and Bland–Altman analysis. A new equation was developed by median regression followed by preliminary validation.ResultsMeasured REE (adjusted for age along with fat‐free mass [FFM], FFM index, FFM plus fat mass, FFM index plus fat mass index) in White subjects was significantly higher (p < 0.001) than in Black subjects for men and women alike, regardless of obesity class. None of the sets of estimation equations had good agreement with measured REE for Black, White, male and female subjects simultaneously. A new estimation equation, based on whole‐body variables, had good reliability (ICC = 0.79) and agreement (mean difference: 27 kJ) and presents practical opportunities for groups at the local grass‐roots level.ConclusionsThe REE in Black South African adults is lower than in White adults. Tailored REE equations may improve REE estimation of racially/ethnically diverse South African groups and contribute to improved obesity management.
A feedback regulation between ARF7‐mediated auxin signaling and auxin homeostasis involving MES17 affects plant gravitropism
Authors: Zhang Feng , Li Cuiling , Qu Xingzhen , Liu Jiajia , Yu Zipeng , Wang Junxia , Zhu Jiayong , Yu Yongqiang , Ding Zhaojun 
Published: April 2022

ABSTRACTGravitropism is an essential adaptive response of land plants. Asymmetric auxin gradients across plant organs, interpreted by multiple auxin signaling components including AUXIN RESPONSE FACTOR7 (ARF7), trigger differential growth and bending response. However, how this fundamental process is strictly maintained in nature remains unclear. Here, we report that gravity stimulates the transcription of METHYL ESTERASE17 (MES17) along the lower side of the hypocotyl via ARF7‐dependent auxin signaling. The asymmetric distribution of MES17, a methyltransferase that converts auxin from its inactive form methyl indole‐3‐acetic acid ester (MeIAA) to its biologically active form free‐IAA, enhanced the gradient of active auxin across the hypocotyl, which in turn reversely amplified the asymmetric auxin responses and differential growth that shape gravitropic bending. Taken together, our findings reveal the novel role of MES17‐mediated auxin homeostasis in gravitropic responses and identify an ARF7‐triggered feedback mechanism that reinforces the asymmetric distribution of active auxin and strictly controls gravitropism in plants.
Can a constitutional monarch influence democratic preferences? Japanese emperor and the regulation of public expression
Authors: Annaka Susumu , Kato Gento 
Published: April 2022

AbstractObjectiveThis study examines whether hereditary constitutional monarchs have any influence on democratic public opinion, focusing on the case of the Japanese emperor.MethodsA survey experiment on the regulation of public expression. This issue can be framed both as left wing (i.e., the regulation of hate speech) and right wing (i.e., the regulation of publicly funded anti‐nationalistic exhibitions). Taking advantage of the dual nature of the issue, we test the effects of the emperor's endorsement on support for regulation under each ideological frame.ResultsThe (former) emperor's endorsement for freedom of expression does have a cross‐cutting effect and decreases support for regulation. This effect is relatively small but statistically significant. Additionally, the findings provide weak evidence for the emperor's own ideological position conditioning his endorsement effect.ConclusionHereditary monarchs do influence democratic public opinion, and their influence can cross‐cut ideology.
Diagnostic accuracy of Abbott Architect Assay as a screening tool for human T‐cell leukaemia virus type‐1 and type‐2 infection in a London teaching hospital with a large solid organ transplant centre
Authors: Lee Nathaniel , Murphy Jamie , Al‐Khudairi Rasheed , Sturdy Ann , Mahungu Tabitha , Haque Tanzina , Griffiths Paul , Tosswill Jennifer , Irish Dianne 
Published: April 2022

AbstractAimIn the United Kingdom, organ donors/recipients are screened for evidence of human T‐cell leukaemia virus type‐1 and type‐2 (HTLV‐1/2) infections. Since the United Kingdom is a low prevalence country for HTLV infections, a screening assay with high sensitivity and specificity is required. Samples with repeat reactivity on antibody testing are sent to a reference lab for confirmatory serological and molecular testing. In the case of donor screen, this leads to delays in the release of organs and can result in wastage. We aim to assess whether a signal/cut‐off (S/CO) ratio higher than the manufacturer's recommendation of 1.0 in the Abbott Architect antibody assay is a reliable measure of HTLV‐1/2 infection.MethodsWe conducted a 5 year retrospective analysis of 7245 patients from which 11 766 samples were tested on the Abbott Architect rHTLV I/II assay. Reactive samples (S/CO >1) were referred for confirmatory serological and molecular detection (Western Blot and proviral DNA) at UK Health Security Agency, (formerly PHE, Colindale), the national reference laboratory. Electronic, protected laboratory and hospital patient databases were employed to collate data.ResultsA total of 45 patients had initially reactive samples. 42.2% (n = 19/45) had an S/CO ratio > 20, with HTLV infection confirmed in n = 18/19 and indeterminate confirmatory results in n = 1/19. No samples with an S/CO ratio <4 (48.9%, n = 22/45) or 4–20 (8.9%, n = 4/45) had positive confirmatory results on subsequent confirmatory testing.ConclusionSamples with an S/CO >20 likely represent a true HTLV‐1/2 infection. Reactive samples with an S/CO <4 were unlikely to confirm for HTLV infections. Interpretation of these ratios can assist clinicians in the assessment of low reactive samples and reiterates the need for faster access to confirmatory testing.
The endoplasmic reticulum membrane–bending protein RETICULON facilitates chloroplast relocation movement in Marchantia polymorpha
Authors: Ishikawa Kazuya , Konno Ryota , Hirano Satoyuki , Fujii Yuta , Fujiwara Masayuki , Fukao Yoichiro , Kodama Yutaka 
Published: April 2022

SUMMARYPlant cells alter the intracellular positions of chloroplasts to ensure efficient photosynthesis, a process controlled by the blue light receptor phototropin. Chloroplasts migrate toward weak light (accumulation response) and move away from excess light (avoidance response). Chloroplasts are encircled by the endoplasmic reticulum (ER), which forms a complex network throughout the cytoplasm. To ensure rapid chloroplast relocation, the ER must alter its structure in conjunction with chloroplast relocation movement, but little is known about the underlying mechanism. Here, we searched for interactors of phototropin in the liverwort Marchantia polymorpha and identified a RETICULON (RTN) family protein; RTN proteins play central roles in ER tubule formation and ER network maintenance by stabilizing the curvature of ER membranes in eukaryotic cells. Marchantia polymorpha RTN1 (MpRTN1) is localized to ER tubules and the rims of ER sheets, which is consistent with the localization of RTNs in other plants and heterotrophs. The Mprtn1 mutant showed an increased ER tubule diameter, pointing to a role for MpRTN1 in ER membrane constriction. Furthermore, Mprtn1 showed a delayed chloroplast avoidance response but a normal chloroplast accumulation response. The live cell imaging of ER dynamics revealed that ER restructuring was impaired in Mprtn1 during the chloroplast avoidance response. These results suggest that during the chloroplast avoidance response, MpRTN1 restructures the ER network and facilitates chloroplast movement via an interaction with phototropin. Our findings provide evidence that plant cells respond to fluctuating environmental conditions by controlling the movements of multiple organelles in a synchronized manner.
Reducing the Search Space for Global Minimum: A Focused Regions Identification Method for Least Squares Parameter Estimation in Nonlinear Models
Authors: Zhang Guanglu , Allaire Douglas , Cagan Jonathan 
Published: April 2022

AbstractImportant for many science and engineering fields, meaningful nonlinear models result from fitting such models to data by estimating the value of each parameter in the model. Since parameters in nonlinear models often characterize a substance or a system (e.g., mass diffusivity), it is critical to find the optimal parameter estimators that minimize or maximize a chosen objective function. In practice, iterative local methods (e.g., Levenberg–Marquardt method) and heuristic methods (e.g., genetic algorithms) are commonly employed for least squares parameter estimation in nonlinear models. However, practitioners are not able to know whether the parameter estimators derived through these methods are the optimal parameter estimators that correspond to the global minimum of the squared error of the fit. In this paper, a focused regions identification method is introduced for least squares parameter estimation in nonlinear models. Using expected fitting accuracy and derivatives of the squared error of the fit, this method rules out the regions in parameter space where the optimal parameter estimators cannot exist. Practitioners are guaranteed to find the optimal parameter estimators through an exhaustive search in the remaining regions (i.e., focused regions). The focused regions identification method is validated through two case studies in which a model based on Newton’s law of cooling and the Michaelis–Menten model are fitted to two experimental data sets, respectively. These case studies show that the focused regions identification method can find the optimal parameter estimators and the corresponding global minimum effectively and efficiently.
The Effect of Inlet Conditions on Turbine Endwall Loss
Authors: Coull John D. , Clark Christopher J. 
Published: April 2022

Abstract
There can be significant variation and uncertainty in the flow conditions entering a blade row. This article explores how this variability can affect endwall loss in axial turbines. A computational study of three cascades with collinear inlet boundary layers is conducted. Endwall loss varies by more than a factor of 3 depending on the inlet conditions. This variation is caused by dissipation of secondary kinetic energy (SKE). The results can be understood by observing that the inlet conditions predominantly control how secondary vorticity is distributed within the blade passage. Modestly thick inlet boundary layers with high shape factor tend to displace vorticity toward the center of the passage. This displacement reduces vorticity cancellation, increasing secondary velocities, and SKE. A general method is formulated to estimate SKE in preliminary design. Optimum aspect ratio is shown to depend on the inlet boundary condition. Strategies to reduce endwall loss and minimize sensitivity to inlet conditions are then highlighted.
Finite volume effects in the McLerran–Venugopalan initial condition for the JIMWLK equation
Authors: Korcyl Piotr 
Published: April 2022

AbstractWe revisit the numerical construction of the initial condition for the dipole amplitude from the McLerran–Venugopalan model in the context of the JIMWLK evolution equation. We observe large finite volume effects induced by the Poisson equation formulated on a torus. We show that the situation can be partially cured by introducing an infrared regularization. We propose a procedure which has negligible finite volume corrections. The control of the finite volume and finite lattice spacings effects is crucial when considering the numerical solutions of the JIMWLK evolution equation with the collinear improvement.
OnSRAM: Efficient Inter-Node On-Chip Scratchpad Management in Deep Learning Accelerators
Authors: Pal Subhankar , Venkataramani Swagath , Srinivasan Viji , Gopalakrishnan Kailash 
Published: April 2022

Hardware acceleration of Artificial Intelligence (AI) workloads has gained widespread popularity with its potential to deliver unprecedented performance and efficiency. An important challenge remains in how AI accelerators are programmed to sustain high utilization without impacting end-user productivity. Prior software optimizations start with an input graph and focus on node-level optimizations,
viz.
dataflows and hierarchical tiling, and graph-level optimizations such as operation fusion. However, little effort has been devoted to inter-node on-chip scratchpad memory (SPM) management in Deep Learning (DL) accelerators, whose significance is bolstered by the recent trends in complex network topologies and the emergence of eager execution in DL frameworks.

We characterize and show that there exists up to a 5.2× performance gap in DL inference to be bridged using SPM management and propose OnSRAM, a novel SPM management framework integrated with the compiler runtime of a DL accelerator. We develop two variants, viz. OnSRAM-Static, which works on static graphs to identify data structures that can be lucratively held on-chip based on their size, liveness and significance, and OnSRAM-Eager, which targets an eager execution model (no graph) and uses a history-based speculative scheme to hold/discard data structures. We integrate OnSRAM with TensorFlow and analyze it on multiple accelerator configurations. Across a suite of 12 images, objects, and language networks, on a 3 TFLOP system with a 2 MB SPM and 32 GBps external memory bandwidth, OnSRAM-Static and OnSRAM-Eager achieve 1.02–4.8× and 1.02–3.1× reduction in inference latency (batch size of 1), over a baseline with no SPM management. In terms of energy savings, we observe average reductions of 1.51× (up to 4.1×) and 1.23× (up to 2.9×) for the static and eager execution scenarios, respectively.
Application Layer-Forward Error Correction Raptor Q Codes in 5G Mobile Networks for Factory of the Future
Authors: Ramly Athirah Mohd , Nordin Rosdiadee , Abdullah Nor Fadzilah 
Published: April 2022

The future communication requirements for industrial automation will differ significantly from existing technologies. Traffic in Industry 4.0 imposes real-time requirements, requiring ultra-reliable communication (URC) with high reliability and minimal latency. The demand for ultra-high reliability as high as 99.999999 percent and as low as 1 ms end-to-end latency is the major challenge of the NOMA communication system in the factory of the future. The high expectations on reliability and latency need modifications to the radio system’s baseband signal processing, medium access control (MAC) layer, and application layer to protect against packet losses. Thus, this paper investigates the utilization of Raptor Q codes, which is a type of Application Layer Forward Error Correction (AL-FEC), by developing an end-to-end system level simulator to evaluate and analyze the performance of the transmission signals based on cross-layer approach; from the physical layer (PHY), MAC layer, and application layer parameters in an indoor factory network setting. The factory is assumed to be operated with various factory robots of different speeds, from static to 10 km/h. The 5G technology relies heavily on flexible network operations. High user density, high user mobility, deployment, and coverage are all qualities that allow for this flexibility. Through extensive simulations, the results showed that the Raptor Q codes are not only able to give good results, i.e.,

packet

reception

rate

PRR

=
0.9

of 10 m or 1.8% to 10 m or 3.4% depending on different scenarios, but are also able to meet

PRR
=
0.9

in the mobility scenario at 10 km/h. Thus, the Raptor Q codes can be seen as a good candidate for obtaining results within a strict range of requirements set by URC communications for the factory of the future replacing RLNC.
Association of Exposure to Abuse, Nurture, and Household Organization in Childhood With 4 Cardiovascular Disease Risks Factors Among Participants in the CARDIA Study
Authors: Aguayo Liliana , Chirinos Diana A. , Heard‐Garris Nia , Wong Mandy , Davis Matthew M. , Merkin Sharon Stein , Seeman Teresa , Kershaw Kiarri N. 
Published: April 2022

Background
We investigated associations of childhood abuse with 4 cardiovascular disease risk factors in adulthood, and whether exposure to nurturing and household organization in childhood mitigated these associations.

Methods and Results
The CARDIA (Coronary Artery Risk Development in Young Adults) study (baseline examination, 1985–1986) was used to examine associations of childhood exposures (measured retrospectively at the year 15 examination) with incident obesity, type 2 diabetes, hypertension, and hyperlipidemia (assessed from baseline to year 30). Race‐ and sex‐stratified Cox proportional hazards models were used to examine associations of exposure to childhood abuse with incident cardiovascular disease risk factors. Interaction terms between exposure to abuse and exposure to nurturing relationship and household organization were included to test for effect modifications. Exposure to occasional/frequent abuse (versus no abuse) was associated with incident type 2 diabetes among White men (hazard ratio [HR], 1.81; 95% CI, 1.06–3.08). Exposure to low versus no abuse was associated with incident hyperlipidemia among White men (HR, 1.35; 95% CI, 1.09–1.67) and White women (HR, 1.26; 95% CI, 1.01–1.56). Risks of incident hyperlipidemia were higher for White women who experienced abuse and lived in dysfunctional households (HR, 3.61; 95% CI, 1.62–8.05) or households with low levels of organization (HR, 2.05; 95% CI, 1.25–3.36) compared with White women who experienced abuse but lived in well‐organized households (HR, 0.66; 95% CI, 0.41–1.06). Similar patterns were seen for Black men who lived in dysfunctional households (HR, 3.62; 95% CI, 1.29–10.12) or households with low organization (HR, 2.01; 95% CI, 1.08–3.72).

Conclusions
We identified race‐ and sex‐specific associations of childhood exposures with incident cardiovascular disease risk factors. The associations of household organization and dysfunction with cardiovascular disease risks merits further investigation.
Enabling Canonical Analysis Workflows Documented Data Harmonization on Global Air Quality Data
Authors: Schröder Sabine , Epp Eleonora , Mozaffari Amirpasha , Romberg Mathilde , Selke Niklas , Schultz Martin G. 
Published: April 2022

AbstractData harmonization and documentation of the data processing are essential prerequisites for enabling Canonical Analysis Workflows. The recently revised Terabyte-scale air quality database system, which the Tropospheric Ozone Assessment Report (TOAR) created, contains one of the world's largest collections of near-surface air quality measurements and considers FAIR data principles as an integral part. A special feature of our data service is the on-demand processing and product generation of several air quality metrics directly from the underlying database. In this paper, we show that the necessary data harmonization for establishing such online analysis services goes much deeper than the obvious issues of common data formats, variable names, and measurement units, and we explore how the generation of FAIR Digital Objects (FDO) in combination with automatically generated documentation may support Canonical Analysis Workflows for air quality and related data.
Hotspots of Monthly Land Precipitation Variations Affected by SST Anomalies
Authors: Li Xiaofan , Hu Zeng-Zhen , Gong Zhiqiang , Jha Bhaskar 
Published: April 2022

Abstract
Climate predictability at seasonal to interannual time scales is mainly associated with sea surface temperature anomalies (SSTAs). How to quantitatively assess the impact of SSTAs on climate variability and predictability is an unresolved topic. Using a novel metric [bulk connectivity (BC)], the integrated influences of global SSTAs on precipitation anomalies over land are examined in observations and compared with Atmospheric Model Intercomparison Project (AMIP) simulations in 1957–2018. The hotspots of the land precipitation variation affected by global SSTA are identified, and the seasonality is evaluated. Such hotspots indicate the regions of land precipitation predictability caused by SSTAs. The hotspots are observed in the Sahel region in September–March, in the Indochina Peninsula in April and May, and in southwestern United States in December–March, which are mostly linked to the influence of El Niño–Southern Oscillation (ENSO). The overall impact of SSTAs on land precipitation is larger in the Southern Hemisphere than in the Northern Hemisphere. The spatial variations of BC and hotspots in the observations are partially reproduced in the AMIP simulations. However, an individual run in the AMIP simulations underestimates the integrated influence of global SSTA on land precipitation anomalies, while the ensemble mean amplifies the integrated influence, and both show a challenge in capturing the seasonality of the SST influence, particularly the time of the strongest impact. The results of the BC metric can serve as a benchmark to evaluate climate models and to identify the predictability sources.