bluuebunny/crossref_metadata_2025_split huggingface dataset:
Roadmap on measurement technologies for next generation structural health monitoring systems
Authors: Laflamme Simon , Ubertini Filippo , Di Matteo Alberto , Pirrotta Antonina , Perry Marcus , Fu Yuguang , Li Jian , Wang Hao , Hoang Tu , Glisic Branko , Bond Leonard J , Pereira Mauricio , Shu Yening , Loh Kenneth J , Wang Yang , Ding Siqi , Wang Xinyue , Yu Xun , Han Baoguo , Goldfeld Yiska , Ryu Donghyeon , Napolitano Rebecca , Moreu Fernando , Giardina Giorgia , Milillo Pietro 
Published: April 2023

Abstract
Structural health monitoring (SHM) is the automation of the condition assessment process of an engineered system. When applied to geometrically large components or structures, such as those found in civil and aerospace infrastructure and systems, a critical challenge is in designing the sensing solution that could yield actionable information. This is a difficult task to conduct cost-effectively, because of the large surfaces under consideration and the localized nature of typical defects and damages. There have been significant research efforts in empowering conventional measurement technologies for applications to SHM in order to improve performance of the condition assessment process. Yet, the field implementation of these SHM solutions is still in its infancy, attributable to various economic and technical challenges. The objective of this Roadmap publication is to discuss modern measurement technologies that were developed for SHM purposes, along with their associated challenges and opportunities, and to provide a path to research and development efforts that could yield impactful field applications. The Roadmap is organized into four sections: distributed embedded sensing systems, distributed surface sensing systems, multifunctional materials, and remote sensing. Recognizing that many measurement technologies may overlap between sections, we define distributed sensing solutions as those that involve or imply the utilization of numbers of sensors geometrically organized within (embedded) or over (surface) the monitored component or system. Multi-functional materials are sensing solutions that combine multiple capabilities, for example those also serving structural functions. Remote sensing are solutions that are contactless, for example cell phones, drones, and satellites. It also includes the notion of remotely controlled robots.
A simple digital readout circuit for differential resistive or capacitive sensors
Authors: Hidalgo-López José Antonio 
Published: April 2023

Abstract
This paper introduces and analyzes a novel direct interface circuit (DIC) that directly connects differential resistive and capacitive sensors to digital processors (DPs), performing a magnitude-to-time-to-digital conversion of the information they provide. The simple circuit performs the readout using two passive components, the differential sensor and the DP. In some cases, the circuit may require an additional passive element. The DP only uses common digital resources such as bidirectional pins or a counter, meaning microcontrollers, FPGAs, or ASICs could all be used as DPs. Different DICs proposed in the literature for reading differential sensors require three time measurement processes to estimate the variable to be measured. The new circuit requires only one, saving time and energy dissipation and reducing the number of error sources. A design based on an FPGA has been implemented as a proof of concept. Measurement times in the order of 1.1–1.3 ms have been obtained with this configuration. Errors in the readout of a differential resistive sensor are below 0.34% in the worst case and below 0.63% for a differential capacitive sensor.
Ultrathin AlO
x
layer modified ferroelectric organic field-effect transistor for artificial synaptic characteristics
Authors: Bu Yunlong , Su Jie , Li Hangfei , Chen Dong , Xu Ting 
Published: April 2023

Abstract
The challenges associated with autonomous information processing and storage will be resolved by neuromorphic computing, which takes inspiration from neural networks in the human brain. To create suitable artificial synaptic devices for artificial intelligence, it is essential to look for approaches to improve device performance. In the present study, we suggest a method to address this problem by inserting an ultrathin AlO
X
layer at the side of ferroelectric film for the prepared ferroelectric organic effect transistor (Fe-OFET) to modify a ferroelectric polymer film with a low coercive field. The transistors parameters are greatly improved (large memory window exceeding 14 V, high on-off current ratio of 103, and hole mobility up to 10−2 cm2 V−1 s−1). Furthermore, the optimized high-performance Fe-OFET with 2 nm thickness of AlO
X
layer is found to have synaptic behaviors including postsynaptic current, short-term/long-term plasticity, spike-amplitude-dependent plasticity, spike-duration-dependent plasticity, paired-pulse facilitation, spike-rate-dependent plasticity, and spike-number-dependent plasticity. An outstanding learning accuracy of 87.5% is demonstrated by an imitated artificial neural network made up of Fe-OFET for a big image version of handwritten digits (28 × 28 pixel) from the Modified National Institute of Standards and Technology dataset. By improving synaptic transistor performance in this way, a new generation of neuromorphic computing systems is set to be developed.
Using the ear photoplethysmographic waveform as an early indicator of central hypovolemia in healthy volunteers utilizing LBNP induced hypovolemia model
Authors: Eid Anna-Maria , Elgamal Mohamed , Gonzalez-Fiol Antonio , Shelley Kirk H , Wu Hau-Tieng , Alian Aymen Awad 
Published: April 2023

AbstractObjective. To study the photoplethysmographic (PPG) waveforms of different locations (ear and finger) during lower body negative pressure (LBNP) induced hypovolemia. Then, to determine whether the PPG waveform can be used to detect hypovolemia during the early stage of LBNP.Approach. 36 healthy volunteers were recruited for progressive LBNP induced hypovolemia, with an endpoint of −60 mmHg or development of hypoperfusion symptoms, whichever comes first. Subjects tolerating the entire protocol without symptoms were designated as high tolerance (HT), while symptomatic subjects were designated as low tolerance (LT). Subjects were monitored with an electrocardiogram, continuous noninvasive blood pressure monitor, and two pulse oximetry probes, one on the ear (Xhale) and one the finger (Nellcor). Stroke volume was measured non-invasively utilizing Non-Invasive Cardiac Output Monitor (NICOM, Cheetah Medical). The waveform morphology was analyzed using novel PPG waveforms indices, including phase hemodynamic index (PHI) and amplitude hemodyamaic index and were evaluated from the ear PPG and finger PPG at different LBNP stages.Main results. The PHI, particularly the phase relationship between the second harmonic and the fundamental component of the ear PPG denoted as∇φ2,during the early stage of LBNP (−15 mmHg) in the HT and LT groups is statistically significantly different (pvalue = 0.0033) with the area under curve 0.81 (CI: 0.616–0.926). The other indices are not significantly different. The 5 fold cross validation shows that∇φ2during the early stage of LBNP (−15 mmHg) as the single index could predict the tolerance of the subject with the sensitivity, specificity, accuracy andF1 as 0.771 ± 0.192, 0.71 ± 0.107, 0.7 ± 0.1 and 0.771 ± 0.192 respectively.Significance. The ear’s PPG PHI which compares the phases of the fundamental and second harmonic has the potential to be used as an early predictor of central hypovolemia.
The effect of the barrier thickness on DC and RF performances of AlGaN/GaN HEMTs on silicon
Authors: Wang Chun , Hsu Heng-Tung , Lin Jui-Lung , Weng You-Chen , Tsao Yi-Fan , Wang Yuan , Chang Edward Yi 
Published: April 2023

Abstract
In this study, the effect of barrier thickness on the DC and RF performances of AlGaN/GaN high-electron mobility transistors (HEMTs) on silicon for millimeter wave applications is experimentally investigated. GaN HEMT devices with different barrier thicknesses were fabricated and characterized. While the device with the thinnest barrier exhibited the highest extrinsic transconductance (gm) resulting from the shortest gate-to-channel distance, such configuration suffered from the lowest unit current-gain cut-off frequency (fT) due to the increase of the total gate capacitance. Moreover, degradation in the output power was observed for devices with thinner barriers. Such degradation was related to the severe knee walkout as evidenced from drain-lag characterization.
Adaptive neural controller with predefined boundary constraints for 3D printed cable-driven soft actuators
Authors: Xia Chengkai , Xu Zhenbang , Sai Huayang , Li Hang , Wang Kai 
Published: April 2023

Abstract
It is difficult to build dynamic models for 3D-printed soft actuators because of their material and structural flexibility and the complex intrinsic and extrinsic interactions encountered in human-centric or complex non-structural environments. Soft actuators require the control error during motion to be limited. However, existing control methods with predefined boundary constraints are designed for rigid actuators and are not directly applicable to soft actuators. In this paper, an adaptive neural controller based on a quasi-static model is proposed. The quasi-static model of the soft actuator is used to determine how the viscoelasticity of the flexible material influences the neural network, enabling the neural network to identify a better fit to the dynamic model of the soft actuator. Finally, experimental results verify that the proposed controller constrains the tracking error of the soft actuator to within the predefined boundary.
Transient analysis of high-Z impurity screening by additional injection of low-Z impurity using integrated divertor code SONIC
Authors: Yamoto Shohei , Hoshino Kazuo , Homma Yuki , Nakano Tomohide , Hayashi Nobuhiko 
Published: April 2023

Abstract
The dynamics of the screening effect of Ar impurity by the injection of additional Ne has been studied through time-dependent analysis with the integrated divertor code SONIC. In the preceding study (Yamoto et al 2020 Plasma Phys. Control. Fusion 62 045006), the predictive simulation of JT-60SA plasma by SONIC has shown that the injection of additional Ne into Ar-seeded plasma results in lower Ar density and radiation power in the SOL and core edge than in the Ar-only seeded case. The results have demonstrated that the mixed impurity seeding of Ar and Ne may be advantageous for maintaining a high core plasma performance with a low divertor heat load. It was found that the friction force induced by the high D+ flow in the SOL towards the inner divertor (ID) region in the Ar + Ne seeded case pushes Ar impurities to the ID. However, the dynamics of D+ flow acceleration cannot be interpreted in the previous study because SONIC was a steady state code. In this study, we have developed the time-dependent version of SONIC and applied it to the transient analysis of the injection of additional Ne into Ar-seeded plasma in JT-60SA. When additional Ne is injected, Ne ions stay in the ID plasma near the X-point. As a result, the Ne radiation power increases near the X-point. The electron pressure then decreases due to the radiation cooling and the D+ flow is accelerated by the electron pressure gradient. The ion pressure also decreases due to the convection by the accelerated D+ flow by electron pressure gradient. The resulting ion pressure gradient further accelerates the D+ flow velocity towards the ID. The results suggest that both the high-performance core plasma and the low divertor heat load can be achieved by the Ar + Ne mixed impurity seeding.
Influence of positive ions on the beamlet optics for negative-ion neutral beam injectors
Authors: Pimazzoni A. , Sartori E. , Serianni G. , Veltri P. 
Published: April 2023

Abstract
Neutral beam injectors are based on the neutralization of ion beams accelerated at the desired energy. In the case of the ITER heating and diagnostic neutral beams, the target heating power translates into stringent requirements on the acceptable beamlet divergence and aiming to allow the beam to reach the fusion plasma. The beamlets composing the accelerated beam are experimentally found to feature a transverse velocity distribution exhibiting two Gaussian components: the well-focused one is referred to as the core component while the rest of the beam, the halo, describes beam particles with much worse optics. The codes that simulate beam extraction and acceleration usually assume that the negative ions move towards the plasma meniscus with a laminar flow (no transverse velocity) or that the transverse velocity distribution can be modelled as a Maxwellian and that the current density is uniformly illuminating the meniscus; under such approximations, the presence of highly divergent components cannot be explained. In this work, we develop a simple test-particle tracing code with Monte Carlo collisions, named ICARO (for Ions Coming Around), to study the transport of negative ions in the extraction region and derive the spatial and velocity distribution of the negative ions at the meniscus (i.e. the plasma boundary where a beamlet is extracted). In particular, the origin of the beamlet halo and its dependence on the source parameters are discussed, highlighting as a key parameter the energy distribution of positive ions in the source plasma.
Multi-scale systems genomics analysis predicts pathways, cell types, and drug targets involved in normative variation in peri-adolescent human cognition
Authors: Pai Shraddha , Hui Shirley , Weber Philipp , Narayan Soumil , Whitley Owen , Li Peipei , Labrie Viviane , Baumbach Jan , Wheeler Anne L , Bader Gary D 
Published: April 2023

Abstract
An open challenge in human genetics is to better understand the systems-level impact of genotype variation on developmental cognition. To characterize the genetic underpinnings of peri-adolescent cognition, we performed genotype–phenotype and systems analysis for binarized accuracy in nine cognitive tasks from the Philadelphia Neurodevelopmental Cohort (~2,200 individuals of European continental ancestry aged 8–21 years). We report a region of genome-wide significance within the 3′ end of the Fibulin-1 gene (P = 4.6 × 10−8), associated with accuracy in nonverbal reasoning, a heritable form of complex reasoning ability. Diffusion tensor imaging data from a subset of these participants identified a significant association of white matter fractional anisotropy with FBLN1 genotypes (P &lt; 0.025); poor performers show an increase in the C and A allele for rs77601382 and rs5765534, respectively, which is associated with increased fractional anisotropy. Integration of published human brain-specific ’omic maps, including single-cell transcriptomes of the developing human brain, shows that FBLN1 demonstrates greatest expression in the fetal brain, as a marker of intermediate progenitor cells, demonstrates negligible expression in the adolescent and adult human brain, and demonstrates increased expression in the brain in schizophrenia. Collectively these findings warrant further study of this gene and genetic locus in cognition, neurodevelopment, and disease. Separately, genotype-pathway analysis identified an enrichment of variants associated with working memory accuracy in pathways related to development and to autonomic nervous system dysfunction. Top-ranking pathway genes include those genetically associated with diseases with working memory deficits, such as schizophrenia and Parkinson’s disease. This work advances the “molecules-to-behavior” view of cognition and provides a framework for using systems-level organization of data for other biomedical domains.
Data-driven mortality risk prediction of severe degenerative mitral regurgitation patients undergoing mitral valve surgery
Authors: Kwak Soongu , Lee Seung-Ah , Lim Jaehyun , Yang Seokhun , Hwang Doyeon , Lee Hyun-Jung , Choi Hong-Mi , Hwang In-Chang , Lee Sahmin , Yoon Yeonyee E , Park Jun-Bean , Kim Hyung-Kwan , Kim Yong-Jin , Song Jong-Min , Cho Goo-Yeong , Kang Duk-Hyun , Kim Dae-Hee , Lee Seung-Pyo 
Published: April 2023

Abstract

Aims
The outcomes of mitral valve replacement/repair (MVR) in severe degenerative mitral regurgitation (MR) patients depend on various risk factors. We aimed to develop a risk prediction model for post-MVR mortality in severe degenerative MR patients using machine learning.

Methods and results
Consecutive severe degenerative MR patients undergoing MVR were analysed (n = 1521; 70% training/30% test sets). A random survival forest (RSF) model was constructed, with 3-year post-MVR all-cause mortality as the outcome. Partial dependency plots were used to define the thresholds of each risk factor. A simple scoring system (MVR-score) was developed to stratify post-MVR mortality risk. At 3 years following MVR, 90 patients (5.9%) died in the entire cohort (59 and 31 deaths in the training and test sets). The most important predictors of mortality in order of importance were age, haemoglobin, valve replacement, glomerular filtration rate, left atrial dimension, and left ventricular (LV) end-systolic diameter. The final RSF model with these six variables demonstrated high predictive performance in the test set (3-year C-index 0.880, 95% confidence interval 0.834–0.925), with mortality risk increased strongly with left atrial dimension &gt;55 mm, and LV end-systolic diameter &gt;45 mm. MVR-score demonstrated effective risk stratification and had significantly higher predictability compared to the modified Mitral Regurgitation International Database score (3-year C-index 0.803 vs. 0.750, P = 0.034).

Conclusion
A data-driven machine learning model provided accurate post-MVR mortality prediction in severe degenerative MR patients. The outcome following MVR in severe degenerative MR patients is governed by both clinical and echocardiographic factors.
Cardiovascular disease burden attributable to non-optimal temperature: analysis of the 1990–2019 global burden of disease
Authors: Al-Kindi Sadeer , Motairek Issam , Khraishah Haitham , Rajagopalan Sanjay 
Published: April 2023

Abstract

Aims
Extreme temperatures are increasingly experienced as a result of climate change. Both high and low temperatures, impacted by climate change, have been linked with cardiovascular disease (CVD). Global estimates on non-optimal temperature-related CVD are not known. The authors investigated global trends of temperature-related CVD burden over the last three decades.

Methods and results
The authors utilized the 1990–2019 global burden of disease methodology to investigate non-optimal temperature, low temperature- and high temperature-related CVD deaths, and disability-adjusted life years (DALYs) globally. Non-optimal temperatures were defined as above (high temperature) or below (low temperature) the location-specific theoretical minimum-risk exposure level or the temperature associated with the lowest mortality rates. Analyses were later stratified by sociodemographic index (SDI) and world regions. In 2019, non-optimal temperature contributed to 1 194 196 (95% uncertainty interval [UI]: 963 816–1 425 090) CVD deaths and 21 799 370 (95% UI: 17 395 761–25 947 499) DALYs. Low temperature contributed to 1 104 200 (95% UI: 897 783–1 326 965) CVD deaths and 19 768 986 (95% UI: 16 039 594–23 925 945) DALYs. High temperature contributed to 93 095 (95% UI: 10 827–158 386) CVD deaths and 2 098 989 (95% UI: 146 158–3 625 564) DALYs. Between 1990 and 2019, CVD deaths related to non-optimal temperature increased by 45% (95% UI: 32–63%), low temperature by 36% (95% UI: 25–48%), and high temperature by 600% (95% UI: −1879–2027%). Non-optimal temperature- and high temperature-related CVD deaths increased more in countries with low income than countries with high income.

Conclusion
Non-optimal temperatures are significantly associated with global CVD deaths and DALYs, underscoring the significant impact of temperature on public health.
Dynamic expression of mucins and the genes controlling mucin-type O-glycosylation within the mouse respiratory system
Authors: Tian E , Syed Zulfeqhar A , Edin Matthew L , Zeldin Darryl C , Ten Hagen Kelly G 
Published: April 2023

Abstract
The COVID-19 global pandemic has underscored the need to understand how viruses and other pathogens are able to infect and replicate within the respiratory system. Recent studies have highlighted the role of highly O-glycosylated mucins in the protection of the respiratory system as well as how mucin-type O-glycosylation may be able to modify viral infectivity. Therefore, we set out to identify the specific genes controlling mucin-type O-glycosylation throughout the mouse respiratory system as well as determine how their expression and the expression of respiratory mucins is influenced by infection or injury. Here, we show that certain mucins and members of the Galnt family are abundantly expressed in specific respiratory tissues/cells and demonstrate unique patterns of O-glycosylation across diverse respiratory tissues. Moreover, we find that the expression of certain Galnts and mucins is altered during lung infection and injury in experimental mice challenged with infectious agents, toxins, and allergens. Finally, we examine gene expression changes of Galnts and mucins in a mouse model of SARS-CoV-2 infection. Our work provides foundational knowledge regarding the specific expression of Galnt enzyme family members and mucins throughout the respiratory system, and how their expression is altered upon lung infection and injury.
Establishment of non-native Anoplophora horsfieldii (Coleoptera: Cerambycidae) in South Korea
Authors: Lee Seunghyun , Choi Junhyeong , Jang Hyunkyu , Choi Woong , Kwon Woochan , Kim Doyoon , Gim Jaedong , Park Jonghyun , Park Sangwook , Kim Sangil , Shin Seunggwan , Lee Seunghwan 
Published: April 2023

Abstract
The genus Anoplophora (Coleoptera: Cerambycidae) is among the most well-known insect genera in invasive entomology and is represented by 2 noted invasive alien species: the Asian longhorned beetle (Anoplophora glabripennis (Motschulsky, 1854)) and the Citrus longhorned beetle (Anoplophora chinensis (Forster, 1771)). In this study, a new non-native species belonging to the genus Anoplophora, Anoplophora horsfieldii (Hope, 1843), has been discovered on Jeju Island, South Korea (33°30′N, 126°30′E). Our field survey of the established area and potential habitats nearby identified numerous adult beetles and exit holes in its host, Celtis sinensis Persoon, 1805. This finding emphasizes the importance of continued monitoring and management of this new non-native species, which has the potential to cause significant ecological and economic damage.