bluuebunny/crossref_metadata_2025 huggingface dataset:
On the variation of apparent weight with altitude above a planet with an atmosphere
Authors: Emslie A Gordon , Oliver Travis P
Published: August 2022

We study the variation of the apparent weight of an object with height above the surface of a planet with a (buoyant) atmosphere. Interestingly, this variation depends on two competing factors—the reduced gravitational acceleration (which acts to reduce the weight with increasing height) and the reduced buoyancy force in the progressively less dense atmosphere (which acts to increase the apparent weight of an object relative to its value at the planetary surface). The relative sizes of these two competing effects are evaluated for various bodies in the Solar System. For most planets, and the one pertinent moon (Titan), the effects are quite comparable in magnitude. However, the relatively tenuous atmosphere of Mars renders the reduced buoyancy effect negligible; the apparent weight of an object thus (as generally assumed) does decrease with height. At the other extreme, the very dense atmosphere of Venus makes the reduced buoyancy effect an order of magnitude more important than the effect of reduced gravitational acceleration, so that the apparent weight of an object increases with height in the Venusian atmosphere. In addition to deriving these intrinsic results (which are admittedly somewhat esoteric in nature), studying this problem presents students at the high-school or introductory undergraduate levels with an opportunity not only to develop a deeper appreciation of the underlying physics, but also to more fully appreciate the considerable power of parametric dimensional analyses in quickly and straightforwardly obtaining (here within a factor of two) a reasonably accurate solution to a problem. The degree to which that approximate solution is sufficiently interesting (and for this particular problem it turns out that the ‘sufficiently interesting’ threshold is indeed met) then informs whether or not a more rigorous mathematical approach is justified.
A 50 dB high-gain operational amplifier integrated with metal-oxide TFTs
Authors: Chen Jun-Rong , Xu Wen-Xing , Zuo Wen-Cai , Mei Xiang-Lin , Zhou Lei , Xu Miao , Wang Lei , Wu Wei-Jing , Liu Yu-Rong , Peng Jun-Biao
Published: August 2022

This paper presents a 50 dB high-gain operational amplifier (OPAMP), which is fabricated by unipolar n-type indium–zinc–oxide thin-film transistors. Different positive feedback technologies are employed to achieve sufficient voltage gain. The fabricated OPAMP exhibits an open-loop voltage gain (A
v) of 50 dB over a −3 dB bandwidth of 15 kHz at the supply voltage of 20 V. The measured unity-gain frequency (f
UG) and the DC power consumption are 500 kHz and 8.07 mW, respectively. In addition, an effective frequency compensation scheme is also introduced and simulated. The simulation results that the proposed OPAMP has a voltage gain of 50 dB with 60° phase margin at 150 kHz unity-gain frequency after compensation.
Dynamic modeling of a fish tail actuated by IPMC actuator based on the absolute nodal coordinate formulation
Authors: Li Liang , Guo Xian , Liu Ye , Zhang Dingguo , Liao Wei-Hsin
Published: August 2022

Ionic polymer metal composite (IPMC) is a smart material with low driving voltage, high energy conversion, light weight and simple structure. It is suitable for driving the tail fin of small bionic fish. Actuators made of this material are quite flexible, and they are laborious to accurately describe the complex deformation of structures. Absolute nodal coordinate formulation (ANCF) has great merits in describing large deformation and large displacement problems. In this paper, the feasibility of ANCF in dynamic modeling of a fish tail actuated by IPMC actuator will be explored for the first time. The tail fin is simplified into two forms: a pure flexible IPMC beam and a hybrid beam that consists of an IPMC beam and a fixed rigid beam. The ANCF one-dimensional two-node beam element is adopted. Considering the influence of deformation curvature, the exact expression of generalized elastic force is obtained. The proposed dynamic model can describe the large deformation problem of the flexible beam. The dynamic responses of the pure IPMC beam tail fin and the hybrid tail fin driven by square wave voltage are calculated. The displacement changes of end nodes are compared, and the swing law under different driving voltage amplitude, frequency, and fluid resistance is analyzed. It is found that the driving efficiency of IPMC can be improved by increasing the driving voltage amplitude, reducing the voltage frequency, and reducing the fluid resistance in a certain range. This research would be beneficial to the study of the large swing motion mechanism of bionic robotic fish.
Bias-modulated switching in Chern insulator
Authors: Huang Yu , Sun Huimin , He Mengyun , Fu Yu , Zhang Peng , Wang Kang L , He Qing Lin
Published: August 2022

The Chern insulator manifests itself via the surface quantized Hall current and magnetoelectric effect. The manipulation of surface magnetizations enables a control of the dissipationless chiral transport and thus allows for potential applications of topological magnetoelectric devices with low-energy consumption. Here, we present experimental studies of bias-modulated switching the magnetic states utilizing the magnetoelectric coupling in a Chern insulator. This is achieved via applying a d.c. bias across the source and drain at various magnetic states, during which an effective magnetic field is developed to switch the quantum anomalous Hall state towards its opposite. Comprehensive transport studies show that the switch efficiency is proportional to the amplitude and applying time of the bias, depends on the initial magnetic state, but is insensitive to the electric polarity. Our results provide an efficient scheme to manipulate the Chern insulator and understanding on the electric breakdown of chiral edge states.
Master equation approach for transport through Majorana zero modes
Authors: Jin Jinshuang , Li Xin-Qi
Published: August 2022

Based on an exact formulation, we present a master equation approach to transport through Majorana zero modes (MZMs). Within the master equation treatment, the occupation dynamics of the regular fermion associated with the MZMs holds a quite different picture from the Bogoliubov–de Gennes (BdG) S-matrix scattering process, in which the ‘positive’ and ‘negative’ energy states are employed, while the master equation treatment does not involve them at all. Via careful analysis for the structure of the rates and the rate processes governed by the master equation, we reveal the intrinsic connection between both approaches. This connection enables us to better understand the confusing issue of teleportation when the Majorana coupling vanishes. We illustrate the behaviors of transient rates, occupation dynamics and currents. Through the bias voltage dependence, we also show the Markovian condition for the rates, which can extremely simplify the applications in practice. As future perspective, the master equation approach developed in this work can be applied to study important time-dependent phenomena such as photon-assisted tunneling through the MZMs and modulation effect of the Majorana coupling energy.
Transcranial ultrasound stimulation relieves depression in mice with chronic restraint stress
Authors: Zhu Yiyue , He Jiaru , Wu Canwen , Wu Junwei , Cheng Zhongwen , Chen Yan , Yuan Maodan , Zeng Lvming , Ji Xuanrong
Published: August 2022

Objective. Exhaustion of Serotonin (5-hydroxytryptamine, 5-HT) is a typical cause of the depression disorder’s development and progression, including depression-like behaviors. Transcranial ultrasound stimulation (TUS) is an emerging non-invasive neuromodulation technique treating various neurodegenerative diseases. This study aims to investigate whether TUS ameliorates depression-like behaviors by restoring 5-HT levels. Methods. The depression model mice are established by chronic restraint stress (CRS). Ultrasound waves (FF = 1.1 MHz, PRF = 1000 Hz, TBD = 0.5 ms, SD = 1 s, ISI = 1 s, and DC = 50%) were delivered into the dorsal raphe nucleus (DRN) for 30 min per day for 2 weeks. Depression-like behavior changes are evaluated with the sucrose preference and tail suspension tests. Liquid chromatography–mass spectrometry is performed to quantitatively detect the concentration of 5-HT in the DRN to explore its potential mechanism. The effectiveness and safety of TUS were assessed by c-Fos immunofluorescence and hematoxylin and eosin (HE) staining, respectively. Results. Three weeks after CRS, 22 depressive mice models were screened by sucrose preference index (SPI). After 2 weeks of ultrasound stimulation of the DRN (DRN-TUS) in depressive mice, the SPI was increased (p = 0.1527) and the tail suspension immobility duration was significantly decreased (p = 0.0038) compared with the non-stimulated group. In addition, TUS significantly enhances the c-Fos (p = 0.05) positive cells’ expression and the 5-HT level (p = 0.0079) in the DRN. Importantly, HE staining shows no brain tissue damage. Conclusion. These results indicate that DRN-TUS has safely and effectively improved depression-like behaviors including anhedonia and hopelessness, potentially by reversing the depletion of 5-TH. Significance TUS may provide a new perspective on depression therapy, possibly through restoring monoamine levels.
Effect of Irradiation (SRFE) on MSM Photodetectors Device
Authors: Srithanachai Itsara , Sangwaranatee Narong
Published: August 2022

This paper presents the effect of high energy irradiation expose on metal-semiconductor-metal (MSM) photodetectors device. High energy radiation may impact to lattice structure of semiconductor device. The most impact of radiation on MSM device had been studied base on polycrystalline silicon. Based on our research in SRFE process exposed on P-N power device, radiation will interact with device mechanism and structure that change electrical properties of device. However, MSM device show electrical properties change after irradiation exposure process by photocurrent increased around 4 times when compare with non-irradiated.
Design of a Novel Wireless NoC Architecture for Chip Multiprocessor
Authors: Xin Yin , Song Guozhi
Published: August 2022

The Network on chip is a new communication method of System on Chip. It is the main part of multi-core technology. A large number of embedded cores can be combined on a single chip. Due to the multi-hop characteristics of communication, there are some problems in the design of traditional NoC, such as high latency and power consumption. Thus, to handle the communication problem of long-distance transmission of traditional NoC, wireless Networks on Chip (WiNoC) has been proposed. Using WiNoC to design the multi-core System on Chip can significantly reduce the latency and energy consumption of the network. The advantage of using wireless network on chip is to replace the multi-hop path of traditional network on chip with wireless single hop link. However, due to the limited space on the chip and the cost, it is very important to determine the optimal number and correct location of wireless hubs. In this paper, we propose a new method to obtain the optimum configuration of a WiNoC by using the Co-evolutionary Algorithms (CA) and a wireless NoC architecture based on mesh. This work examines the effect of VC and sub-net size on WiNoC performance efficiency and energy under different packet injection rate (PIR) and the number of cores (64, 144 and 256). The simulation experiment of the algorithm proposed in the whole architecture has been implemented on the Noxim platform.
UK perspective research landscape for offshore renewable energy and its role in delivering Net Zero
Authors: Greaves Deborah , Jin Siya , Wong Puiwah , White Dave , Jeffrey Henry , Scott Beth , Wigg Ross
Published: August 2022

This paper sets out the role of offshore renewable energy (ORE) in UK targets for Net Zero greenhouse gas emissions by 2050 and provides a review of the research challenges that face the sector as it grows to meet these targets. The research challenges are set out in a Research Landscape that was established by the ORE Supergen Hub following extensive consultation with the ORE community. The challenges are divided into eight themes, each challenge is described, and current progress is summarised. The progress of the ORE sector in recent years has seen huge cost reductions, which have encouraged the great ambition for the sector seen in UK Government targets. However, in order to meet these critical targets and achieve Net Zero, further innovations and novel technologies will be needed and at pace, driven forward by new research and innovation. The strategy of the Supergen ORE Hub in framing the research and innovation activities within a community-developed research landscape and working together across disciplines and with close collaboration between academia and industry is a necessary component in achieving the ambition of sustainable energy generation.
Evaluation of the physical-mechanical properties of mortar with cement/‘Ndoor’ composite binder
Authors: Mabekou Takam Jeanne Sandrine , Signe Tatchuen Brice , Tchitnga Robert , Kouefouet Hervice , Talla Pierre Kisito
Published: August 2022

The aim of our work is to characterize a mortar with a cement/‘Ndoor’ composite binder. The ‘Ndoor’ of scientific name ‘Irvingia Gabonensis’ is a vegetal material used as food (glutinous sauce) in Nigeria and also in the region of the East, the South, the North-West and the South-West of Cameroon. It is in fact the kernels of wild mango. We determine experimentally the mechanical properties of a mortar modified by partial substitution of cement by an addition called ‘Ndoor’. In experimental campaign, we realize different formulations of mortar diversified by the dosage of cement and ‘Ndoor’, which were made in the form of prismatic specimens 4*4*16 cm3. Compression tests were carried out, which allowed us to obtain the values of compressive strength and tensile strength. The results show that the ‘Ndoor’ improves the development of the mechanical resistances at the young age especially for values of substitution of the order of 2.5%, 5% and 7.5%. As a complement to the tests, a modeling having a predictive character of the elastic behavior of a mortar elastic behavior of a composite cement/‘Ndoor’ binder mortar is done. For this purpose, we have mortar has two phases: the hydrated cement paste and the inclusions (sand and ‘Ndoor’). The elastic properties of the cement paste are determined by the self-coherent homogenization model. Knowing the elastic properties of the cement paste and the inclusions, those of the mortar are deduced by the diluted scheme model of ESHELBY. The results show that, in the presence of the ‘Ndoor’, as the mass ratio e/c increases, the Young’s modulus of the modified mortar decreases.
Keys to accurate feature extraction using residual spiking neural networks
Authors: Vicente-Sola Alex , Manna Davide L , Kirkland Paul , Di Caterina Gaetano , Bihl Trevor
Published: August 2022

Spiking neural networks (SNNs) have become an interesting alternative to conventional artificial neural networks (ANN) thanks to their temporal processing capabilities and energy efficient implementations in neuromorphic hardware. However, the challenges involved in training SNNs have limited their performance in terms of accuracy and thus their applications. Improving learning algorithms and neural architectures for a more accurate feature extraction is therefore one of the current priorities in SNN research. In this paper we present a study on the key components of modern spiking architectures. We design a spiking version of the successful residual network architecture and provide an in-depth study on the possible implementations of spiking residual connections. This study shows how, depending on the use case, the optimal residual connection implementation may vary. Additionally, we empirically compare different techniques in image classification datasets taken from the best performing networks. Our results provide a state of the art guide to SNN design, which allows to make informed choices when trying to build the optimal visual feature extractor. Finally, our network outperforms previous SNN architectures in CIFAR-10 (94.14%) and CIFAR-100 (74.65%) datasets and matches the state of the art in DVS-CIFAR10 (72.98%), with less parameters than the previous state of the art and without the need for ANN–SNN conversion. Code available at: https://github.com/VicenteAlex/Spiking_ResNet.
Significance of mitochondrial fatty acid β-oxidation for the survivability of Aurantiochytrium limacinum ATCC MYA-1381 during sugar starvation
Authors: Nyunoya Hayato , Ishibashi Yohei , Ito Makoto , Okino Nozomu
Published: August 2022

Thraustochytrids are marine protists that accumulate large amounts of palmitic acid and docosahexaenoic acid in lipid droplets. Random insertional mutagenesis was adopted for Aurantiochytrium limacinum ATCC MYA-1381 to search for genes that regulate lipid metabolism in thraustochytrids. A mutant strain, M17, was selected because of its significant decrease in myristic acid, palmitic acid, and triacylglycerol contents and cell growth defect. Genome analysis revealed that the gene encoding for mitochondrial electron-transfer flavoprotein ubiquinone oxidoreductase (ETFQO) was lacking in the M17 strain. This mutant strain exhibited a growth defect at the stationary phase, possibly due to stagnation of mitochondrial fatty acid β-oxidation and branched-chain amino acid degradation, both of which were caused by lack of ETFQO. This study shows the usability of random insertional mutagenesis to obtain mutants of lipid metabolism in A. limacinum and clarifies that ETFQO is integral for survival under sugar starvation in A. limacinum.
The impact of type 2 diabetes on long-term gastrointestinal sequelae after colorectal cancer surgery: national population-based study
Authors: Laurberg Tinne , Frandsen Sara , Larsen Helene M , Lehrskov Louise L , Graversen Susanne B , Drewes Asbjørn M , Emmertsen Katrine J , Krogh Klaus
Published: August 2022

Background

Long-term gastrointestinal sequelae are common after colorectal cancer surgery, but the impact of type 2 diabetes (T2D) is unknown.

Methods

In a cross-sectional design, questionnaires regarding bowel function and quality of life (QoL) were sent to all Danish colorectal cancer survivors, who had undergone surgery between 2001 and 2014 and had more than 2 years follow-up without relapse. The prevalence of long-term gastrointestinal sequelae among colorectal cancer survivors with and without T2D were compared while stratifying for type of surgical resection and adjusting for age, sex, and time since surgery.

Results

A total of 8747 out of 14 488 colorectal cancer survivors answered the questionnaire (response rate 60 per cent), consisting of 3116 right-sided colonic, 2861 sigmoid, and 2770 rectal resections. Of these, 690 (7.9 per cent) had a diagnosis of T2D before surgery. Survivors with T2D following rectal resection had a 15 per cent (95 per cent c.i. 7.8 to 22) higher absolute risk of major low anterior resection syndrome, whereas survivors with T2D following right-sided and sigmoid resection had an 8 per cent higher risk of constipation (P < 0.001) but otherwise nearly the same long-term risk of bowel symptoms as those without T2D. For all types of colorectal cancer resections, T2D was associated with a 6–10 per cent higher risk of severe pain (P < 0.035) and a 4–8 per cent higher risk of impaired QoL.

Conclusion

T2D at time of surgery was associated with a higher risk of long-term bowel dysfunction after rectal resection, but not after colon resection excluding a higher risk of constipation. T2D was associated with a slightly higher frequency of severe pain and inferior QoL after both rectal and colonic cancer resection.
Retrieval of olfactory fear memory alters cell proliferation and expression of pCREB and pMAPK in the corticomedial amygdala and piriform cortex
Authors: Hakim Marziah , Beecher Kate , Jacques Angela , Chaaya Nicholas , Belmer Arnauld , Battle Andrew R , Johnson Luke R , Bartlett Selena E , Chehrehasa Fatemeh
Published: August 2022

The brain forms robust associations between odors and emotionally salient memories, making odors especially effective at triggering fearful or traumatic memories. Using Pavlovian olfactory fear conditioning (OFC), a variant of the traditional tone-shock paradigm, this study explored the changes involved in its processing. We assessed the expression of neuronal plasticity markers phosphorylated cyclic adenosine monophosphate response element binding protein (pCREB) and phosphorylated mitogen-activated protein kinase (pMAPK) 24 h and 14 days following OFC, in newborn neurons (EdU+) and in brain regions associated with olfactory memory processing; the olfactory bulb, piriform cortex, amygdale, and hippocampus. Here, we show that all proliferating neurons in the dentate gyrus of the hippocampus and glomerular layer of the olfactory bulb were colocalized with pCREB at 24 h and 14 days post-conditioning, and the number of proliferating neurons at both time points were statistically similar. This suggests the occurrence of long-term potentiation within the neurons of this pathway. Finally, OFC significantly increased the density of pCREB- and pMAPK-positive immunoreactive neurons in the medial and cortical subnuclei of the amygdala and the posterior piriform cortex, suggesting their key involvement in its processing. Together, our investigation identifies changes in neuroplasticity within critical neural circuits responsible for olfactory fear memory.
The Disproportionate Impact of Coronavirus Disease 2019 (COVID-19) Pandemic on Healthcare-Associated Infections in Community Hospitals: Need for Expanding the Infectious Disease Workforce
Authors: Advani Sonali D , Sickbert-Bennett Emily , Moehring Rebekah , Cromer Andrea , Lokhnygina Yuliya , Dodds-Ashley Elizabeth , Kalu Ibukunoluwa C , DiBiase Lauren , Weber David J , Anderson Deverick J ,   for the CDC Prevention Epicenters Program
Published: August 2022

Background

The coronavirus disease 2019 (COVID-19) pandemic had a considerable impact on US healthcare systems, straining hospital resources, staff, and operations. However, a comprehensive assessment of the impact on healthcare-associated infections (HAIs) across different hospitals with varying level of infectious disease (ID) physician expertise, resources, and infrastructure is lacking.

Methods

This retrospective longitudinal multicenter cohort study included central-line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), Clostridioides difficile infections (CDIs), and ventilator-associated events (VAEs) from 53 hospitals (academic and community) in Southeastern United States from 1 January 2018 to 31 March 2021. Segmented negative binomial regression generalized estimating equations models estimated changes in monthly incidence rates in the baseline (01/2018–02/2020) compared to the pandemic period (03/2020–03/2021, further divided into three pandemic phases).

Results

CLABSIs and VAEs increased by 24% and 34%, respectively, during the pandemic period. VAEs increased in all phases of the pandemic, while CLABSIs increased in later phases of the pandemic. CDI trend increased by 4.2% per month in the pandemic period. On stratifying the analysis by hospital characteristics, the impact of the pandemic on healthcare-associated infections was more significant in smaller sized and community hospitals. CAUTIs did not change significantly during the pandemic across all hospital types.

Conclusions

CLABSIs, VAEs, and CDIs increased significantly during the pandemic, especially in smaller community hospitals, most of which lack ID physician expertise. Future efforts should focus on better understanding challenges faced by community hospitals, strengthening the infection prevention infrastructure, and expanding the ID workforce, particularly to community hospitals.
Task reformulation and data-centric approach for Twitter medication name extraction
Authors: Zhang Yu , Lee Jong Kang , Han Jen-Chieh , Tsai Richard Tzong-Han
Published: August 2022

Automatically extracting medication names from tweets is challenging in the real world. There are many tweets; however, only a small proportion mentions medications. Thus, datasets are usually highly imbalanced. Moreover, the length of tweets is very short, which makes it hard to recognize medication names from the limited context. This paper proposes a data-centric approach for extracting medications in the BioCreative VII Track 3 (Automatic Extraction of Medication Names in Tweets). Our approach formulates the sequence labeling problem as text entailment and question–answer tasks. As a result, without using the dictionary and ensemble method, our single model achieved a Strict F1 of 0.77 (the official baseline system is 0.758, and the average performance of participants is 0.696). Moreover, combining the dictionary filtering and ensemble method achieved a Strict F1 of 0.804 and had the highest performance for all participants. Furthermore, domain-specific and task-specific pretrained language models, as well as data-centric approaches, are proposed for further improvements.

Database URL https://competitions.codalab.org/competitions/23925 and https://biocreative.bioinformatics.udel.edu/tasks/biocreative-vii/track-3/
Asymmetric septal thickening is observed in hypertrophic cardiomyopathy mutation carriers without left ventricular hypertrophy: insights from AI analysis
Authors: Shiwani H , Hughes R K , Camaioni C , Augusto J B , Knott K , Rosmini S , Burke L , Pierce I , Moon J C , Davies R H
Published: August 2022

Funding Acknowledgements

Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): Dr Hughes is supported by the British Heart Foundation (grant number FS/17/82/33222).

Background

Hypertrophic cardiomyopathy (HCM) is a common inherited cardiac disease characterised by left ventricular hypertrophy (LVH), often, with asymmetric septal thickening. Despite the prevalence of inherited mutations present in >50% of cases, there is variable phenotypic expression in those with abnormal sarcomere protein genes. In individuals with abnormal genes but without LVH, we hypothesised that there is subtle asymmetric septal hypertrophy, detectable by the increased precision offered by an artificial intelligence (AI) tool for measuring wall thickness.

Purpose

We explored the septal-lateral ratio measured by AI in individuals with an identified genotype but no left ventricular hypertrophy as a component of sub-clinical HCM.

Methods

43 individuals with identified genotype, but no left ventricular hypertrophy (G+LVH-) and 97 age-, sex- and disease-matched controls underwent CMR. Patients were excluded if they had a maximum wall thickness (MWT) of ≥13mm. A clinically validated AI tool was used to measure the MWT, for each segment in the 16-segment AHA model. The septal-lateral ratio was calculated using the septal segment with the largest MWT and the lateral segment with the largest MWT.

Results

The mean septal-lateral ratio of the G+LVH- patients was 1.22 (SD 0.22) and the mean septal-lateral ratio of the matched controls was 1.14 (SD 0.15) with a statistically significant mean difference of 0.08 (p=0.01). There was no significant difference between the MWT of the G+LVH- patients at 10.3mm (SD 2.2) and healthy volunteers at 10.1mm (SD 1.8) (p = 0.61).

Conclusion

G+LVH- patients have a 7% increase in their septal-lateral ratio compared with age-matched controls despite the lack of difference in the MWT. Using increased precision offered by AI, early features of HCM can be observed in patients without overt LVH.
Fully automated machine learning-based selection of optimal bSSFP frequency offset for artifact reduction in cardiac MRI
Authors: Yoon S , Gadjimuradov F , Schmidt M , Wetzl J , Maier A
Published: August 2022

Funding Acknowledgements

Type of funding sources: Private company. Main funding source(s): Research Support from Siemens Healthineers GmbH.

Background

In bSSFP sequences commonly used for cardiac MRI, signal modulation (e.g. banding artifacts) due to B0 inhomogeneity is often observed, especially at higher field strengths. The spatial position of these artifacts can be shifted by a frequency offset to reduce artifacts in a region of interest (ROI), e.g. the heart. To this end, frequency scout (FS) scans are acquired to visually select the optimal frequency offset [1,2]. In this work, we propose a fully automated image-based system for selecting the optimal frequency offset on FS images based on machine learning.

Methods

The proposed prototype system consists of four main steps (Fig.1). First, a pre-trained deep-learning-based whole heart segmentation network is applied on a four chamber-view FS image to localize the ROI where artifacts should be reduced. Second, high frequency components within the ROI (for each frequency offset in the FS series) are extracted by successive processing of Fourier transformation, high-pass filtering, inverse Fourier transformation and subtraction over series. and N images with the lowest high-frequency content are selected. Third, an adaptive weighting map for each FS image is generated which penalizes signal deviations from a pixel-wise median that is calculated based on the selected images [3]. By averaging the maps and selecting the frame with maximum percentage, the optimal frequency offset is selected.

A total of 38 datasets, acquired on multiple clinical 3T MRI scanners (MAGNETOM Skyra, Vida, Prisma, Lumina; Siemens Healthcare, Erlangen, Germany), were used to evaluate the proposed system. All FS series were annotated manually and used to compare with the system output. The experts were allowed to select multiple possible optimal FS images within a FS series. In case of multiple annotations, the system output was labelled as correct when it selected one of the offsets chosen by the expert. Further, the generated weighting maps were visually evaluated.

Results

The proposed system achieved an accuracy of 92.1% compared to experts’ ground truth annotations. From the failed cases (n=3), the maximum difference was off by 2 frames. Based on the generated weighting maps, a reasonable decision on the selection of the optimal frequency offset is made. The algorithm successfully selects an FS image with minimized banding and flow artifacts within the ROI (Fig. 2a). Further, it reveals that the generated weighting map correctly suppress areas containing artifacts (Fig. 2b).

Conclusions

Initial results demonstrate the feasibility of the proposed system to automatically select the optimal frequency offset on FS scans. Therefore, it can improve the automation of a cardiac MRI workflow. An example of the result of each step
Surface wave dispersion inversion using an energy likelihood function
Authors: Zhang Xin , Zheng York , Curtis Andrew
Published: August 2022

Seismic surface wave dispersion inversion is used widely to study the subsurface structure of the Earth. The dispersion property is usually measured by using frequency–phase velocity (f–c) analysis of data recorded on a local array of receivers. The apparent phase velocity at each frequency of the surface waves travelling across the array is that at which the f–c spectrum has maximum amplitude. However, because of potential contamination by other wave arrivals or due to complexities in the velocity structure the f–c spectrum often has multiple maxima at each frequency for each mode. These introduce errors and ambiguity in the picked phase velocities, and consequently the estimated shear velocity structure can be biased, or may not account for the full uncertainty in the data. To overcome this issue we introduce a new method which directly uses the spectrum as the data to be inverted. We achieve this by solving the inverse problem in a Bayesian framework and define a new likelihood function, the energy likelihood function, which uses the spectrum energy to define data fit. We apply the new method to a land data set recorded by a dense receiver array, and compare the results to those obtained using the traditional method. The results show that the new method produces more accurate results since they better match independent data from refraction tomography. This real-data application also shows that it can be applied with relatively little adjustment to current practice since it uses standard f–c panels to define the likelihood, and efficiently since it removes the need to pick phase velocities. We therefore conclude that the energy likelihood function can be a valuable tool for surface wave dispersion inversion in practice.
Separating GIA signal from surface mass change using GPS and GRACE data
Authors: Vishwakarma Bramha Dutt , Ziegler Yann , Bamber Jonathan L , Royston Sam
Published: August 2022

The visco-elastic response of the solid Earth to the past glacial cycles and the present-day surface mass change (PDSMC) are detected by the geodetic observation systems such as global navigation satellite system and satellite gravimetry. Majority of the contemporary PDSMC is driven by climate change and in order to better understand them using the aforementioned geodetic observations, glacial isostatic adjustment (GIA) signal should be accounted first. The default approach is to use forward GIA models that use uncertain ice-load history and approximate Earth rheology to predict GIA, yielding large uncertainties. The proliferation of contemporary, global, geodetic observations and their coverage have therefore enabled estimation of data-driven GIA solutions. A novel framework is presented that uses geophysical relations between the vertical land motion (VLM) and geopotential anomaly due to GIA and PDSMC to express GPS VLM trends and GRACE geopotential trends as a function of either GIA or PDSMC, which can be easily solved using least-squares regression. The GIA estimates are data-driven and differ significantly from forward models over Alaska and Greenland.
Expression and subcellular localization ofUSH1C/harmonin in human retina provides insights into pathomechanisms and therapy
Authors: Nagel-Wolfrum Kerstin , Fadl Benjamin R , Becker Mirjana M , Wunderlich Kirsten A , Schäfer Jessica , Sturm Daniel , Fritze Jacques , Gür Burcu , Kaplan Lew , Andreani Tommaso , Goldmann Tobias , Brooks Matthew , Starostik Margaret R , Lokhande Anagha , Apel Melissa , Fath Karl R , Stingl Katarina , Kohl Susanne , DeAngelis Margaret M , Schlötzer-Schrehardt Ursula , Kim Ivana K , Owen Leah A , Vetter Jan M , Pfeiffer Norbert , Andrade-Navarro Miguel A , Grosche Antje , Swaroop Anand , Wolfrum Uwe
Published: August 2022

Usher syndrome (USH) is the most common form of hereditary deaf-blindness in humans. USH is a complex genetic disorder, assigned to three clinical subtypes differing in onset, course and severity, with USH1 being the most severe. Rodent USH1 models do not reflect the ocular phenotype observed in human patients to date; hence, little is known about the pathophysiology of USH1 in the human eye. One of the USH1 genes, USH1C, exhibits extensive alternative splicing and encodes numerous harmonin protein isoforms that function as scaffolds for organizing the USH interactome. RNA-seq analysis of human retinae uncovered harmonin_a1 as the most abundant transcript of USH1C. Bulk RNA-seq analysis and immunoblotting showed abundant expression of harmonin in Müller glia cells (MGCs) and retinal neurons. Furthermore, harmonin was localized in the terminal endfeet and apical microvilli of MGCs, presynaptic region (pedicle) of cones and outer segments (OS) of rods as well as at adhesive junctions between MGCs and photoreceptor cells (PRCs) in the outer limiting membrane (OLM). Our data provide evidence for the interaction of harmonin with OLM molecules in PRCs and MGCs and rhodopsin in PRCs. Subcellular expression and colocalization of harmonin correlate with the clinical phenotype observed in USH1C patients. We also demonstrate that primary cilia defects in USH1C patient-derived fibroblasts could be reverted by the delivery of harmonin_a1 transcript isoform. Our studies thus provide novel insights into PRC cell biology, USH1C pathophysiology and development of gene therapy treatment(s).
Investment Funds, Monetary Policy, and the Global Financial Cycle
Authors: Kaufmann Christoph
Published: August 2022

This paper examines the role of international investment funds in the transmission of global financial conditions to the euro area using structural Bayesian vector auto regressions. While cross-border banking sector capital flows receded significantly in the aftermath of the global financial crisis, portfolio flows from investors actively searching for yield on financial markets worldwide gained importance during the post-crisis “second phase of global liquidity”. The analysis presented in this paper shows that a loosening of US monetary policy leads to higher investment fund inflows to equities and debt globally. Focussing on the euro area, these inflows not only imply elevated asset prices but also coincide with increased debt and equity issuance. The findings demonstrate the growing importance of non-bank financial intermediation over the past decade and hold important policy implications for monetary and financial stability.
Firms and Collective Reputation: a Study of the Volkswagen Emissions Scandal
Authors: Bachmann Rüdiger , Ehrlich Gabriel , Fan Ying , Ruzic Dimitrije , Leard Benjamin
Published: August 2022

This paper uses the 2015 Volkswagen (VW) emissions scandal as a natural experiment to provide evidence that collective reputation externalities are economically significant. Using a combination of difference-in-differences and demand estimation approaches, we document a spillover effect from the scandal to the non-VW German auto manufacturers. The spillover amounts to an average drop of $2,057 in consumer valuations of these manufacturers’ vehicles and a 34.6% reduction in their annual sales. We substantiate our interpretation that the estimates reflect a reputation spillover using data on internet search behavior and direct measures of consumer sentiment from Twitter.
Using a Workplace Rehabilitation and Reintegration Program Tracker Tool to Explore Factors Associated With Return to Duty Among Ill/Injured Military Personnel: A Preliminary Analysis
Authors: Lee Jennifer E C , Coulthard Julie
Published: August 2022

Introduction

A great deal of time and resources have been spent on developing and implementing evidence-based return to work programs over the past few decades, compelling researchers to better understand the factors associated with more favorable outcomes. Using data collected as part of a participant tracking system trial for the Canadian Armed Forces (CAF) Return to Duty (RTD) program, analyses were conducted to better understand the trajectories of program participants and identify the factors associated with RTD.

Materials and Methods

Participants included 205 Regular Force CAF members from a single military base located in Eastern Canada who entered the RTD program during the trial period between April 2018 and March 2020. The health condition they were facing was mostly recent (i.e., onset within the past 6 months; 43%) and involved their mental health (67%). Data were collected on various demographic, military, health, and program characteristics using the RTD Data Collection Tool, which was updated periodically by program coordinators. Using data gathered by the Tool, a cumulative incidence function was generated to estimate the overall marginal probability of RTD over the duration of the program. Associations between RTD and a range of factors that were captured using the Tool were also examined in a series of competing-risks regressions.

Results

Findings indicated that the rate of RTD among program participants increased at around 3 months and began to level off around 9 months, suggesting that the likelihood of RTD after this window is diminished. Of the many factors that were considered, only years of service and work placement status at 3 months were found to be associated with RTD. Specifically, lower rates of RTD were observed among participants with 15 or more years of service compared to those with less than 5 years of service in the CAF and among those who were not yet assigned a work placement at 3 months relative to those who were.

Conclusion

This study represents a first step in addressing the gap in our current knowledge about the characteristics of CAF members participating in the RTD program and the factors associated with RTD. Several recommendations are made for improving the participant tracking system in view of enhancing the level and quality of information that is available to assess participants’ trajectories and inform further development of the program.
Comorbidity, life-style factors and healthcare utilization in incident chronic kidney disease: sex-specific analyses of claims data
Authors: Colombo Miriam Giovanna , Förster Christian , Wallwiener Stephanie , Hassdenteufel Kathrin , Hawighorst-Knapstein Sabine , Kirtschig Gudula , Chaudhuri Ariane , Dally Simon , Joos Stefanie
Published: August 2022

Background

Chronic kidney disease (CKD) is common in aging men and women. In contrast to other European countries, Germany lacks CKD registries. The aim of this study was to determine the incidence of CKD stages 2–5 in men and women in Germany. Furthermore, differences between the sexes in terms of comorbidities, potentially inappropriate medications (PIM), and healthcare utilization were examined.

Methods

In this retrospective observational study, claims data from members of a statutory health insurance fund aged 18 years or older with incident CKD between 2011 and 2018 were analyzed. Incident CKD was defined as having two confirmed diagnoses of CKD stages 2–5 from outpatient care or one primary or secondary diagnosis from inpatient care.

Results

The age- and sex-standardized incidence of all CKD stages was 945/100 000 persons between 2011 and 2018. Incident CKD, especially stages 3 and 4, occurred more frequently in women, while the incidence of stages 2 and 5 was higher in men. While women visited their GP more frequently and were prescribed PIMs more often, men were more likely to visit a nephrologist and were more often hospitalized after the incident CKD diagnosis.

Conclusion

More awareness needs to be raised towards the early detection of CKD and the use of PIMs, especially in women. Improved care coordination is needed to avoid an overprovision of patients with uncomplicated incident stages and ensure that patients with advanced CKD stages get timely access to specialist care.
Automated detection and quantification of brain metastases on clinical MRI data using artificial neural networks
Authors: Pflüger Irada , Wald Tassilo , Isensee Fabian , Schell Marianne , Meredig Hagen , Schlamp Kai , Bernhardt Denise , Brugnara Gianluca , Heußel Claus Peter , Debus Juergen , Wick Wolfgang , Bendszus Martin , Maier-Hein Klaus H , Vollmuth Philipp
Published: August 2022

Background

Reliable detection and precise volumetric quantification of brain metastases (BM) on MRI are essential for guiding treatment decisions. Here we evaluate the potential of artificial neural networks (ANN) for automated detection and quantification of BM.

Methods

A consecutive series of 308 patients with BM was used for developing an ANN (with a 4:1 split for training/testing) for automated volumetric assessment of contrast-enhancing tumors (CE) and non-enhancing FLAIR signal abnormality including edema (NEE). An independent consecutive series of 30 patients was used for external testing. Performance was assessed case-wise for CE and NEE and lesion-wise for CE using the case-wise/lesion-wise DICE-coefficient (C/L-DICE), positive predictive value (L-PPV) and sensitivity (C/L-Sensitivity).

Results

The performance of detecting CE lesions on the validation dataset was not significantly affected when evaluating different volumetric thresholds (0.001–0.2 cm3; P = .2028). The median L-DICE and median C-DICE for CE lesions were 0.78 (IQR = 0.6–0.91) and 0.90 (IQR = 0.85–0.94) in the institutional as well as 0.79 (IQR = 0.67–0.82) and 0.84 (IQR = 0.76–0.89) in the external test dataset. The corresponding median L-Sensitivity and median L-PPV were 0.81 (IQR = 0.63–0.92) and 0.79 (IQR = 0.63–0.93) in the institutional test dataset, as compared to 0.85 (IQR = 0.76–0.94) and 0.76 (IQR = 0.68–0.88) in the external test dataset. The median C-DICE for NEE was 0.96 (IQR = 0.92–0.97) in the institutional test dataset as compared to 0.85 (IQR = 0.72–0.91) in the external test dataset.

Conclusion

The developed ANN-based algorithm (publicly available at www.github.com/NeuroAI-HD/HD-BM) allows reliable detection and precise volumetric quantification of CE and NEE compartments in patients with BM.
Fungal dual-domain LysM effectors undergo chitin-induced intermolecular, and not intramolecular, dimerization
Authors: Tian Hui , Fiorin Gabriel L , Kombrink Anja , Mesters Jeroen R , Thomma Bart P H J
Published: August 2022

Chitin is a homopolymer of β-(1,4)-linked N-acetyl-D-glucosamine (GlcNAc) and a major structural component of fungal cell walls. In plants, chitin acts as a microbe-associated molecular pattern (MAMP) that is recognized by lysin motif (LysM)-containing plant cell surface-localized pattern recognition receptors (PRRs) that activate a plethora of downstream immune responses. To deregulate chitin-induced plant immunity and successfully establish infection, many fungal pathogens secrete LysM domain-containing effector proteins during host colonization. The LysM effector Ecp6 from the tomato (Solanum lycopersicum) leaf mold fungus Cladosporium fulvum can outcompete plant PRRs for chitin binding because two of its three LysM domains cooperate to form a composite groove with ultra-high (pM) chitin-binding affinity. However, most functionally characterized LysM effectors contain only two LysMs, including Magnaporthe oryzae MoSlp1, Verticillium dahliae Vd2LysM, and Colletotrichum higginsianum ChElp1 and ChElp2. Here, we performed modeling, structural, and functional analyses to investigate whether such dual-domain LysM effectors can also form ultra-high chitin-binding affinity grooves through intramolecular LysM dimerization. However, our study suggests that intramolecular LysM dimerization does not occur. Rather, our data support the occurrence of intermolecular LysM dimerization for these effectors, associated with a substantially lower chitin binding affinity than monitored for Ecp6. Interestingly, the intermolecular LysM dimerization allows for the formation of polymeric complexes in the presence of chitin. Possibly, such polymers may precipitate at infection sites to eliminate chitin oligomers, and thus suppress the activation of chitin-induced plant immunity.