bluuebunny/crossref_metadata_2025_split huggingface dataset:
Designed and synthesized de novo ANTPABA-PDI nanomaterial as an acceptor in inverted solar cell at ambient atmosphere
Authors: Mitra Soumyadeep , Ray Sudipta , Ghosh Narendra Nath , Hota Poulami , Mukherjee Arnab , Bagui Anirban , Maiti Dilip K 
Published: May 2023

Abstract
In this work, a novel soluble and air-stable electron acceptor containing perylenediimide moiety named ANTPABA-PDI was designed and synthesized with band gap 1.78eV and that was used as non-fullerene acceptor material. ANTPABA-PDI possess not only good solubility but also much lower LUMO (lowest unoccupied molecular orbital) energy level. Furthermore, its excellent electron acceptor capability also supported by density functional theory calculation which validates the experimental observations. Inverted organic solar cell has been fabricated using ANTPABA-PDI along with P3HT as standard donor material in ambient atmosphere. The device, after characterization in open air, exhibited a power conversion efficiency of 1.70%. This is the first ever PDI based organic solar cell that has been fabricated completely in ambient atmosphere. The characterizations of the device have also been performed in ambient atmosphere. This kind of stable organic material can easily be used in fabricating organic solar cell and therefore it can be used as the best alternative as non-fullerene acceptor materials.
Uncertainty estimation for deep learning-based pectoral muscle segmentation via Monte Carlo dropout
Authors: Klanecek Zan , Wagner Tobias , Wang Yao-Kuan , Cockmartin Lesley , Marshall Nicholas , Schott Brayden , Deatsch Ali , Studen Andrej , Hertl Kristijana , Jarm Katja , Krajc Mateja , Vrhovec Miloš , Bosmans Hilde , Jeraj Robert 
Published: May 2023

Abstract

Objective. Deep Learning models are often susceptible to failures after deployment. Knowing when your model is producing inadequate predictions is crucial. In this work, we investigate the utility of Monte Carlo (MC) dropout and the efficacy of the proposed uncertainty metric (UM) for flagging of unacceptable pectoral muscle segmentations in mammograms. Approach. Segmentation of pectoral muscle was performed with modified ResNet18 convolutional neural network. MC dropout layers were kept unlocked at inference time. For each mammogram, 50 pectoral muscle segmentations were generated. The mean was used to produce the final segmentation and the standard deviation was applied for the estimation of uncertainty. From each pectoral muscle uncertainty map, the overall UM was calculated. To validate the UM, a correlation between the dice similarity coefficient (DSC) and UM was used. The UM was first validated in a training set (200 mammograms) and finally tested in an independent dataset (300 mammograms). ROC-AUC analysis was performed to test the discriminatory power of the proposed UM for flagging unacceptable segmentations. Main results. The introduction of dropout layers in the model improved segmentation performance (DSC = 0.95 ± 0.07 versus DSC = 0.93 ± 0.10). Strong anti-correlation (r = −0.76, p < 0.001) between the proposed UM and DSC was observed. A high AUC of 0.98 (97% specificity at 100% sensitivity) was obtained for the discrimination of unacceptable segmentations. Qualitative inspection by the radiologist revealed that images with high UM are difficult to segment. Significance. The use of MC dropout at inference time in combination with the proposed UM enables flagging of unacceptable pectoral muscle segmentations from mammograms with excellent discriminatory power.
Strategy to implement a convolutional neural network based ideal model observer via transfer learning for multi-slice simulated breast CT images
Authors: Kim Gihun , Han Minah , Baek Jongduk 
Published: May 2023

Abstract

Objective. In this work, we propose a convolutional neural network (CNN)-based multi-slice ideal model observer using transfer learning (TL-CNN) to reduce the required number of training samples. Approach. To train model observers, we generate simulated breast CT image volumes that are reconstructed using the FeldkampDavisKress algorithm with a ramp and Hanning-weighted ramp filter. The observer performance is evaluated on the background-known-statistically (BKS)/signal-known-exactly task with a spherical signal, and the BKS/signal-known-statistically task with random signal generated by the stochastic grown method. We compare the detectability of the CNN-based model observer with that of conventional linear model observers for multi-slice images (i.e. a multi-slice channelized Hotelling observer (CHO) and volumetric CHO). We also analyze the detectability of the TL-CNN for different numbers of training samples to examine its performance robustness to a limited number of training samples. To further analyze the effectiveness of transfer learning, we calculate the correlation coefficients of filter weights in the CNN-based multi-slice model observer. Main results. When using transfer learning for the CNN-based multi-slice ideal model observer, the TL-CNN provides the same performance with a 91.7% reduction in the number of training samples compared to that when transfer learning is not used. Moreover, compared to the conventional linear model observer, the proposed CNN-based multi-slice model observers achieve 45% higher detectability in the signal-known-statistically detection tasks and 13% higher detectability in the SKE detection tasks. In correlation coefficient analysis, it is observed that the filters in most of the layers are highly correlated, demonstrating the effectiveness of the transfer learning for multi-slice model observer training. Significance. Deep learning-based model observers require large numbers of training samples, and the required number of training samples increases as the dimensions of the image (i.e. the number of slices) increase. With applying transfer learning, the required number of training samples is significantly reduced without performance drop.
Segmentation of retinal detachment and retinoschisis in OCT images based on complementary multi-class segmentation networks
Authors: Shi Fei , Yang Changqing , Jiang Qingxin , Zhu Weifang , Xu Xun , Chen Xinjian , Fan Ying 
Published: May 2023

Abstract
Retinal detachment (RD) and retinoschisis (RS) are the main complications leading to vision loss in high myopia. Accurate segmentation of RD and RS, including its subcategories (outer, middle, and inner retinoschisis) in optical coherence tomography images is of great clinical significance in the diagnosis and management of high myopia. For this multi-class segmentation task, we propose a novel framework named complementary multi-class segmentation networks. Based on domain knowledge, a three-class segmentation path (TSP) and a five-class segmentation path (FSP) are designed, and their outputs are integrated through additional decision fusion layers to achieve improved segmentation in a complementary manner. In TSP, a cross-fusion global feature module is adopted to achieve global receptive field. In FSP, a novel three-dimensional contextual information perception module is proposed to capture long-range contexts, and a classification branch is designed to provide useful features for segmentation. A new category loss is also proposed in FSP to help better identify the lesion categories. Experiment results show that the proposed method achieves superior performance for joint segmentation of RD and the three subcategories of RS, with an average Dice coefficient of 84.83%.
Constrained CycleGAN for effective generation of ultrasound sector images of improved spatial resolution
Authors: Sun Xiaofei , Li He , Lee Wei-Ning 
Published: May 2023

Abstract

Objective. A phased or a curvilinear array produces ultrasound (US) images with a sector field of view, which inherently exhibits spatially-varying image resolution with inferior quality in the far zone and towards the two sides azimuthally. Sector US images with improved spatial resolutions are favorable for accurate quantitative analysis of large and dynamic organs, such as the heart. Therefore, this study aims to translate US images with spatially-varying resolution to ones with less spatially-varying resolution. CycleGAN has been a prominent choice for unpaired medical image translation; however, it neither guarantees structural consistency nor preserves backscattering patterns between input and generated images for unpaired US images. Approach. To circumvent this limitation, we propose a constrained CycleGAN (CCycleGAN), which directly performs US image generation with unpaired images acquired by different ultrasound array probes. In addition to conventional adversarial and cycle-consistency losses of CycleGAN, CCycleGAN introduces an identical loss and a correlation coefficient loss based on intrinsic US backscattered signal properties to constrain structural consistency and backscattering patterns, respectively. Instead of post-processed B-mode images, CCycleGAN uses envelope data directly obtained from beamformed radio-frequency signals without any other nonlinear postprocessing. Main results. In vitro phantom results demonstrate that CCycleGAN successfully generates images with improved spatial resolution as well as higher peak signal-to-noise ratio and structural similarity compared with benchmarks. Significance. CCycleGAN-generated US images of the in vivo human beating heart further facilitate higher quality heart wall motion estimation than benchmarks-generated ones, particularly in deep regions. The codes are available at https://github.com/xfsun99/CCycleGAN-TF2
Prevention of mode coupling by external applied resonant magnetic perturbation on the J-TEXT tokamak
Authors: He Ying , Wang Nengchao , Li Da , Ding Yonghua , Zhou Song , Mao Feiyue , Ren Zhengkang , Zha Xianqian , Zhao Chuanxu , Li Yangbo , Hu Bo , Wang Jiaming , Bala Abba Alhaji , Hou Zhangrong , Jiang Zhonghe , Yang Zhoujun , Chen Zhipeng , Chen Zhongyong , Pan Yuan 
Published: May 2023

Abstract
Toroidal coupling between m/n = 2/1 and m/n = 3/1 modes frequently occurs in the J-TEXT, where m (n) is the poloidal (toroidal) mode number. These coupled modes destabilize each other, leading to confinement degradation and even triggering a major disruption. This paper presents two control strategies for preventing the mode coupling through the application of a proper static resonant magnetic perturbation (RMP) field. Experimental results demonstrate that moderate 2/1 RMP can suppress the small, rotating 2/1 mode thus prevent coupling between the 2/1 and 3/1 modes. The 3/1 static RMP can excite a large 3/1 locked island while leave the small 2/1 mode rotating at 8 kHz. Enlarging the frequency difference between 2/1 and 3/1 modes makes mode coupling more difficult. Both strategies can break the frequency coupling condition between the 2/1 and 3/1 modes, and hence avoid coupling and mutual destabilizing.
MICROSCOPE’s view at gravitation
Authors: Bergé Joel 
Published: May 2023

Abstract
The weak equivalence principle (WEP) is the cornerstone of general relativity (GR). Testing it is thus a natural way to confront GR to experiments, which has been pursued for four centuries with increasing precision. MICROSCOPE is a space mission designed to test the WEP with a precision of 1 in 1015 parts, two orders of magnitude better than previous experimental constraints. After completing its two-year mission, from 2016 to 2018, MICROSCOPE delivered unprecedented precise constraints

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(at 1σ in statistical errors) on the Eötvös parameter between one proof mass made of titanium and another made of platinum. This bound allowed for improved constraints on alternative theories of gravitation. This review discusses the science beyond MICROSCOPE—GR and its alternatives, with an emphasis on scalar–tensor theories—before presenting the experimental concept and apparatus. The mission’s science returns are then discussed before future tests of the WEP are introduced.
Interpreting the Hi 21-cm cosmology maps through Largest Cluster Statistics. Part I. Impact of the synthetic SKA1-Low observations
Authors: Dasgupta Saswata , Pal Samit Kumar , Bag Satadru , Dutta Sohini , Majumdar Suman , Datta Abhirup , Pathak Aadarsh , Kamran Mohd , Mondal Rajesh , Sarkar Prakash 
Published: May 2023

Abstract
We analyse the evolution of the largest ionized region using the topological and
morphological evolution of the redshifted 21-cm signal coming from the neutral hydrogen
distribution during the different stages of reionization. For this analysis, we use the “Largest
Cluster Statistics” — LCS. We mainly study the impact of the array synthesized beam on the LCS
analysis of the 21-cm signal considering the upcoming low-frequency Square Kilometer Array (SKA1-Low) observations using a realistic simulation for such observation based on the
21cmE2E-pipeline using OSKAR. We find that bias in LCS estimation is introduced in synthetic
observations due to the array beam. This in turn shifts the apparent percolation transition point
towards the later stages of reionization. The biased estimates of LCS, occurring due to the effect
of the lower resolution (lack of longer baselines) and the telescope synthesized beam will lead to
a biased interpretation of the reionization history. This is important to note while interpreting
any future 21-cm signal images from upcoming or future telescopes like the SKA, HERA, etc. We
conclude that one may need denser uv-coverage at longer baselines for a better deconvolution of
the array synthesized beam from the 21-cm images and a relatively unbiased estimate of LCS from
such images.
Dual-HR-FBG based single-frequency fiber laser at 1030 nm
Authors: Sun Bo , Ma Li , Ren Li , Zhang Xueqiang , Bai Jintao 
Published: May 2023

Abstract
We demonstrate a single-frequency fiber laser operating at 1030 nm with a distributed Bragg reflector cavity consisting of two high-reflectivity fiber Bragg gratings (HR-FBGs). By proper thermal adjustment, the gain bandwidth of the fiber laser is significantly compressed through the spectral overlap near the edges of the reflection band of two HR-FBGs, and the single-longitudinal-mode lasing is achieved. The effective cavity length of the fiber laser with the proposed cavity configuration is calculated, and its variation with the temperature difference between two HR-FBGs is also verified through the observation of the relaxation oscillation frequency shift. The measured laser linewidth is about 4.45 kHz at a temperature difference of 48.2 °C. The single-frequency output power of 14.4 mW is achieved at a pump power of 540 mW.
Excitation of toroidally localized harmonics of global Alfvén eigenmodes
Authors: Fredrickson E.D. 
Published: May 2023

Abstract
The spherical tokamak NSTX and the upgraded, higher toroidal field, NSTX-U, routinely create plasmas with large un-thermalized populations of super-Alfvénic fast ions. This population of non-thermal energetic ions excites a broad spectrum of Alfvénic waves, from the lower frequency (≈30 kHz–≈200 kHz) toroidal Alfvén eigenmodes (Cheng and Chance 1986 Phys. Fluids 29 3695), to the higher frequency (400 kHz–3 MHz) global Alfvén eigenmodes (GAEs) and compressional Alfvén eigenmodes (Goedbloed 1975 Phys. Fluids 18 1258). In this paper we present evidence that the GAE non-linearly excite modes, presumably GAE, at frequencies consistent with non-linear or 3-wave coupling. The observation of the excitation of 2nd harmonic GAE through the intrinsic non-linearity of Global Alfvén modes demonstrates that the non-linear terms can act as an exciter-antenna inside the plasma, broadcasting at harmonics of the mode frequency and with concomitantly shorter wavelengths. As with experiments using external antenna to excite otherwise weakly stable Alfvénic modes, this data can provide information about the stability of modes at harmonics of the GAE. It may also provide information on the nature of the non-linearities in the wave dispersion equation or a direct measure of the mode amplitude (Smith et al 2006 Phys. Plasmas 13 042504). We also report that the short wavelength 2nd harmonic GAE can be strongly toroidally localized. The observation that the shorter wavelength (n ≈ 20) 2nd harmonic modes can be toroidally localized potentially has implications for the impact of fast-ion driven instabilities on fast-ion confinement in ITER and future fusion reactors (Gorelenkov et al 2014 Nucl. Fusion 54 125001).
Development of polarized neutron techniques at the China Spallation Neutron Source
Authors: Tian Long , Huang Chuyi , Dong Yuchen , Salman Ahmed , Zhang Junpei , Qin Zecong , Ye Fan , Kreuzpaintner Wolfgang , Wang Tianhao , Tong Xin 
Published: May 2023

Abstract
In this article, the ongoing development progress of the polarized neutron technique developments at the China Spallation Neutron Source (CSNS) is presented. The general goal of establishing polarized neutron capability in parallel to CSNS beamline construction is also explained. The key instrument development projects of developing the Spin-Exchange Optical Pumping (SEOP) 3He systems, polarized neutron devices, and their application on neutron beamlines are demonstrated. Performance parameters of the developed techniques are also discussed.
in-situ
3He neutron spin filters at JCNS, status and updates
Authors: Babcock E. , Salhi Z. , Feoktystov A. , Bannenberg L.J. , Parnell S.R. , Alba Venero D. , Hutanu V , Thoma H. , Xu J. , Pistel P. , Damean J. , Ioffe A. , Mattauch S. 
Published: May 2023

Abstract
The JCNS has been developing and using in-situ polarized neutron spin filters for many applications. The system used for analysis on MARIA and polarization for TOPAS were completed about 10 years ago with the MARIA system in standard operation for users and the TOPAS system employed for a long measurement on the POLI instrument. In the meantime we are progressing on several new in-situ polarizers based on these first two but with additional innovations. The KWS-1 analyzer device which was recently used in tests at TU Delft and ISIS is essentially a 50%-sized copy of the MARIA device. The two devices in construction for polarization and analysis on POLI for hot neutrons feature magic-boxes with angled plates on both the entrance and exit sides to minimize overal length and the polarizer device will employ an additional passive magnetic shield of soft iron so that it can operate inside the stray field area of a 8-T vertical (compensated) sample magnet. We will summarize the current status of our 3He neutron spin filters and provide extra focus on the technical aspects and measured performance characteristics of the new devices for KWS-1 and POLI in particular.
Impact of land tenure on deforestation control and forest restoration in Brazilian Amazonia
Authors: Camara Gilberto , Simoes Rolf , Ruivo Heloisa M , Andrade Pedro R , Soterroni Aline C , Ramos Fernando M , Ramos Rafael G , Scarabello Marluce , Almeida Claudio , Sanches Ieda , Maurano Luis , Coutinho Alexandre , Esquerdo Julio , Antunes João , Venturieri Adriano , Adami Marcos 
Published: May 2023

Abstract
This study examines how land tenure constrains Brazil’s ability to meet its deforestation control and forest restoration goals in its Amazonia biome. Our findings are based on an updated assessment of land tenure and land use in the region. Between 2019 and 2021, 44% of deforestation in Amazonia occurred in private lands, while forest removal in settlements ranged from 31% to 27% of the total. Deforestation in undesignated public lands increased from 11% in 2008 to 18% in 2021. Deforestation is highly concentrated, with 1% of properties accounting for 82.5% of forest cuts in 2021. In Amazonia, there is considerable non-compliance with the legal reserve provisions set by Brazil’s Forest Code. Legal reserve deficits in private lands sum up to 18.17 Mha (million hectares), compared with 12.49 Mha of legal reserve surpluses. Even if all forest surpluses are offered in the forest credits market set in the Forest Code, farmers still need to restore 5.67 Mha to comply with the law. Large-scale cattle ranchers have a legal reserve deficit of 10.35 Mha (34% of their area). Most crop farming occurs in medium and large properties (4.63 Mha) with a large proportion of legal reserve deficits (45%). Given the political power and financial resources of large ranchers and crop producers, Brazil faces major challenges in inducing these farmers to meet their legal obligations. Therefore, Brazil needs to combine robust command-and-control strategies with market-based policies to achieve its deforestation and forest restoration goals. The government should tailor forest protection and restoration policies to the needs of different landowners, considering their land use practices, technical capacity, and financial resources.
Understanding Consumer perception towards the usage of natural gas as Compressed Natural Gas (CNG) and Piped Natural Gas (PNG)
Authors: Paul Dipen , Sharma Rashi 
Published: May 2023

Abstract
Natural gas is one of the cleanest and most environment-friendly fuels compared to all other alternative fuels. It can potentially be the next-generation fuel in India, but there is still limited use of natural gas. The paper aims to understand consumer perception and identify the main driving factors influencing consumers to use natural gas as a fuel source. A survey was conducted to understand consumers’ perceptions, and a sample size of 105 individuals was tested for various hypotheses. Most of the responses from the individuals are from Delhi, followed by Uttar Pradesh and Chhattisgarh. The data collected was analyzed by IBM SPSS software through factor analysis followed by regression. The result showed that implementing policies is one of the highest influential factors in accelerating the use of natural gas. Further, it was analyzed that affordability, infrastructure, environmental benefits, and performance of natural gas are the factors on which policies should be focused to increase the use of natural gas as Compressed natural gas (CNG) and Piped natural gas (PNG).
Performance of hydraulic oils and its additives in fluid power system: A review
Authors: Pabsetti Pranav , Murty R S V N , Bhoje Jai , Mathew Simon , Harivenkatesh  , Rahul K , Feroskhan M 
Published: May 2023

Abstract
The main objective of this paper is to analyze various hydraulic oils and the effect of additives like nanomaterials in order to increase lubricity, counter friction, reduce wear, etc. A detailed list of additives is focused in this review which will enhance the performance and working of the hydraulic fluid by enhancing lubrication, modifying viscosity and cleaning engine deposits. Mineral oils or Synthetic hydrocarbon blends are used to derive lubricants. Although they lack properties of their own to fulfill the requirements set by the Original Equipment Manufacturers (OEMs). By using nanomaterials in mineral oils various advantages can be obtained. Various nanomaterials such as metal chalcogenides, soft metals, carbon-based materials, etc. are available which via mechanisms such as the rolling effect, protective film effect, etc., can change the various properties of hydraulic oils as required. Similarly, additives are added to hydraulic oils like viscosity index improvers, anti-wear agents which will improve the properties of the hydraulic oil by eliminating negative properties and improving the life of the fluid. These additives play a crucial role in sustainability of hydraulic oils and their size can be optimized to get better tribological characteristics. The increasing usage of these high performance additives in the country is projected to register a compound annual growth rate (CARG) of more than 1.5% during the forecast period (2021-2026). The review focusses on the improved performance of these nanomaterials and additives when added to the Hydraulic Fluid and will serve as a reference for future developments in the application of additives and nanotechnology in hydraulic oils.