bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient Reconfigurable Mixed Precision $$\ell _1$$ Solver for Compressive Depth Reconstruction
Authors: Wu Yun , Wallace Andrew M. , Mota João F.C. , Aßmann Andreas , Stewart Brian 
Published: May 2022

AbstractRapid reconstruction of depth images from sparsely sampled data is important for many applications in machine perception, including robot or vehicle assistance or autonomy. Approximate computing techniques have been widely adopted to reduce resource consumption and increase efficiency in energy and resource constrained systems, especially targeted at FPGA and solid state implementation. Whereas previous work has focused on approximate, but static, representation of data in LiDAR systems, in this paper we show how the flexibility of an arbitrary precision accelerator with fine-grain tuning allows a better trade-off between algorithmic performance and implementation efficiency. A mixed precision framework of $$\ell _1$$

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1

solvers is presented, with compact ADMM and PGD, for the lasso problem, enabling compressive depth reconstruction by varying the precision scaling in single bit granularity during the iterative optimization process. Implementing mixed precision $$\ell _1$$

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solvers on an FPGA with a pipelined architecture for depth image reconstruction across various sensing scenarios, over 74% savings in hardware resources and 60% in power are achieved with only minor reductions in reconstructed depth image quality when compared to single float precision, while over 10% saving in hardware resources and power is achieved compared to relative consistently reduced precision solutions.
Improved distinct bone segmentation from upper-body CT using binary-prediction-enhanced multi-class inference.
Authors: Schnider Eva , Huck Antal , Toranelli Mireille , Rauter Georg , Müller-Gerbl Magdalena , Cattin Philippe C. 
Published: May 2022

Abstract

Purpose:

Automated distinct bone segmentation has many applications in planning and navigation tasks. 3D U-Nets have previously been used to segment distinct bones in the upper body, but their performance is not yet optimal. Their most substantial source of error lies not in confusing one bone for another, but in confusing background with bone-tissue.

Methods:

In this work, we propose binary-prediction-enhanced multi-class (BEM) inference, which takes into account an additional binary background/bone-tissue prediction, to improve the multi-class distinct bone segmentation. We evaluate the method using different ways of obtaining the binary prediction, contrasting a two-stage approach to four networks with two segmentation heads. We perform our experiments on two datasets: An in-house dataset comprising 16 upper-body CT scans with voxelwise labelling into 126 distinct classes, and a public dataset containing 50 synthetic CT scans, with 41 different classes.

Results:

The most successful network with two segmentation heads achieves a class-median Dice coefficient of 0.85 on cross-validation with the upper-body CT dataset. These results outperform both our previously published 3D U-Net baseline with standard inference, and previously reported results from other groups. On the synthetic dataset, we also obtain improved results when using BEM-inference.

Conclusion:

Using a binary bone-tissue/background prediction as guidance during inference improves distinct bone segmentation from upper-body CT scans and from the synthetic dataset. The results are robust to multiple ways of obtaining the bone-tissue segmentation and hold for the two-stage approach as well as for networks with two segmentation heads.
Deep learning-based classification of DSA image sequences of patients with acute ischemic stroke
Authors: Mittmann Benjamin J. , Braun Michael , Runck Frank , Schmitz Bernd , Tran Thuy N. , Yamlahi Amine , Maier-Hein Lena , Franz Alfred M. 
Published: May 2022

Abstract

Purpose

Recently, a large number of patients with acute ischemic stroke benefited from the use of thrombectomy, a minimally invasive intervention technique for mechanically removing thrombi from the cerebrovasculature. During thrombectomy, 2D digital subtraction angiography (DSA) image sequences are acquired simultaneously from the posterior-anterior and the lateral view to control whether thrombus removal was successful, and to possibly detect newly occluded areas caused by thrombus fragments split from the main thrombus. However, such new occlusions, which would be treatable by thrombectomy, may be overlooked during the intervention. To prevent this, we developed a deep learning-based approach to automatic classification of DSA sequences into thrombus-free and non-thrombus-free sequences.

Methods

We performed a retrospective study based on the single-center DSA data of thrombectomy patients. For classifying the DSA sequences, we applied Long Short-Term Memory or Gated Recurrent Unit networks and combined them with different Convolutional Neural Networks used as feature extractor. These network variants were trained on the DSA data by using five-fold cross-validation. The classification performance was determined on a test data set with respect to the Matthews correlation coefficient (MCC) and the area under the curve (AUC). Finally, we evaluated our models on patient cases, in which overlooking thrombi during thrombectomy had happened.

Results

Depending on the specific model configuration used, we obtained a performance of up to 0.77$$\mid $$
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0.94 for the MCC$$\mid $$
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AUC, respectively. Additionally, overlooking thrombi could have been prevented in the reported patient cases, as our models would have classified the corresponding DSA sequences correctly.

Conclusion

Our deep learning-based approach to thrombus identification in DSA sequences yielded high accuracy on our single-center test data set. External validation is now required to investigate the generalizability of our method. As demonstrated, using this new approach may help reduce the incident risk of overlooking thrombi during thrombectomy in the future.
AI-based optimization for US-guided radiation therapy of the prostate
Authors: Gerlach Stefan , Hofmann Theresa , Fürweger Christoph , Schlaefer Alexander 
Published: May 2022

Abstract
Objectives
Fast volumetric ultrasound presents an interesting modality for continuous and real-time intra-fractional target tracking in radiation therapy of lesions in the abdomen. However, the placement of the ultrasound probe close to the target structures leads to blocking some beam directions.

Methods
To handle the combinatorial complexity of searching for the ultrasound-robot pose and the subset of optimal treatment beams, we combine CNN-based candidate beam selection with simulated annealing for setup optimization of the ultrasound robot, and linear optimization for treatment plan optimization into an AI-based approach. For 50 prostate cases previously treated with the CyberKnife, we study setup and treatment plan optimization when including robotic ultrasound guidance.

Results
The CNN-based search substantially outperforms previous randomized heuristics, increasing coverage from 93.66 to 97.20% on average. Moreover, in some cases the total MU was also reduced, particularly for smaller target volumes. Results after AI-based optimization are similar for treatment plans with and without beam blocking due to ultrasound guidance.

Conclusions
AI-based optimization allows for fast and effective search for configurations for robotic ultrasound-guided radiation therapy. The negative impact of the ultrasound robot on the plan quality can successfully be mitigated resulting only in minor differences.
Two-stage deep learning framework for sRGB image white balance
Authors: Farghaly Marwa , Mansour Romany F. , Sewisy Adel A. 
Published: May 2022

AbstractThis work aims to correct white-balance errors in sRGB images. These white-balance errors are hard to fix due to the nonlinear color-processing procedures applied by camera image signal processors (ISP) to produce the final sRGB colors. Camera ISPs apply these nonlinear procedures after the essential white-balance step to render sensor raw images to the sRGB space through a camera-specific set of tone curves and look-up tables. To correct improperly white-balanced images, projecting non-linear sRGB colors back to their original raw space is required. Recent work formulates the problem as an image translation problem, where input sRGB colors are mapped using nonlinear polynomial correction functions to fix such white-balance errors. In this work, we show that correcting white-balance errors in sRGB images through a global color mapping followed by spatially local adjustments, learned in an end-to-end training, introduces perceptual improvements in the final results. Qualitative and quantitative comparisons with recently published methods for camera-rendered image white balancing validate our method’s efficacy and show that our method achieves competitive results with state-of-the-art methods.
A qualitative study of the experiences of participants in X-Fittt 2.0, a combined lifestyle intervention for citizens with a low socioeconomic status
Authors: Mulderij Lisanne Sofie , Wagemakers Annemarie , Verkooijen Kirsten Thecla 
Published: May 2022

AbstractX‑Fittt 2.0 is a two-year combined lifestyle intervention (CLI) for people with a low socioeconomic status (SES), which starts with 12 weeks of intensive guidance, followed by a follow-up trajectory. In the first 12 weeks, participants receive three weekly sports sessions (two in a group with a sports coach, one individually), dietary advice and monitoring by a dietician, and four hours of coaching by a lifestyle coach to work on personal goals. The follow-up trajectory consists of a total of six hours of lifestyle coaching to encourage behavioural maintenance. The aim of this study was to gain insight into the experiences of participants with X‑Fittt 2.0. Therefore, 17 group discussions after 12 weeks (n = 71) and individual interviews after 1–2 years (n = 68) were held and thematically analysed. This resulted in five themes: ‘goals of the participant’, ‘programme content’, ‘accessibility of the programme’, ‘group dynamics’ and ‘guidance’. Most participants participated because of their health. They considered the programme accessible because the atmosphere in the sports centre was pleasant and X‑Fittt 2.0 was offered free of charge. The majority of participants liked the fact that the programme was offered in a group ‘with people like them’, referring to people who are overweight, because they did not have to be ashamed of themselves, which motivated them. The participants were especially satisfied with the guidance from the lifestyle coach and sports coach. However, they would have expected more guidance from the dietician. Overall, most participants were satisfied with the programme, but many also indicated that the first 12 weeks were too short to achieve sustainable behavioural change. Furthermore, quite a few participants indicated to have stopped sports after the first 12 weeks, because they could not afford to continue. The insights obtained can be used to better adapt (existing) CLIs to people with low SES.
Een kwalitatief onderzoek naar de ervaringen van deelnemers aan X-Fittt 2.0 – een GLI voor mensen met een lage sociaaleconomische status
Authors: Mulderij Lisanne Sofie , Wagemakers Annemarie , Verkooijen Kirsten Thecla 
Published: May 2022

SamenvattingX‑Fittt 2.0 is een tweejarige gecombineerde leefstijlinterventie (GLI) voor mensen met een lage sociaaleconomische status (SES), die start met 12 weken intensieve begeleiding, gevolgd door een laagintensief natraject. Het doel van dit onderzoek was inzicht krijgen in de ervaringen van de deelnemers. Hiervoor zijn 17 groepsgesprekken (n = 71) na 12 weken en 68 individuele interviews na 1 en 2 jaar gehouden. Een thematisch analyse resulteerde in 5 thema’s: ‘doelen van de deelnemer’, ‘programma-inhoud’, ‘toegankelijkheid’, ‘groepsdynamiek’ en ‘begeleiding’. De meeste deelnemers gaven aan mee te doen vanwege hun gezondheid. Deelnemers vonden het programma toegankelijk door de prettige sfeer in het sportcentrum en het gratis (sport)aanbod. Het merendeel vond het fijn dat het programma werd aangeboden in een groep met ‘mensen zoals zij’, namelijk mensen met overgewicht. De deelnemers waren tevreden over de begeleiding door de leefstijlcoach en sportcoach. Van de diëtist hadden ze meer begeleiding verwacht. Hoewel deelnemers over het algemeen tevreden waren over het programma, gaf een groot deel aan dat de intensieve periode van 12 weken te kort was voor duurzame gedragsverandering. De opgedane inzichten kunnen bijdragen aan het aanpassen van (bestaande) GLI’s, zodat deze beter aansluiten bij mensen met een lage SES.
Mindfulness-Based School Interventions: a Systematic Review of Outcome Evidence Quality by Study Design
Authors: Phan Mary L. , Renshaw Tyler L. , Caramanico Julie , Greeson Jeffrey M. , MacKenzie Elizabeth , Atkinson-Diaz Zabryna , Doppelt Natalie , Tai Hungtzu , Mandell David S. , Nuske Heather J. 
Published: May 2022

Abstract

Objectives
The purpose of this systematic review was to assess the current literature on mindfulness-based school interventions (MBSIs) by evaluating evidence across specific outcomes for youth.

Methods
We evaluated 77 studies with a total sample of 12,358 students across five continents, assessing the quality of each study through a robust coding system for evidence-based guidelines. Coders rated each study numerically per study design as 1 +  + (RCT with a very low risk of bias) to 4 (expert opinion) and across studies for the corresponding evidence letter grade, from highest quality (“A Grade”) to lowest quality (“D Grade”) evidence.

Results
The highest quality evidence (“A Grade”) across outcomes indicated that MBSIs increased prosocial behavior, resilience, executive function, attention, and mindfulness, and decreased anxiety, attention problems/ADHD behaviors, and conduct behaviors. The highest quality evidence for well-being was split, with some studies showing increased well-being and some showing no improvements. The highest quality evidence suggests MBSIs have a null effect on depression symptoms.

Conclusions
This review demonstrates the promise of incorporating mindfulness interventions in school settings for improving certain youth outcomes. We urge researchers interested in MBSIs to study their effectiveness using more rigorous designs (e.g., RCTs with active control groups, multi-method outcome assessment, and follow-up evaluation), to minimize bias and promote higher quality—not just increased quantity—evidence that can be relied upon to guide school-based practice.
Soluplus® polymeric nanomicelles improve solubility of BCS-class II drugs
Authors: Pignatello Rosario , Corsaro Roberta , Bonaccorso Angela , Zingale Elide , Carbone Claudia , Musumeci Teresa 
Published: May 2022

Abstract
The issue of poor aqueous solubility is often a great hitch in the development of liquid dosage forms for those drugs that the Biopharmaceutics Classification System (BCS) includes in classes II and IV. Among the possible technological solutions, inclusion of the drug molecule within polymeric micelles, and particularly nanomicelles, has been proposed in the last years as a valid strategy. Our attention has been recently attracted by Soluplus®, an amphiphilic polyvinyl caprolactam-polyvinyl acetate-polyethylene glycol graft copolymer able to form small and stable nanomicelles. The aim of this study was to characterize Soluplus® nanomicelles to enhance the apparent solubility of three model APIs, categorized in BCS class II: ibuprofen (IBU), idebenone (IDE), and miconazole (MIC). Drug-loaded Soluplus® micelles with a mean size around 60–70 nm were prepared by two methods (direct dissolution or film hydration method). The prepared nanosystems were characterized in terms of mean particle size and Zeta potential, physical stability, drug solubility, and in vitro drug release. The solubility of the tested APIs was shown to increase linearly with the concentration of graft copolymer. Soluplus® can be easily submitted to membrane filtration (0.2 µm PES or PTFE membranes), showing the potential to be sterilized by this method. Freeze-drying enabled to obtain powder materials that, upon reconstitution with water, maintained the initial micelle size. Finally, viscosity studies indicated that these nanomicelles have potential applications where a bioadhesive material is advantageous, such as in topical ocular administration.
Graphical abstract
A novel kinematics and statics correction algorithm of semi-cylindrical foot end structure for 3-DOF LHDS of legged robots
Authors: Ba Kai-xian , Song Yan-he , Wang Chun-yu , Shi Ya-peng , Yu Bin , Chen Xin , Ma Guo-liang , Kong Xiang-dong 
Published: May 2022

AbstractIn this paper, aiming at the problem that the ideal modeling point of the foot end deviates from the actual contact point due to the rolling effect of the semi-cylindrical foot end in leg hydraulics drive system (LHDS), a novel and relatively simple kinematics and statics correction algorithm is proposed. This algorithm can effectively improve the accuracy of LHDS kinematics and statics, and it is still applicable when the body and the contact surface are at different angles. Firstly, this paper deduces the kinematics and statics when the foot end of LHDS is regarded as the point foot, analyzes and calculates the deviation under common working conditions. Secondly, in view of this phenomenon, a kinematics correction algorithm based on virtual DOF and a statics correction algorithm based on translation theorem of forces are proposed respectively. Finally, the proposed algorithm is verified by LHDS performance test platform under various working conditions. The results show that after applying the kinematics correction algorithm, the trajectory deviation reduction rate of the hip joint is over 65%; after applying the statics correction algorithm, the deviation reduction rate of foot end contact force is over 43%. The related research results can be applied to any similar foot end, which has engineering application value.
Alternative Method for Treating Electric Arc Furnace Dust: Simulation and Life Cycle Assessment
Authors: Rinne Marja , Halli Petteri , Aromaa Jari , Lundström Mari 
Published: May 2022

AbstractThe technical and environmental aspects of treating electric arc furnace dust (EAFD) using a novel process including alkaline roasting and organic acid leaching were evaluated and compared to the globally applied conventional Waelz process. The global warming potentials of the roasting–organic acid leaching process (with co-product credits) and the Waelz processes were 7.48 and 4.71 kg CO2-eq with 33% Zn dust as the feed material. However, with decreasing Zn content, the novel process become environmentally more competitive, and with 12% Zn, the corresponding GWP values were 6.31 and 9.26 kg CO2-eq. Co-product recovery decreased the net environmental impacts from the processing of the dust, which gave some benefits to the novel process. The Waelz process was observed to be energy intensive; however, the high consumption of leaching and roasting chemicals was the issue in the novel process. The excess caustic soda in the roasting step was observed to be a significant factor in the overconsumption of the organic acid in the leaching stage, and therefore, optimization of the roasting step is crucial. Other ways to decrease leaching chemical consumption include investigating the possibility to reuse the raffinate in leaching, or scrubbing the leach calcine from acid-consuming alkali. Evaluating the impacts of novel processes early enables iterative and agile process development and the directing the focus on the problem areas.
Graphical Abstract
Expanding the gene pool for soybean improvement with its wild relatives
Authors: Zhuang Yongbin , Li Xiaoming , Hu Junmei , Xu Ran , Zhang Dajian 
Published: May 2022

AbstractGenetic diversity is a cornerstone of crop improvement, However, cultivated soybean (Glycine max) has undergone several genetic bottlenecks, including domestication in China, the introduction of landraces to other areas of the world and, latterly, selective breeding, leading to low genetic diversity the poses a major obstacle to soybean improvement. By contrast, there remains a relatively high level of genetic diversity in soybean’s wild relatives, especially the perennial soybeans (Glycine subgenus Glycine), which could serve as potential gene pools for improving soybean cultivars. Wild soybeans are phylogenetically diversified and adapted to various habitats, harboring resistance to various biotic and abiotic stresses. Advances in genome and transcriptome sequencing enable alleles associated with desirable traits that were lost during domestication of soybean to be discovered in wild soybean. The collection and conservation of soybean wild relatives and the dissection of their genomic features will accelerate soybean breeding and facilitate sustainable agriculture and food production.
Assessing the risk of foreign investment within the petroleum sector of South America
Authors: Tafur Yeltsin , Lilford Eric , Aguilera Roberto F. 
Published: May 2022

AbstractThere is presently a shortage of international oil companies investing in South America, due primarily to political instability associated with high levels of corruption, poor quality of institutions, and demanding fiscal regimes that strip significant amounts of revenue from investors. The purpose of this research is to obtain a comprehensive country ranking for South America in terms of investment risk in the upstream oil sector. The study identifies six risk categories (political risk, macroeconomic risk, technical risk, investment climate, non-renewable energy resources potential, and environmental constraint) and ten sub-indicators associated with these risks. The data are gathered to perform an ‘analytic hierarchy process (AHP)’ to obtain the weight index of the ten sub-indicators. These are then used in a ‘technique for order preference by similarity to ideal solution (TOPSIS)’ to obtain the country-ranking risk arrangement. Results indicate that countries with low-risk investment include Brazil, Colombia and Peru, while high-risk countries include Argentina, Ecuador and Bolivia. Finally, this study suggests that countries whose proportions of government take exceed 75% should modify their fiscal regimes to optimize benefits for all parties or design fiscal systems where the host government and contractor share the risk and reward associated with exploiting oil resources.
Environmental severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contamination in hospital rooms during the first and third coronavirus disease 2019 (COVID-19) waves
Authors: Le Neindre Killian , Couturier Jeanne , Schnuriger Aurélie , Jolivet Sarah , Gouot Cyril , Majerholc Mickaël , Supplisson Pierre , Tan Céline , Perrier Marine , Lazare Christelle , Morand-Joubert Laurence , Barbut Frédéric 
Published: May 2022

Abstract
We investigated the frequency, distribution, and risk factors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) environmental contamination around infected patients during the first and third wave of the coronavirus disease 2019 pandemic. The shedding of SARS-CoV-2 in rooms of infected patients was limited in our hospital setting.