bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nonlinear Model Predictive Control with Enhanced Actuator Model for Multi-Rotor Aerial Vehicles with Generic Designs
Authors: Bicego Davide , Mazzetto Jacopo , Carli Ruggero , Farina Marcello , Franchi Antonio 
Published: September 2020

AbstractIn this paper, we propose, discuss, and validate an online Nonlinear Model Predictive Control (NMPC) method for multi-rotor aerial systems with arbitrarily positioned and oriented rotors which simultaneously addresses the local reference trajectory planning and tracking problems. This work brings into question some common modeling and control design choices that are typically adopted to guarantee robustness and reliability but which may severely limit the attainable performance. Unlike most of state of the art works, the proposed method takes advantages of a unified nonlinear model which aims to describe the whole robot dynamics by explicitly including a realistic physical description of the actuator dynamics and limitations. As a matter of fact, our solution does not resort to common simplifications such as: (1) linear model approximation, (2) cascaded control paradigm used to decouple the translational and the rotational dynamics of the rigid body, (3) use of low-level reactive trackers for the stabilization of the internal loop, and (4) unconstrained optimization resolution or use of fictitious constraints. More in detail, we consider as control inputs the derivatives of the propeller forces and propose a novel method to suitably identify the actuator limitations by leveraging experimental data. Differently from previous approaches, the constraints of the optimization problem are defined only by the real physics of the actuators, avoiding conservative – and often not physical – input/state saturations which are present, e.g., in cascaded approaches. The control algorithm is implemented using a state-of-the-art Real Time Iteration (RTI) scheme with partial sensitivity update method. The performances of the control system are finally validated by means of real-time simulations and in real experiments, with a large spectrum of heterogeneous multi-rotor systems: an under-actuated quadrotor, a fully-actuated hexarotor, a multi-rotor with orientable propellers, and a multi-rotor with an unexpected rotor failure. To the best of our knowledge, this is the first time that a predictive controller framework with all the valuable aforementioned features is presented and extensively validated in real-time experiments and simulations.
Advancing Fusion with Machine Learning Research Needs Workshop Report
Authors: Humphreys David , Kupresanin A. , Boyer M. D. , Canik J. , Chang C. S. , Cyr E. C. , Granetz R. , Hittinger J. , Kolemen E. , Lawrence E. , Pascucci V. , Patra A. , Schissel D. 
Published: September 2020

AbstractMachine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available athttps://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.
Are Trustworthiness and Legitimacy ‘Hard to Win, Easy to Lose’? A Longitudinal Test of the Asymmetry Thesis of Police-Citizen Contact
Authors: Oliveira Thiago R. , Jackson Jonathan , Murphy Kristina , Bradford Ben 
Published: September 2020

Abstract
Objectives
Test the asymmetry thesis of police-citizen contact that police trustworthiness and legitimacy are affected more by negative than by positive experiences of interactions with legal agents by analyzing changes in attitudes towards the police after an encounter with the police. Test whether prior attitudes moderate the impact of contact on changes in attitudes towards the police.

Methods
A two-wave panel survey of a nationally representative sample of Australian adults measured people’s beliefs about police trustworthiness (procedural fairness and effectiveness), their duty to obey the police, their contact with the police between the two waves, and their evaluation of those encounters in terms of process and outcome. Analysis is carried out using autoregressive structural equation modeling and latent moderated structural models.

Results
The association between both process and outcome evaluation of police-citizen encounters and changes in attitudes towards the police is asymmetrical for trust in police effectiveness, symmetrical for trust in procedural fairness, and asymmetrical (in the opposite direction expected) for duty to obey the police. Little evidence of heterogeneity in the association between encounters and trust in procedural fairness and duty to obey, but prior levels of perceived effectiveness moderate the association between outcome evaluation and changes in trust in police effectiveness.

Conclusions
The association between police-citizen encounters and attitudes towards the police may not be as asymmetrical as previously thought, particularly for changes in trust in procedural fairness and legitimacy. Policy implications include considering public-police interactions as ‘teachable moments’ and potential sources for enhancing police trustworthiness and legitimacy.
Comparison of Machine Learning Performance Using Analytic and Holistic Coding Approaches Across Constructed Response Assessments Aligned to a Science Learning Progression
Authors: Jescovitch Lauren N. , Scott Emily E. , Cerchiara Jack A. , Merrill John , Urban-Lurain Mark , Doherty Jennifer H. , Haudek Kevin C. 
Published: September 2020

AbstractWe systematically compared two coding approaches to generate training datasets for machine learning (ML): (i) a holistic approach based on learning progression levels and (ii) a dichotomous, analytic approach of multiple concepts in student reasoning, deconstructed from holistic rubrics. We evaluated four constructed response assessment items for undergraduate physiology, each targeting five levels of a developing flux learning progression in an ion context. Human-coded datasets were used to train two ML models: (i) an 8-classification algorithm ensemble implemented in the Constructed Response Classifier (CRC), and (ii) a single classification algorithm implemented in LightSide Researcher’s Workbench. Human coding agreement on approximately 700 student responses per item was high for both approaches with Cohen’s kappas ranging from 0.75 to 0.87 on holistic scoring and from 0.78 to 0.89 on analytic composite scoring. ML model performance varied across items and rubric type. For two items, training sets from both coding approaches produced similarly accurate ML models, with differences in Cohen’s kappa between machine and human scores of 0.002 and 0.041. For the other items, ML models trained with analytic coded responses and used for a composite score, achieved better performance as compared to using holistic scores for training, with increases in Cohen’s kappa of 0.043 and 0.117. These items used a more complex scenario involving movement of two ions. It may be that analytic coding is beneficial to unpacking this additional complexity.
The assessment of lining structure impact on radon behaviour inside selected underground workings under the cour d’honneur of Książ castle
Authors: Fijałkowska-Lichwa Lidia 
Published: September 2020

AbstractThe results based on 2-year long measurements 01 Jan. 2016–2031 Dec. 2017 have been used for discussing the influence of tunnel lining on the size of 222Rn activity concentration and the impact of the employed rock mass insulation on natural convective air exchange. In April, air movement started when the temperature was at least 7 °C lower than the mean inside. Between May and October, an increase to 9 °C above the underground temperature resulted in an increase of radon concentration. An unconstrained convection process did not start until November and it continued until the end of March. The reinforced concrete lining insulated the fractured and absorptive rock mass. The roof and the sidewall lining had little impact on air movement process.
Cleaved amplified polymorphic sequences (CAPS) marker for identification of two mutant alleles of the rapeseed BnaA.FAD2 gene
Authors: Matuszczak Marcin , Spasibionek Stanisław , Gacek Katarzyna , Bartkowiak-Broda Iwona 
Published: September 2020

AbstractTwo mutants of winter rapeseed (Brassica napus L. var. oleifera) with an increased amount of oleic acid in seeds were created by chemical mutagenesis (HOR3-M10453 and HOR4-M10464). The overall performance of the mutated plants was much lower than that of wild-type cultivars. Multiple rounds of crossing with high-yielding double-low (“00”) cultivars and breeding lines having valuable agronomic traits, followed by selection of high oleic acid genotypes is then needed to obtain new “00” varieties of rapeseed having high oleic acid content in seeds. To perform such selection, the specific codominant cleaved amplified polymorphic sequences (CAPS) marker was used. This marker was designed to detect the presence of two relevant point mutations in the desaturase gene BnaA.FAD2, and it was previously described and patented. The specific polymerase chain reaction product (732 bp) was digested using FspBI restriction enzyme that recognizes the 5′-C↓TAG-3′ sequence which is common to both mutated alleles, thereby yielding band patterns specific for those alleles. The method proposed in the patent was redesigned, adjusted to specific laboratory conditions, and thoroughly tested. Different DNA extraction protocols were tested to optimize the procedure. Two variants of the CAPS method (with and without purification of amplified product) were considered to choose the best option. In addition, the ability of the studied marker to detect heterozygosity in the BnaA.FAD2 locus was also tested. Finally, we also presented some examples for the use of the new CAPS marker in the marker-assisted selection (MAS) during our breeding programs. The standard CTAB method of DNA extraction and the simplified, two-step (amplification/digestion) procedure for the CAPS marker are recommended. The marker was found to be useful for the detection of two mutated alleles of the studied BnaA.FAD2 desaturase gene and can potentially assure the breeders of the purity of their HOLL lines. However, it was also shown that it could not detect any other alleles or genes that were revealed to play a role in the regulation of oleic acid level.
EVI1 oncoprotein expression and CtBP1-association oscillate through the cell cycle
Authors: Paredes Roberto , Schneider Marion , Pearson Stella , Teng Hsiang Yin , Kelly James R. , Pierce Andrew , Somervaille Tim C. P. , Whetton Anthony D. , Meyer Stefan 
Published: September 2020

AbstractAberrantly high expression of EVI1 in acute myeloid leukaemia (AML) is associated with poor prognosis. For targeted treatment of EVI1 overexpressing AML a more detailed understanding of aspects of spatiotemporal interaction dynamics of the EVI1 protein is important. EVI1 overexpressing SB1690CB AML cells were used for quantification and protein interaction studies of EVI1 and ΔEVI1. Cells were cell cycle-synchronised by mimosine and nocodazole treatment and expression of EVI1 and related proteins assessed by western blot, immunoprecipitation and immunofluorescence. EVI1 protein levels oscillate through the cell cycle, and EVI1 is degraded partly by the proteasome complex. Both EVI1 and ΔEVI1 interact with the co-repressor CtBP1 but dissociate from CtBP1 complexes during mitosis. Furthermore, a large fraction of EVI1, but not ΔEVI1 or CtBP1, resides in the nuclear matrix. In conclusion, EVI1- protein levels and EVI1-CtBP1 interaction dynamics vary though the cell cycle and differ between EVI1 and ΔEVI1. These data ad to the functional characterisation of the EVI1 protein in AML and will be important for the development of targeted therapeutic approaches for EVI1-driven AML.
Chloramphenicol enhances Photosystem II photodamage in intact cells of the cyanobacterium Synechocystis PCC 6803
Authors: Kodru Sandeesha , ur Rehman Ateeq , Vass Imre 
Published: September 2020

AbstractThe effect of chloramphenicol, an often used protein synthesis inhibitor, in photosynthetic systems was studied on the rate of Photosystem II (PSII) photodamage in the cyanobacterium Synechocystis PCC 6803. Light-induced loss of PSII activity was compared in the presence of chloramphenicol and another protein synthesis inhibitor, lincomycin, by measuring the rate of oxygen evolution in Synechocystis 6803 cells. Our data show that the rate of PSII photodamage was significantly enhanced by chloramphenicol, at the usually applied 200 μg mL−1 concentration, relative to that obtained in the presence of lincomycin. Chloramphenicol-induced enhancement of photodamage has been observed earlier in isolated PSII membrane particles, and has been assigned to the damaging effect of chloramphenicol-mediated superoxide production (Rehman et al. 2016, Front Plant Sci 7:479). This effect points to the involvement of superoxide as damaging agent in the presence of chloramphenicol also in Synechocystis cells. The chloramphenicol-induced enhancement of photodamage was observed not only in wild-type Synechocystis 6803, which contains both Photosystem I (PSI) and PSII, but also in a PSI-less mutant which contains only PSII. Importantly, the rate of PSII photodamage was also enhanced by the absence of PSI when compared to that in the wild-type strain under all conditions studied here, i.e., without addition and in the presence of protein synthesis inhibitors. We conclude that chloramphenicol enhances photodamage mostly by its interaction with PSII, leading probably to superoxide production. The presence of PSI is also an important regulatory factor of PSII photodamage most likely via decreasing excitation pressure on PSII.
Entry Regulation and Persistence of Profits in Incumbent Firms
Authors: Desai Sameeksha , Eklund Johan E. , Lappi Emma 
Published: September 2020

AbstractIn line with the theory of creative destruction, industries where incumbent firms generate high profits will attract entry, which should drive down profits. This disciplinary effect of entry implies that profits above the norm should not exist in the long run. Factors that affect entry—such as entry regulations—could affect this profits convergence process. Using an unbalanced panel of firm- and country-level data for approximately 13,000 firms in 33 countries between 2005 and 2013, we examine the profit dynamics of incumbent firms in the context of entry and entry regulations.
Firmware code instrumentation technology for internet of things-based services
Authors: Chen Chen , Ma Jinxin , Qi Tao , Cui Baojiang , Qi Weikong , Zhang Zhaolei , Sun Peng 
Published: September 2020

AbstractWith the rapid development of electronic and information technology, Internet of Things (IoT) devices have become extensively utilised in various fields. Increasing attention has been paid to the performance and security analysis of IoT-based services. Dynamic instrumentation is a common process in software analysis for acquiring runtime information. However, due to the limited software and hardware resources in IoT devices, most dynamic instrumentation tools do not support IoT-based services. In this paper, we provide an analysis tool, IoTDIT, to solve the current problem of runtime detection in IoT-based services. IoTDIT employs static analysis andptracesystem calls to obtain dynamic firmware information, which can aid in firmware performance analysis and security detection. We perform experiments to verify the performance and effectiveness of the proposed instrumentation tool.
Estimated biomass carbon in thinned Cunninghamia lanceolate plantations at different stand-ages
Authors: Zhang Xie , Wu Zhenming , Xu Zhongkun , Xu Liang , Xu Qingqian , Lin Jianzhong 
Published: September 2020

AbstractChinese fir (Cunninghamia lanceolate [Lamb.] Hook.) is a fast-growing species which is not only important as a timber-supplier, but also as an available sink for carbon (C) storage in biomass. Stand age and density are two critical factors that can determine tree C sequestration as interrelated drivers through natural self-thinning. C. lanceolate were planted using 1-year-old bare-root seedlings at the initial density of 1800 stems ha−1 in a 15-ha montane area of Hunan Province, China in 1987. The plantation was thinned twice 10 and 20 years after planting to leave trees of 437.5 ± 26.6, 675.0 ± 155.2 and 895.8 ± 60.1 stems ha−1 as low, medium, and high densities, respectively. Tree height and diameter at breast height (DBH) were measured every 2 years beginning from 23 years (2009) to 31 years (2018) after establishment, timber volume (TV) and biomass C were estimated accordingly. We did not find any interactive effect of age and density on any variables except for height. Both TV and biomass C increased with stand age or decreased in higher densities. The allometric height-DBH relationship can be fitted by an exponential rising-to-maximum model with higher maximum value over time. The decline of biomass C along density fit with the inverse first-order polynomial model which indicated that at least 1300–1500 stems ha−1 may be needed to maximize TV and biomass C for a longer term over 20 years. Therefore, to control the density to a reasonable level, over 1300 stems ha−1 in a rotation over 20 years old will be practical for tree biomass C in Chinese fir plantations.
Participative Innovation Platforms (PIP) for Upgrading NTFP Value Chains in East Africa
Authors: Auch Eckhard , Pretzsch Jürgen 
Published: September 2020

AbstractImproving forest product value chains is considered a means to solve forest-related challenges in the Global South. The ‘Participative Innovation Platform’ (PIP) instrument has been developed to design and to continually adapt solutions and strategies for effective cooperation amongst value chain actors. The instrument is rooted in the action-oriented and social learning approach, combined with the concept of innovation systems. This paper presents findings from three PIPs conducted for upgrading non-timber forest product value chains in Ethiopia (bamboo, natural gums) and Sudan (gum Arabic). A comparative analysis of highest ranked contents revealed similarities in the challenges: lack of government support, poor infrastructure, producers’ lack of knowledge and skills, and lack of market information. Priority upgrading measures focused on producers’ knowledge, skills, and capacity to engage in collective action and to lobby interests, and on capital resources to invest in processing technology. It is concluded that although the PIP instrument presents an innovative way to upgrade forest-based value chains, the instrument requires a long-term process with frequently held platform meetings, conducted by neutral institutions with skilled moderators. Crucial in this process is the need to consistently verify and ensure that all actor groups of the chain are represented, and are confident they will derive benefits from the value chain upgrading.
Prevention, Detection, and Management of Heart Failure in Patients Treated for Breast Cancer
Authors: Broberg Agneta Månsson , Geisler Jürgen , Tuohinen Suvi , Skytta Tanja , Hrafnkelsdóttir Þórdís Jóna , Nielsen Kirsten Melgaard , Hedayati Elham , Omland Torbjørn , Offersen Birgitte V. , Lyon Alexander R. , Gulati Geeta 
Published: September 2020

Abstract
Purpose of Review
Long-term survival has increased significantly in breast cancer patients, and cardiovascular side effects are surpassing cancer-related mortality. We summarize risk factors, prevention strategies, detection, and management of cardiotoxicity, with focus on left ventricular dysfunction and heart failure, during breast cancer treatment.

Recent Findings
Baseline treatment of cardiovascular risk factors is recommended. Anthracycline and trastuzumab treatment constitute a substantial risk of developing cardiotoxicity. There is growing evidence that this can be treated with beta blockers and angiotensin antagonists. Early detection of cardiotoxicity with cardiac imaging and circulating cardiovascular biomarkers is currently evaluated in clinical trials. Chest wall irradiation accelerates atherosclerotic processes and induces fibrosis. Immune checkpoint inhibitors require consideration for surveillance due to a small risk of severe myocarditis. Cyclin-dependent kinases4/6 inhibitors, cyclophosphamide, taxanes, tyrosine kinase inhibitors, and endocrine therapy have a lower-risk profile for cardiotoxicity.

Summary
Preventive and management strategies to counteract cancer treatment–related left ventricular dysfunction or heart failure in breast cancer patients should include a comprehensive cardiovascular risk assessment and individual clinical evaluation. This should include both patient and treatment-related factors. Further clinical trials especially on early detection, cardioprevention, and management are urgently needed.