bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning-Enabled Prediction of Transient Injection Map In Automotive Injectors With Uncertainty Quantification
Authors: Mondal Sudeepta , Magnotti Gina M. , Lusch Bethany , Maulik Romit , Torelli Roberto
Published: November 2021

Accurate prediction of injection profiles is a critical aspect of linking injector operation with engine performance and emissions. However, highly resolved injector simulations can take one to two weeks of wall-clock time, which is incompatible with engine design cycles with desired turnaround times of less than a day. Hence, it is important to reduce the time-to-solution of the internal flow simulations by several orders of magnitude to make it compatible with engine simulations. This work demonstrates a data-driven approach for tackling the computational overhead of injector simulations, whereby the transient injection profiles are emulated for a side-oriented, single-hole diesel injector using a Bayesian machine-learning framework. First, an interpretable Bayesian learning strategy was employed to understand the effect of design parameters on the total void fraction field. Then, autoencoders are utilized for efficient dimensionality reduction of the flowfields. Gaussian process models are finally used to predict the spatio-temporal void fraction field at the injector exit for unknown operating conditions. The Gaussian process models produce principled uncertainty estimates associated with the emulated flowfields, which provide the engine designer with valuable information of where the data-driven predictions can be trusted in the design space. The Bayesian flowfield predictions are compared with the corresponding predictions from a deep neural network, which has been transfer-learned from static needle simulations from a previous work by the authors. The emulation framework can predict the void fraction field at the exit of the orifice within a few seconds, thus achieving a speed-up factor of up to 38 million over the traditional simulation-based approach of generating transient injection maps.
Data-Driven Approaches to Learn HyChem Models
Authors: Ji Weiqi , Zanders Julian , Park Ji-Woong , Deng Sili
Published: November 2021

The HyChem (Hybrid Chemistry) approach has recently been proposed for modeling high-temperature combustion of real, multi-component fuels. The approach combines lumped reaction steps for fuel thermal and oxidative pyrolysis with detailed chemistry for the oxidation of the resulting pyrolysis products. Determining the pyrolysis submodel requires extensive experimentation on speciation measurements. Recent work has been directed to learn HyChem from an existing HyChem model for a similar fuel, which requires less data. However, the approach usually shows substantial discrepancies with experimental data within the Negative Temperature Coefficient (NTC) regime, as the low-temperature chemistry is more fuel-specific than high-temperature chemistry. This paper proposes a machine learning approach to learn the HyChem models that can cover both high-temperature and low-temperature regimes. Specifically, we develop a HyChem model using the experimental datasets of ignition delay times covering a wide range of temperatures and equivalence ratios. The chemical kinetic model is treated as a neural network model, and we then employ stochastic gradient descent (SGD), a technique that was developed for deep learning, for the training. We demonstrate the approach in learning the HyChem model for F-24, which is a Jet-A derived fuel, and compare the results with previous work employing genetic algorithms. The results show that the SGD approach can achieve comparable model performance with genetic algorithms but the computational cost is reduced by 1000 times. In addition, with regularization in SGD, the SGD approach changes the kinetic parameters from their original values much less than genetic algorithm and is thus more likely to retrain mechanistic meanings. Finally, our approach is built upon open-source packages and can be applied to the development and optimization of chemical kinetic models for internal combustion engine simulations.
Investigations of Low-Temperature Heat Release and Negative Temperature Coefficient Regions of Iso-Paraffinic Kerosene in a Constant Volume Combustion Chamber
Authors: Soloiu Valentin , Smith Richard , Weaver Amanda , Grall Drake , Carapia Cesar , Parker Lily , Ilie Marcel , Rahman Mosfequr , Molina Gustavo
Published: November 2021

Research was conducted to observe the correlation of ignition delay, combustion delay, the negative temperature coefficient region (NTCR), and the low temperature heat release region (LTHR), in a constant volume combustion chamber (CVCC) in relation to blended amounts of iso-paraffinic kerosene (IPK) by mass with Jet-A and their derived cetane numbers (DCN). The study utilizes the ASTM standard D7668-14.a in a PAC CID 510 CVCC. The DCN was calculated using the ignition delay and combustion delay measured over 15 combustion events. The fuel blends investigated were 75%Jet-A blended with 25%IPK, 50%Jet-A with 50%IPK, 25%Jet-A with 75%IPK, neat Jet-A, and neat IPK. The ignition delay of neat Jet-A and IPK was found to be 3.26ms and 5.31ms, respectively, and the combustion delay of the fuels were 5.00ms and 17.17 ms, respectively. The ignition delay for 75Jet-A25IPK, 50Jet-A50IPK, 25Jet-A75IPK, fuel blends were found to be 3.5ms, 3.8ms, and 4.2ms, respectively. The combustion delay between the 75Jet-A25IPK, 50Jet-A50IPK, 25Jet-A75IPK, blends are 5.8ms, 7.0ms, and 9.4ms, respectively. The DCNs for 75Jet-A25IPK, 50Jet-A50IPK, 25Jet-A75IPK 43.1, 38.7, and 33.5, respectively. The DCN of the fuel blends compared to neat Jet-A was lower by 10.16% for 75Jet-A25IPK, 19.37% for 50Jet-A50IPK, 30.50% for 25Jet-A75IPK and 46.03% for neat IPK. Blends with larger amounts by mass of IPK resulted in extended ignition and combustion delays. It is concluded that the fuels that have larger amounts of IPK blended within them have extended NTC regions, LTHR regions, and decreased ringing intensity during combustion.
On Blow-by Aerosol Sources in a Single-Cylinder Crankcase Environment
Authors: Nowak N. , Scheiber K. , Stieler C. , Heller M. T. , Pfeil J. , Koch T. , Kasper G.
Published: November 2021

Crankcase aerosol contributes to the particulate matter (PM) emissions of combustion engines equipped with an open crankcase ventilation system. In case of closed crankcase ventilation, the aerosol forms deposits that diminish engine efficiency, performance, and reliability. Such issues are best avoided by highly efficient filters combined with in-engine reduction strategies based on a quantitative understanding of aerosol sources and formation mechanisms in a crankcase environment. This paper reports key findings from a study of aerosol spectra in the range of 0.01 μm to 10 μm obtained from a 1.3-L single-cylinder engine under well-defined conditions.

Supermicron particles were formed mainly by cooling jet break-up when the piston was positioned in TDC, while at BDC aerosol generation decreased by about 90 % because the oil jet was short and thus stable. Motoring the engine yielded an additional peak around 0.7 μm. It is associated with oil atomization at the piston rings and increased strongly with cylinder peak pressure. No significant contribution of the bearings could be identified at peak pressures below 116 bar. Engine speed had only a minor effect on aerosol properties. Operating the engine in fired mode increased the submicron aerosol concentration substantially, presumably because high(er) peak pressures boost aerosol generation at the piston rings, and because additional particles may have formed from recondensing oil vapor generated at hotspots. Soot or ash aerosols could not be identified in the crankcase aerosol, because they may have been integrated into the bulk oil.
Oribotritia species (Acari, Oribatida) from northeast China with descriptions of two new species and a key to Chinese species
Authors: Liu Dong , Huang Min
Published: November 2021

In the present study, two new species of oribatid mites, Oribotritia paragigas sp. nov. from Liaoning Province and Oribotritia mordagaensis sp. nov. from Great Khingan, are described. An identification key to all known Chinese species of the genus Oribotritia is provided.
Neoseiulus californicus (Acari: Phytoseiidae) shows good predation potential when reared on an artificial diet supplemented with Tetranychus cinnabarinus
Authors: Jiang ChunXian , Chen Lin , Huang TingTing , Mumtaz Maryam , Li Qing
Published: November 2021

To evaluate the predation potential of Neoseiulus californicus (McGregor) reared on an artificial diet as a biological control agent for Tetranychus cinnabarinus (Boisduval), life table and functional response studies were performed. To identify alternative food sources for rearing N. californicus, we compared the nutritional values of the basal diet (composed of sucrose, yeast extract, honey, tryptone and egg yolk), meridic diet (add T. cinnabarinus on the basis of basal diet) and control (T. cinnabarinus). Further, the predation ability of N. californicus continuously reared for ten consecutive generations on a meridic diet to control T. cinnabarinus was assessed. The results showed that N. californicus fed the basal and meridic diets successfully completed development from eggs to adults, but they did not oviposit when fed the basal diet. The high fecundity (41.00 eggs per female) and intrinsic rate of increase (0.2357 d-1) recorded in the meridic diet group suggests that it is a suitable diet for N. californicus rearing. Additionally, a functional response (type II) was observed in N. californicus reared on the meridic diet. We found that when the predator was reared on the meridic diet, the estimated maximum attack rate (T/Th) associated with larvae was 58.67, which was only 13.94% lower than the control (68.17). The 10th generation of N. californicus did not lose the ability to capture and kill T. cinnabarinus when fed on meridic diet. In conclusion, N. californicus reared on the meridic diet containing T. cinnabarinus showed good predation ability; therefore, this diet may be beneficial for the mass production of N. californicus.
Enhancing Student Learning of Global Warming Through Reflective Writing
Authors: Zeng Liang , Zeng Guang
Published: November 2021

The National Academy of Science has published studies showing strong scientific evidence that global warming is caused by human consumption of fossil fuels, yet recent surveys have shown young adults in the U.S. are disengaged or disagree with this fact. Accordingly, the United Nations Educational, Scientific, and Cultural Organization (UNESCO) published learning objectives to educate the world population on global warming and renewable energy by 2030. In this paper, we introduce a reflective writing activity physics educators can employ to foster a deeper understanding of global warming in introductory college physics and physical science courses, without overloading their teaching time.
PEER Physics: An evidence-based framework for inclusive physics curricula
Authors: Martins Julian S. , Belleau Shelly N. , Otero Valerie K.
Published: November 2021

Physics is one of the least diverse disciplines amongst the natural sciences. Large-scale studies, such as those from the National Assessment of Educational Progress, have indicated that students from underrepresented and racially minoritized groups score below students from dominant groups, and female students are typically outperformed by their male peers. While there are several complex systemic factors that maintain the status quo, we ask: what is it about how we engage our students in physics classes that perpetuates these inequities, and: how can our pedagogy promote inclusion?
Active noise and vibration control of systems with primary path nonlinearities using FxLMS, Neural Networks and Recursive Neural Networks
Authors: Pike Xander , Cheer Jordan
Published: November 2021

Active control systems are often used to surmount the challenges associated with using passive control measures to control low frequencies, since they achieve control without the application of large or heavy control treatments. Historically, linear active control strategies have been used in feed-forward control systems to drive the control source to minimise the signal measured at the error sensor. However, when the response from noise source to error sensor becomes nonlinear, either in the primary or secondary path, the performance of such controllers can suffer. To overcome this limitation, it has previously been shown that Neural Networks (NNs) can outperform linear controllers. Furthermore, Recursive Neural Networks (RNNs) have been shown to outperform classical feed-forward networks in some cases. This is usually explained by the RNNs ability to form a rudimentary “memory.” This paper compares the behaviour of the linear FxLMS algorithm, a NN and an RNN through their application to the control of a simulated system with variable levels of saturation and hysteretic nonlinearities in the primary path. It is demonstrated that the NN is capable of greater control of saturation nonlinearities than FxLMS. Similarly, the RNN is capable of greater control of hysteretic nonlinearities than the NN.
Supplemental Material: The importance of oxbow lakes in the floodplain storage of pollutants
Authors: Thomas Summer-Solstice , Constantine José , al. et
Published: November 2021

Radiometric data from Woods Pond, Massachusetts, loss-on-ignition data from cores collected along transect T1, and coordinates of core locations.
Acceptability of different oral dosage forms in paediatric patients in hospital setting
Authors: Pokharkar Varsha , Sajith Manjusha , Vallet Thibault , Akshantal Shruti , Shah Rathin , Ruiz Fabrice , Salunke Smita
Published: November 2021

Objective

The understanding of acceptability of existing dosage forms is limited in most of the world and hinders the development of acceptable, age‐appropriate medicines. The attributes of paediatric medicine acceptability may differ from country to country based on culture, healthcare infrastructure and health policies. This study was designed to map the acceptability of oral medicines in paediatric patients treated in hospital in India.

Methods

An observational, cross-sectional study was conducted in patients aged below 18 years and taking any form of oral medication. Acceptability scores were obtained using CAST–ClinSearch Acceptability Score Test tool.

Findings

490 patients were recruited and 193 evaluations of different pharmaceutical products available in 20 dosage forms and 7 routes of administration were studied. Oral liquids (50%) and tablets (35%) were the most commonly prescribed and administered forms. Regardless of the therapeutic class and age, the oral liquids were ‘positively accepted’ in infants and toddlers. Acceptability of tablets improved with age and appeared to be generally good from the age of 6.

Conclusion

This study indicates the limited progress towards adoption of age-appropriate dosage forms in India and thus impact on the acceptability of existing oral dosage forms. The key challenges posed by the adoption of age-appropriate formulations in India are (1) awareness of importance of appropriate administration and acceptability of medicines to children in India, (2) availability of age-appropriate dosage forms and (3) lack of child-appropriate medicine policies.
Impact of COVID-19 lockdown on surgical procedures for retinal detachment in France: a national database study
Authors: Baudin Florian , Benzenine Eric , Mariet Anne-Sophie , Ben Ghezala Inès , Daien Vincent , Gabrielle Pierre-Henry , Quantin Catherine , Creuzot-Garcher Catherine P
Published: November 2021

Background/aims

The COVID-19 crisis and the decisions made regarding population lockdown may have changed patient care. We aimed to investigate the incidence rate of rhegmatogenous retinal detachment (RRD) cases during the COVID-19 lockdown period.

Methods

In this nationwide database study, we identified hospital and clinic admissions of French residents for a first episode of RRD in France from 2017 to the lockdown period in 2020. The monthly hospital incidence rates of RRD procedures per 100 000 inhabitants before, during and after lockdown were computed for the whole country. Finally, we assessed the influence of viral incidence on the RRD incidence rate, comparing two regions with highly contrasting viral penetration.

Results

From January to July, the average monthly national hospital incidence rate of RRD decreased from a mean of 2.59/100 000 inhabitants during 2017–2019 to 1.57/100 000 inhabitants in 2020. Compared with 2019, during the 8-week lockdown period in 2020, a 41.6% decrease in the number of RRD procedures was observed (p<0.001) with the weekly incidence of RRD decreasing from 0.63/100 000 inhabitants in 2019 to 0.36/100 000 inhabitants. During the 4-month post-lockdown period, no increased activity related to postponed procedures was observed. No difference was found in the rate of RRD surgery when comparing two regions with highly contrasting viral incidence.

Conclusion

Containment may have been responsible for a decrease in the number of surgical procedures for RRD, without any compensating post-lockdown activity in France. These results might help increase awareness of the management of RRD emergencies.
Monocyte and neutrophil levels are potentially linked to progression to IPF for patients with indeterminate UIP CT pattern
Authors: Achaiah Andrew , Rathnapala Amila , Pereira Andrea , Bothwell Harriet , Dwivedi Kritica , Barker Rosie , Benamore Rachel , Hoyles Rachel K , Iotchkova Valentina , Ho Ling-Pei
Published: November 2021

Rationale

Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease with poor prognosis. Identifying patients early may allow intervention which could limit progression. The ‘indeterminate for usual interstitial pneumonia’ (iUIP) CT pattern, defined in the 2018 IPF guidelines, could be a precursor to IPF but there is limited data on how patients with iUIP progress over time.

Objective

To evaluate the radiological progression of iUIP and explore factors linked to progression to IPF.

Methods

We performed a retrospective analysis of a lung fibrosis clinic cohort (n=230) seen between 2013 and 2017. Cases with iUIP were identified; first ever CTs for each patient found and categorised as 'non-progressor' or 'progressors' (the latter defined as increase in extent of disease or to 'definite' or 'probable' UIP CT pattern) during their follow-up. Lung function trends, haematological data and patient demographics were examined to explore disease evolution and potential contribution to progression.

Results

48 cases with iUIP CT pattern were identified. Of these, 32 had follow-up CT scans, of which 23 demonstrated progression. 17 patients in this cohort were diagnosed with IPF over a mean (SD) period of 3.9 (±1.9) years. Monocyte (HR: 23, 95% CI: 1.6 to 340, p=0.03) and neutrophil levels (HR: 1.8, 95% CI: 1.3 to 2.3, p<0.001), obtained around the time of initial CT, were associated with progression to IPF using Cox proportional hazard modelling.

Conclusion

53% of our evaluable patients with iUIP progressed to IPF over a mean of 4 years. Monocyte and neutrophil levels at initial CT were significantly associated with progression in disease. These data provide a single-centre analysis of the evolution of patients with iUIP CT pattern, and first signal for potential factors associated with progression to IPF.
In vivo detection of damage in multiple sclerosis cortex and cortical lesions using NODDI
Authors: Preziosa Paolo , Pagani Elisabetta , Bonacchi Raffaello , Cacciaguerra Laura , Falini Andrea , Rocca Maria A , Filippi Massimo
Published: November 2021

Objective

To characterise in vivo the microstructural abnormalities of multiple sclerosis (MS) normal-appearing (NA) cortex and cortical lesions (CLs) and their relations with clinical phenotypes and disability using neurite orientation dispersion and density imaging (NODDI).

Methods

One hundred and seventy-two patients with MS (101 relapsing–remitting multiple sclerosis (RRMS), 71 progressive multiple sclerosis (PMS)) and 62 healthy controls (HCs) underwent a brain 3T MRI. Brain cortex and CLs were segmented from three-dimensional T1-weighted and double inversion recovery sequences. Using NODDI on diffusion-weighted sequence, intracellular volume fraction (ICV_f) and Orientation Dispersion Index (ODI) were assessed in NA cortex and CLs with default or optimised parallel diffusivity for the cortex (D//=1.7 or 1.2 µm2/ms, respectively).

Results

The NA cortex of patients with MS had significantly lower ICV_f versus HCs’ cortex with both D// values (false discovery rate (FDR)-p <0.001). CLs showed significantly decreased ICV_f and ODI versus NA cortex of both HCs and patients with MS with both D// values (FDR-p ≤0.008). Patients with PMS versus RRMS had significantly decreased NA cortex ICV_f and ODI (FDR-p=0.050 and FDR-p=0.032) with only D//=1.7 µm2/ms. No CL microstructural differences were found between MS clinical phenotypes. MS NA cortex ICV_f and ODI were significantly correlated with disease duration, clinical disability, lesion burden and global and regional brain atrophy (r from −0.51 to 0.71, FDR-p from <0.001 to 0.045).

Conclusions

A significant neurite loss occurs in MS NA cortex. CLs show a further neurite density reduction and a reduced ODI suggesting a simplification of neurite complexity. NODDI is relevant to investigate in vivo the heterogeneous pathology affecting the MS cortex.
Switching people who smoke to unfiltered cigarettes: perceptions, addiction and behavioural effects in a cross-over randomised controlled trial
Authors: Pulvers Kim , Tracy LaRee , Novotny Thomas E , Satybaldiyeva Nora , Hunn Adam , Romero Devan R , Dodder Nathan G , Magraner Jose , Oren Eyal
Published: November 2021

Background

Behavioural research is needed to inform a ban on sales of filtered cigarettes that could reduce plastic waste due to discarded filters. This study reports on differences in perceptions, nicotine dependence and behaviour among participants in a cross-over randomised trial of filtered compared with unfiltered cigarettes.

Method

This proof-of-concept study involved 43 people who smoke filtered cigarettes (41.9% women, mean age 36.7 years). Participants were provided 2 weeks’ supply of filtered cigarettes, 2 weeks of the same brand of unfiltered cigarettes and randomly assigned to starting conditions. Measures included the Modified Cigarette Evaluation Questionnaire; single-item cigarette perception questions; Fagerström Test of Nicotine Dependence; 7-day cigarette consumption, urinary cotinine and intention to quit. Analyses included linear and ordinal repeated measures mixed-effects models and paired t-tests.

Results

Filtered cigarettes were perceived as better tasting, more satisfying, more enjoyable, less aversive, less harsh, less potent and less negatively reinforcing than unfiltered cigarettes. Filtered cigarettes were smoked at a higher rate during the trial than unfiltered cigarettes (p<0.05). There was no difference in cotinine, dependence or intention to quit between filtered versus unfiltered cigarette conditions (p>0.05).

Conclusion

People who smoke perceived unfiltered cigarettes as having greater nicotine effects and less desirable sensory effects than filtered cigarettes, and they smoked fewer of these during the trial. Although cotinine, dependence and intention to quit were similar for smoking unfiltered and filtered cigarettes in this small trial, results suggest that banning the sale of filtered cigarettes might make smoking less attractive overall to people who smoke.

Trial registration number

NCT03749876.
Stratigraphic profiling, slip surface detection, and assessment of remolding in sensitive clay landslides using the CPT
Authors: Potvin Joshua J. , Woeller David , Sharp James , Take W. Andy
Published: November 2021

A multi-year cone penetration testing program was conducted at a landslide subject to episodic retrogression in Mud Creek, Ottawa, to assess whether a hand-operated mobile cone penetration test (CPT) could yield new insights into the current degree of remolding under progressive failure in metastable areas of a landslide where conventional tracked rigs are unable to gain access. The mobile CPT rig permitted tests to be performed through the entire thickness of the Champlain Sea deposit at a penetration rate of 0.5 cm/s, with similar results to tests performed at the standard 2 cm/s. Measurements of pore pressure varied considerably with cone size, with the magnitude of pore pressure response decreasing with cone size. The elevation of the slip surface was identified in the tip resistance as the point of transition between the remolded soil above the slip surface and the intact soil below the slip surface, whereas a further 0.5 m of penetration was required to elevate pore pressures to values indicative of the intact soil behaviour. In situ measurements of shear strength of corresponding layers between the intact and remolded profiles to be compared indicated that the soil above the slip surface had remolded to 50% of its fully remolded strength.
Diversity and function of microbial communities in the sand sheath of Agropyron cristatum by metagenomic analysis
Authors: Wang Yuehua , Wu Meixiao , Wang Yijing , Wang Xuefei , Yu Ming , Liu Guixia , Tang Hui
Published: November 2021

The roots of most gramineous plants are surrounded by a variety of microorganisms; however, few studies have focused on the rhizosheath of psammophytes. Therefore, in this study, we used Illumina HiSeq high-throughput sequencing technology to analyse the composition and functional diversity of microbial communities in the rhizosheath of sand-grown Agropyron cristatum (L.) Gaertn. We found that the number of species and functions of microbial communities gradually decreased from the rhizosheath to the bulk soil. Thus, the microbial composition of the rhizosheath was richer and more diverse, and the abundance of bacteria, including Sphingosinicella, Rhizorhabdus, Friedmanniella, Geodermatophilus, Blastococcus, and Oscillatoria, was higher, and the abundance of fungi, such as Mycothermus, was higher. The abundance of CO2 fixation-related genes (acsA, Pcc, and cbbL) in the carbon cycle; NO3–, NO2–, NH2OH, and N2 transformation genes (nrtP, nirS, hao, and nifK) in the nitrogen cycle; soxB/A/C, Sat, and dsrB genes in the sulphur cycle; and 1-phosphate mannitol dehydrogenase (MtlD) gene and polyketide synthase gene (pks) were higher in the rhizosheath than in the bulk soil, as well as genes related to phosphorus uptake in the phosphorus cycle. Our findings showed that the rhizosheath may host the predominant microbial species related to the formation of a rhizosheath.
Dynamo seeds from gravitational torsional anomalies and de Sitter magnetized metrics
Authors: Garcia de Andrade L.C.
Published: November 2021

Recently gravitational and Nieh–Yan (NY) chiral anomalies have been obtained in Riemann–Cartan space–time (L.C. Garcia de Andrade. Class Quantum Grav. 38(6), 065005 (2021). doi: 10.1088/1361-6382/abd25f ), where electrodynamics is encoded in the metric geometry. In this paper we follow the same pathway by obtaining a class of deformed de Sitter metrics in teleparallelism. The existence of the unmagnetized de Sitter metric (DSMM) without axial anomalies is proved. Unified theories à la Einstein, Eddington, and Schroedinger, called modified de Sitter metrics, present some novel features. First, we show that a pure DSMM in T4 does not induce gravitational anomalies. This is a motivation to study modifications of DSMM. NY torsional anomaly in DSMM teleparallel T4 geometry is shown to vanish in all cases. Gravitational non-trivial anomalies are obtained from these metrics. Torsional anomaly, much used in condensed matter physics, does not vanish. From these deformed DSMM, we show that a dynamo equation with torsional gradient sources is valid from class III of the metrics but is torsionless sourced in class II. We show that in the gravitational anomaly of new deformed de Sitter metric one may cancel the gravitational anomaly, by a proper choice of the metric function. The axial anomaly is obtained for some metric deformation as well. A simple deformation leads to the existence of the NY density in the case of DSMM. This would be class IV of DSMM.
Cucumber powdery mildew detection using hyperspectral data
Authors: Fernández Claudio I. , Leblon Brigitte , Wang Jinfei , Haddadi Ata , Wang Keri
Published: November 2021

This study aimed to understand the spectral changes induced by Podosphaera xanthii, the causal agent of powdery mildew, in cucumber leaves from the moment of inoculation until visible symptoms are apparent. A principal component analysis (PCA) was applied to the spectra to assess the spectral separability between healthy and infected leaves. A spectral ratio between infected and healthy leaf spectra was used to determine the best wavelengths for detecting the disease. Additionally, the spectra were used to compute two spectral variables [i.e., the red-well point (RWP) and the red-edge inflexion point (REP)]. A linear support vector machine (SVM) classifier was applied to certain spectral features to assess how well these features can separate the infected leaves from the healthy ones. The PCA showed that a good separability could be achieved from 4 days post-inoculation (DPI). The best model to fit the RWP and REP wavelengths corresponded to a linear model. The linear model had a higher adjusted R2 for the infected leaves than for the healthy leaves. The SVM trained with five first principal components scores achieved an overall accuracy of 95% at 4 DPI (i.e., two days before the visible symptoms). With the RWP and REP parameters, the SVM accuracy increased as a function of the day of inoculation, reaching 89% and 86%, respectively, when symptoms were visible at 6 DPI. Further research must consider a higher number of samples and more temporal repetitions of the experiment.
An Improved Quantum-Inspired Gravitational Search Algorithm to Optimize the Facial Features
Authors: Kumar Yogesh , Kant Verma Shashi , Sharma Sandeep
Published: November 2021

The optimization of the features is vital to effectively detecting facial expressions. This research work has optimized the facial features by employing the improved quantum-inspired gravitation search algorithm (IQI-GSA). The improvement to the quantum-inspired gravitational search algorithm (QIGSA) is conducted to handle the local optima trapping. The QIGSA is the amalgamation of the quantum computing and gravitational search algorithm that owns the overall strong global search ability to handle the optimization problems in comparison with the gravitational search algorithm. In spite of global searching ability, the QIGSA can be trapped in local optima in the later iterations. This work has adapted the IQI-GSA approach to handle the local optima, stochastic characteristics and maintaining balance among the exploration and exploitation. The IQI-GSA is utilized for the optimized features selection from the set of extracted features using the LGBP (a hybrid approach of local binary patterns with the Gabor filter) method. The system performance is analyzed for the application of automated facial expressions recognition with the classification technique of deep convolutional neural network (DCNN). The extensive experimentation evaluation is conducted on the benchmark datasets of Japanese Female Facial Expression (JAFFE), Radboud Faces Database (RaFD) and Karolinska Directed Emotional Faces (KDEF). To determine the effectiveness of the proposed facial expression recognition system, the results are also evaluated for the feature optimization with GSA and QIGSA. The evaluation results clearly demonstrate the outperformed performance of the considered system with IQI-GSA in comparison with GSA, QIGSA and existing techniques available for the experimentation on utilized datasets.
Virtual parity Alexander polynomial
Authors: Dye Heather A. , Kaestner Aaron
Published: November 2021

In this paper, we define the virtual Alexander polynomial following the works of Boden et al. (2016) [Alexander invariants for virtual knots, J. Knot Theory Ramications 24(3) (2015) 1550009] and Kaestner and Kauffman [Parity biquandles, in Knots in Poland. III. Part 1, Banach Center Publications, Vol. 100 (Polish Academy of Science Mathematical Institute, Warsaw, 2014), pp. 131–151]. The properties of this invariant are explored and some examples are computed. In particular, the invariant demonstrates that many virtual knots cannot be unknotted by crossing changes on only odd crossings.
An International Comparison of the COVID-19 Experiences of the Group-of-Seven and the BRICS Countries
Authors: Lau Lawrence J. , Xiong Yanyan
Published: November 2021

The COVID-19 pandemic has been around since December 2019. In this study, the experiences of the Group-of-Seven Countries (G-7 — Canada, France, Germany, Italy, Japan, the UK and the US) and the BRICS Countries (Brazil, Russia, India, China and South Africa) are compared in terms of the numbers of confirmed cases and deaths and the infection and mortality rates. The objective is to see whether such a comparison may yield some insight on how and when the COVID-19 pandemic in the world will finally be under control. The key turns out to be the minimization of secondary and higher-order transmissions of the virus. This requires, first, the practice of good personal hygiene and social distancing on the part of all the residents; second, mandatory rapid testing and exhaustive contact tracing, by the public health authorities; and third, lockdown, quarantine and travel restrictions by the government. The governments of the individual countries must fight the COVID-19 epidemic as if it were a war if they expect to succeed in bringing the epidemic under control in their respective countries.
Digging into big provenance (with SPADE)
Authors: Gehani Ashish , Ahmad Raza , Irshad Hassaan , Zhu Jianqiao , Patel Jignesh
Published: November 2021

A user interface for querying provenance.
What is the cost of living online?
Authors: Greengard Samuel
Published: November 2021

The cost of powering streaming and other rapidly growing online services will not "take down the Internet."
Computational thinking for professionals
Authors: Denning Peter J. , Tedre Matti
Published: November 2021

Professionals practice a form of computational thinking that is significantly more advanced than popular descriptions suggest.
The Hubbard Model
Authors: Arovas Daniel P. , Berg Erez , Kivelson Steven A. , Raghu Srinivas
Published: November 2021

The repulsive Hubbard model has been immensely useful in understanding strongly correlated electron systems and serves as the paradigmatic model of the field. Despite its simplicity, it exhibits a strikingly rich phenomenology reminiscent of that observed in quantum materials. Nevertheless, much of its phase diagram remains controversial. Here, we review a subset of what is known about the Hubbard model based on exact results or controlled approximate solutions in various limits, for which there is a suitable small parameter. Our primary focus is on the ground state properties of the system on various lattices in two spatial dimensions, although both lower and higher dimensions are discussed as well. Finally, we highlight some of the important outstanding open questions.
Electric Field Tuning of Magnetism in Fe3O4/Pt/PZN-PT Heterostructures Prepared by Atomic Layer Deposition
Authors: Zhang Le , Hou Weixiao , Li Tao , Geng Wenping , Mu Jiliang , He Jian , Hou Xiaojuan , Han Shunli , Chou Xiujian
Published: November 2021

Tuning of magnetic properties by electric field (E-field) has received extensive attentions because it is compact, fast, and energy efficient. Here, multiferroic heterostructures of Fe3O4/Pt/PZN-PT (011) (lead zinc niobate-lead titanate single piezoelectric substrate) were in situ fabricated by atomic layer deposition (ALD) using C10H10Fe and O2 as precursors at a low temperature (400 °C) without a subsequent annealing process in H2 atmosphere, which is beneficial in combining with traditional silicon-based semiconductor technology. The E-field dependence of the magnetic anisotropy was studied systematically by ferromagnetic resonance spectroscopy with the larger tunable in-plane magnetic anisotropy of 152 Oe and 318 Oe obtained along the [100] and [0–11] axes, corresponding to the largest magnetoelectric coupling coefficient of 31.8 Oe.cm/kV. Also, the tunable out-of-plane magnetic anisotropy of 35 Oe was obtained along the [011] axis. The outstanding E-field tuning magnetism in the Fe3O4/Pt/PZN-PT heterostructures offers significant possibilities for novel multiferroic devices.
Vascular endothelial adiponectin signaling across the life span
Authors: Cohen Katie E. , Katunaric Boran , SenthilKumar Gopika , McIntosh Jennifer J. , Freed Julie K.
Published: November 2021

Cardiovascular disease risk increases with age regardless of sex. Some of this risk is attributable to alterations in natural hormones throughout the life span. The quintessential example of this being the dramatic increase in cardiovascular disease following the transition to menopause. Plasma levels of adiponectin, a “cardioprotective” adipokine released primarily by adipose tissue and regulated by hormones, also fluctuate throughout one’s life. Plasma adiponectin levels increase with age in both men and women, with higher levels in both pre- and postmenopausal women compared with men. Younger cohorts seem to confer cardioprotective benefits from increased adiponectin levels yet elevated levels in the elderly and those with existing heart disease are associated with poor cardiovascular outcomes. Here, we review the most recent data regarding adiponectin signaling in the vasculature, highlight the differences observed between the sexes, and shed light on the apparent paradox regarding increased cardiovascular disease risk despite rising plasma adiponectin levels over time.
Artificial Intelligence Machine Translation Based on Fuzzy Algorithm
Authors: Li Zhimin
Published: November 2021

In order to study machine translation more in-depth, it is particularly important for the research of artificial intelligence with fuzzy algorithms to convert an unfamiliar language into a mature language. The neural network translation model has been developed in recent years and has achieved rich research results. Aiming at the current lack of accuracy of neural machine translation (NMT), which may cause ambiguity, this paper takes English machine translation as an example and proposes an artificial intelligence machine translation optimization model based on fuzzy theory. On the basis of NMT model translation, first the semantics of English machine translation is classified, a semantic selection model is built, then the analytic hierarchy process is used to determine the semantic order of English machine translation, and the corresponding fault-tolerant operation is carried out to the error-prone errors, weight the semantics, and introduce the fuzzy theory to arrange the English semantics of English machine translation. Finally, the performance of the model is analyzed through specific application experiments. The results show that the accuracy of the machine translation selection permutation model is improved by nearly 4.5% and can reach more than 90% compared with other models, and the timeliness is better than other models, which is improved by nearly 15%, which has obvious advantages.
Transverse Response of an Axially Moving Beam with Intermediate Viscoelastic Support
Authors: Ali Sajid , Khan Sikandar , Jamal Arshad , Horoub Mamon M. , Iqbal Mudassir , Onyelowe Kennedy C.
Published: November 2021

This study presented the transverse vibration of an axially moving beam with an intermediate nonlinear viscoelastic foundation. Hamilton’s principle was used to derive the nonlinear equations of motion. The finite difference and state-space methods transform the partial differential equations into a system of coupled first-order regular differential equations. The numerical modeling procedures are utilized for evaluating the effects of parameters, such as axial translation velocity, flexure rigidities of the beam, damping, and stiffness of the support on the transverse response amplitude and frequencies. It is observed that the dimensionless fundamental frequency and magnitude of axial speed had an inverse correlation. Furthermore, increasing the flexure rigidity of the beam reduced the transverse displacement, but at the same instant, fundamental frequency rises. Vibration amplitude is found to be significantly reduced with higher damping of support. It is also observed that an increase in the foundation damping leads to lower fundamental frequencies, whereas increasing the foundation stiffness results in higher frequencies.
Controlling the PVTOL Aircraft System with an Inverted Pendular Load by means of Nested Saturation Functions and GPI Controller
Authors: Villaseñor Rios Cesar Alejandro , Gutiérrez-Frías Octavio , Aguilar-Ibanez Carlos , Suarez-Castanon Miguel S.
Published: November 2021

This paper presents a control scheme that allows height position regulation and stabilization for an unmanned planar vertical takeoff and landing aircraft system with an inverted pendular load. The proposed controller consists of nested saturations and a generalized proportional integral (GPI). The GPI controls the aircraft height and the roll attitude; the latter is used as the fictitious input control. Next, the system is reduced through linear transformations, expressing it as an integrator chain with a nonlinear perturbation. Finally, the nested saturation function-based controller stabilizes the aircraft’s horizontal position and the pendulum’s angle. Obtaining the control approach was a challenging task due to the underactuated nature of the aircraft, particularly ensuring the pendulum’s upright position. The stability analysis was based on the second method of Lyapunov using a simple candidate function. The numerical simulation confirmed the control strategy’s effectiveness and performance. Additionally, the numerical simulation included a comparison against a PD controller, where its corresponding performance indexes were estimated, revealing that our controller had a better response in the presence of unknown disturbances.
Deep Learning Software Defect Prediction Methods for Cloud Environments Research
Authors: Liu Wenjian , Wang Baoping , Wang Wennan
Published: November 2021

This paper provides an in-depth study and analysis of software defect prediction methods in a cloud environment and uses a deep learning approach to justify software prediction. A cost penalty term is added to the supervised part of the deep ladder network; that is, the misclassification cost of different classes is added to the model. A cost-sensitive deep ladder network-based software defect prediction model is proposed, which effectively mitigates the negative impact of the class imbalance problem on defect prediction. To address the problem of lack or insufficiency of historical data from the same project, a flow learning-based geodesic cross-project software defect prediction method is proposed. Drawing on data information from other projects, a migration learning approach was used to embed the source and target datasets into a Gaussian manifold. The kernel encapsulates the incremental changes between the differences and commonalities between the two domains. To this point, the subspace is the space of two distributional approximations formed by the source and target data transformations, with traditional in-project software defect classifiers used to predict labels. It is found that real-time defect prediction is more practical because it has a smaller amount of code to review; only individual changes need to be reviewed rather than entire files or packages while making it easier for developers to assign fixes to defects. More importantly, this paper combines deep belief network techniques with real-time defect prediction at a fine-grained level and TCA techniques to deal with data imbalance and proposes an improved deep belief network approach for real-time defect prediction, while trying to change the machine learning classifier underlying DBN for different experimental studies, and the results not only validate the effectiveness of using TCA techniques to solve the data imbalance problem but also show that the defect prediction model learned by the improved method in this paper has better prediction performance.
Study of the Therapeutic Effects of Chinese Herbal Decoction Combined with Glucocorticoid in Treating Primary Nephrotic Syndrome in Children
Authors: Hou Xue , Xu Meihua , Li Jie , Li Rui , Zhang Jinzhi , Ju Jing
Published: November 2021

Background. To investigate the clinical effects of Chinese medicine decoction combined with glucocorticoid in treating children with primary nephrotic syndrome. Methods. A total of 70 children with pediatric nephritis nephrotic syndrome treated at Weifang People’s Hospital from January 2019 to December 2019 were randomly allocated to the therapy group and the control group, each with 35 cases. The control group was treated with conventional Western medicine, and the therapy group received Western medicine and Chinese medicine. After 12 weeks of treatment, the therapeutic effect of the two groups was compared. Results. After receiving the treatment, the levels of urine protein (UPro), triglyceride, and cholesterol were significantly decreased in the two groups (

p
<
0.05

), and these levels in the therapy group were much lower than those of the control group (

p
<
0.05

). However, the level of albumin (ALB) was predominantly increased in the two groups after treatment (

p
<
0.05

), and this level in the therapy group was much higher than that of the control group (

p
<
0.05

). Moreover, the immune indicators, coagulation function, and recurrence rate were noticeably improved after treatment (

p
<
0.05

), and the therapy group was better than the control group (

p
<
0.05

). Furthermore, the comparison of renal function indexes, liver function indexes, and blood routine between the two groups showed no statistical significance in the incidence of adverse reactions between the two groups (

p
>
0.05

). Conclusions. For the treatment of refractory nephrotic syndrome in children, based on conventional shock therapy, the addition of traditional Chinese medicine (Liuwei Dihuang pill decoction) remedy can significantly improve the disease symptoms in children and improve the efficacy, and the incidence of adverse reactions is low.
The Cross-Correlations between Foreign Flows in Chinese A-Share Markets and Uncertainties in Home Markets
Authors: Bing Tao , Hu Fei , Ma Hongkun
Published: November 2021

This paper investigates the cross-correlations between the foreign flows in A-share market and the uncertainties of market, economy, and policy in home markets, namely, the VIX index and the US EPU index. By employing the cross-correlation statistics and MF-DCCA method, we find the existence of the cross-correlations between the foreign flows and the VIX index, the foreign flows, and the US EPU index from qualitative and quantitative perspectives, respectively. For the cross-correlation between the foreign flows and VIX, small fluctuations are persistent, while large fluctuations are antipersistent. In contrast, the cross-correlation between the foreign flows and US EPU is antipersistent and steady. These results are robust by dividing the foreign flows into two parts in Shenzhen and Shanghai stock exchanges, respectively, and by shortening the periods to after the implementation of Shenzhen-Hong Kong Stock Connect.