bluuebunny/crossref_metadata_2025 huggingface dataset:
Autonomous Vehicle Path Planning using Q-Learning
Authors: Ibrahim Mohammed M S , Atia Mostafa Rostom , Fakhr MW
Published: December 2021

Path planning is vital in autonomous vehicle technology, from robots to self-driving cars and driverless trucks, it is impossible to navigate without a proper path planning algorithm, various algorithms exist Q-learning being one of them. Q-learning is used extensively in discrete applications as it is effective in finding solutions to these problems. This research investigates the possibility of using Q-learning for solving the local path planning problem with obstacle avoidance. Q-learning is split into two phases, the first being the training phase, and the second being the application phase. During training, Q-learning requires exponentially increasing training time based on the system’s state space. However, when Q-learning is applied it becomes as simple as a lookup table which allows it to run on even the simplest microcontrollers. Two simulations are conducted with varying environments. One to showcase the ability to learn the optimal path, the other to showcase the ability for learning navigation in variable environments. The first simulation was run on a static environment with one obstacle, with enough training episodes, Q-learning could solve the path planning problem with minimal movement steps. The second simulation focuses on a randomized environment, obstacles and the agent’s starting position are randomly chosen at the start of every episode. During testing, Q-learning was able to find a path to the target when a path did exist, as It was possible in certain configurations for the vehicle to be stuck in between obstacles with no feasible path or solution.
Investigating performance of transformer health index in machine learning application using dominant features
Authors: Mohmad Azlan , Ibrahim Shapiai M , Solehin Shamsudin M , Abu Mohd Azlan , Hamid Amirah Abd
Published: December 2021

Transformer Health Index (HI) has become a standard tool for performing transformer health evaluations. Due to economic constraints, the recently published paper focuses on developing various techniques to identify the most dominant features for transformer HI prediction. However, the fundamental problems concerning their input features remain unresolved since most suggested features contradict industry practice. In this paper, the primary objective is to investigate the performance of the transformer HI by developing and utilizing only dominant features following the industry recommendation. The investigated dominant features in this paper using 1) CO2/CO ratio and 2) the Incipient fault for detecting temperature abnormalities, and 3) the Dissipation Factor (DF) for detecting oil contamination. The performance validation is carried out using various machine learning (ML) classifiers. Also, the performance of the ML model is validated based on 10-fold type cross-validation to avoid biases in the experiment. As a result, the proposed Artificial Neural Network (ANN) network utilizing the investigated dominant features following the industry practice has produced the highest average accuracy of 80.09% than others ML techniques as a classifier. Hence, additional studies to complement the investigated dominant features may be considered for the subsequent investigation.
Battery Management System Performance Enhancement using Single Sliding Mode Based Charge Equalization Controller
Authors: Ashraf Ali , Sobaih Abdul-Azim , Nabil Essam
Published: December 2021

In this paper, the study aims to evolve a precision model of a Battery charge equalization controller (BCEC) that manage each cell of a lithium-ion (Li-ion) battery, monitoring a nd balancing by charging a nd discharging a series-connected Li-ion battery with several cells (n) in electric vehicle (E.V.) applications. An intelligent Sliding mode controller is evolved to activate bidirectional cell switches and regulate a chopper circuit’s direct current (DC-DC flyback converter circuit) with PWM generation. To implement a small-scale BCEC, the model consists of individual models of an E.V., cells of Li-ion battery, a fly-back converter, and a single sliding mode controller (SSMC) for charging and discharging are integrated with n series-connected cells of Li-ion-battery. The BCEC output shows that the cells are operated within a safe range, and the difference in the state of charge (SOC) is maintained to be 0.1%. Comparing the developed BCEC with the existing controllers, with the performance, control algorithm, efficiency, power loss, size, and cost.
Enhancement of the Ball Balancing on the Plate using hybrid PD/Machine learning techniques
Authors: Elshamy Mohamed R. , Nabil Essam , Sayed Amged , Abozalam Belal
Published: December 2021

This paper discusses an efficient method to improve the balancing and tracking of the trajectory of the BOPS based on machine learning (ML) algorithm with the Pseudo proportional-derivative (PPD) controller. The proposed controller depends on a ML technique that detect the angle of the servo motor required to correct the ball position on the plate. This paper presents three different ML algorithms for the servo motor angle prediction and achieved higher accuracy which are 99.855%, 99.999%, and 99.998% for support vector regression, decision tree regression, and random forest regression, respectively. The simulation results demonstrate that the proposed strategy has significantly improved the settling time and overshoot of the system. The mathematical formulation can be obtained using the Lagrangian formulation and the servo motor parameter obtained by a practical identification experiment.
The role of fine management techniques in relation to agricultural pollution and farmer income: the case of the fruit industry
Authors: Yuan Bin , Yue Fangzhou , Cui Yuhu , Chen Chao
Published: December 2021

Although agriculture is enjoying booming development it is facing increasingly serious environmental pressures. With increase in the scale of fruit planting, inorganic mineral elements are becoming one of the main sources of non-point pollution. How to achieve sustainable production in agriculture is an issue that needs urgent attention in current rural development. In this paper, based on the micro-production data of peach farmers in 18 prefecture-level provinces, we introduce fine management techniques into the production function to analyze the effects of different techniques and further explore the influence of fine management techniques on fertilizer efficiency. Our findings show that with no change in the degree of investment in fine management techniques the increase in use of chemical fertilizers and pesticides has not only made little contribution to increasing profits but has also resulted in excessive investment in fertilizers that damage the environment. Notably, fine management techniques exerting positive effects on the application efficiency of mineral elements could be an efficient and sustainable way to ease the conflict between environment and profit. However, such techniques are used rarely in practice due to the lack of economic incentives. A brief review of the main measures, such as timely updating of market information, agricultural product branding and socialized services, is offered.
Biophysical feedback of forest canopy height on land surface temperature over contiguous United States
Authors: Zhang Zhijiang , Li Xinxin , Liu Hongguang
Published: December 2021

Forests are considered important in the mitigation of climate change. Biophysical effects of afforestation and deforestation on land surface temperature (LST) have been extensively documented. As a fundamental variable of forest structure, however, few studies have investigated the biophysical feedback of forest canopy height (FCH) changes on LST at large scale. This study is designed to investigate the impact of FCH changes on local land LST and clarify the biophysical processes controlling LST change from 2003 to 2005 over the contiguous United States, based on satellite observations. To this end, one satellite-based FCH product is selected, and the space-for-time approach, together with the energy balance equation, is applied. Results show that for different forest types, namely evergreen forest (EF), deciduous forest (DF), and mixed forest (MF), taller forests present a greater net cooling effect (0.056–0.448 K) than shorter forests at annual scale. The increase in net radiation and sensible heat flux was less than the increase in the latent heat flux when FCH classes converted from shorter to taller, resulting in annual net cooling effects. Furthermore, the cooling effect of EF is stronger than that of DF and MF, whether for tall, medium, or short FCH classes. Multiple regression analysis reveals that the changes in biophysical components can effectively explain the LST change during the growing season. Our findings provide a new insight for forest management decision-making with the purpose of mitigating climate warming.
Modeling of critical strain for dynamic recrystallization of niobium microalloyed steels
Authors: Xing Jun , Ding Hanlin , Zhu Guohui , Li Fan , Li Junliang
Published: December 2021

The critical strain for dynamic recrystallization (DRX) is most important in designing rolling schedules for the refinement of grain size by boundary-induced transformation mechanisms. Modeling of the critical strain for DRX from the stress-strain curves obtained from hot compression was physically built in this paper. The stress-strain behaviour of materials during hot deformation should be a combination of work-hardening and recrystallization softening. Before DRX occurred, the stress-strain behaviours could be described by a constitutive equation in which basic strain hardening and the effect of strain rate and temperature on stress-strain behaviour are included. Once DRX was promoted, obvious deviation between the experimental and calculated stress-strain curves appeared, which denoted the critical strain for DRX. The modeling in this work could be used not only to accurately calculate the critical strain for DRX but also to analyze the dynamic softening behaviours during hot deformation. To validate the calculated results, the stress-strain database was analyzed in the H beam sample deformed at 1000 °C with a strain rate of 0.1/s, and a critical strain of 0.22 was obtained by this novel method as an example. The calculated result is in good agreement with the experimental data obtained by micrographical observations.
Bouncing dynamics of electrostatically actuated NEM switches
Authors: Bognash Mohamed , Asokanthan Samuel
Published: December 2021

The aim of the present research is to understand the bouncing dynamic behavior of nanoelectromechanical (NEM) switches in order to improve switch performance and reliability. It is well known that bouncing can dramatically degrade the switch performance and life; hence, in the present study, the bouncing dynamics of a cantilever-based NEM switch has been studied in detail. To this end, the repulsive van der Waals force is incorporated into a nano-switch model to capture the contact dynamics. Intermolecular forces, surface effects, and gas rarefication effects were also included in the proposed model. The Euler–Bernoulli beam theory and an approximate approach based on Galerkin’s method have been employed to predict transient dynamic responses. In the present study, performance parameters such as initial contact time, permanent contact time, major bounce height, and the number of bounces, were quantified in the presence of interactive system nonlinearities. The performance parameters were used to investigate the influence of surface effects and rarefication effects on the performance of an electrostatically actuated switch. Recommended operating conditions are suggested to avoid excessive bouncing for these types of NEM switches.
A Randomized Clinical Trial Demonstrating Feasibility and Preliminary Efficacy of a Videoconference-Delivered Physical Activity Lifestyle Intervention Among Adolescents With a Congenital Heart Defect
Authors: Jackson Jamie L , Fox Kristen R , Rausch Joseph R , Swenski Taylor N , Neville Steven P , Marousis Noelle C , Korth Christina X , Cua Clifford L , Garg Vidu , Vannatta Kathryn
Published: December 2021

Background

Individuals with congenital heart defects are at increased risk for developing further cardiovascular complications, which can be mitigated by increasing physical activity. Given that positive health behaviors begin declining during older adolescence, it is vital to promote lifestyle changes in this population.

Purpose

The current study aims to (a) determine the feasibility/acceptability of the Congenital Heart Disease Physical Activity Lifestyle (CHD-PAL) intervention among adolescents (ages 15–18) with moderate and complex congenital heart defects, and (b) estimate the preliminary efficacy of CHD-PAL for increasing time spent in moderate-to-vigorous physical activity (MVPA) and cardiorespiratory fitness and decreasing sedentary behavior.

Methods

Eligible participants were randomized into either CHD-PAL (eight 30-min videoconferencing sessions over 20 weeks with an interventionist + Fitbit + exercise prescription) or a comparator (Fitbit + exercise prescription).

Results

Sixty adolescents were randomized (76% recruitment rate; 94% of participants were retained from baseline to follow-up). Most adolescents (73%) and their parents/guardians (76%) reported that the trial was enjoyable. While there was no effect of arm on change in MVPA, sedentary behavior, or cardiorespiratory fitness for the entire sample, among those who engaged in <21 min of MVPA on average at baseline, adolescents in the CHD-PAL intervention had an increase of 16 min/day of MVPA more than comparators (d = 0.90).

Conclusions

The CHD-PAL intervention warrants examination in a larger trial to establish efficacy among those adolescents with a congenital heart defect who engage in <21 min of MVPA/day and should include follow-up assessments to examine effect durability.

Clinical trials registration

NCT03335475.
A compressed variance component mixed model framework for detecting small and linked QTL-by-environment interactions
Authors: Zhou Ya-Hui , Li Guo , Zhang Yuan-Ming
Published: December 2021

Detecting small and linked quantitative trait loci (QTLs) and QTL-by-environment interactions (QEIs) for complex traits is a difficult issue in immortalized F2 and F2:3 design, especially in the era of global climate change and environmental plasticity research. Here we proposed a compressed variance component mixed model. In this model, a parametric vector of QTL genotype and environment combination effects replaced QTL effects, environmental effects and their interaction effects, whereas the combination effect polygenic background replaced the QTL and QEI polygenic backgrounds. Thus, the number of variance components in the mixed model was greatly reduced. The model was incorporated into our genome-wide composite interval mapping (GCIM) to propose GCIM-QEI-random and GCIM-QEI-fixed, respectively, under random and fixed models of genetic effects. First, potentially associated QTLs and QEIs were selected from genome-wide scanning. Then, significant QTLs and QEIs were identified using empirical Bayes and likelihood ratio test. Finally, known and candidate genes around these significant loci were mined. The new methods were validated by a series of simulation studies and real data analyses. Compared with ICIM, GCIM-QEI-random had 29.77 ± 18.20% and 24.33 ± 10.15% higher average power, respectively, in 0.5–3.0% QTL and QEI detection, 43.44 ± 9.53% and 51.47 ± 15.70% higher average power, respectively, in linked QTL and QEI detection, and identified 30 more known genes for four rice yield traits, because GCIM-QEI-random identified more small genes/loci, being 2.69 ± 2.37% for additional genes. GCIM-QEI-random was slightly better than GCIM-QEI-fixed. In addition, the new methods may be extended into backcross and genome-wide association studies. This study provides effective methods for detecting small-effect and linked QTLs and QEIs.
Out-of-the-box deep learning prediction of quantum-mechanical partial charges by graph representation and transfer learning
Authors: Jiang Dejun , Sun Huiyong , Wang Jike , Hsieh Chang-Yu , Li Yuquan , Wu Zhenxing , Cao Dongsheng , Wu Jian , Hou Tingjun
Published: December 2021

Accurate prediction of atomic partial charges with high-level quantum mechanics (QM) methods suffers from high computational cost. Numerous feature-engineered machine learning (ML)-based predictors with favorable computability and reliability have been developed as alternatives. However, extensive expertise effort was needed for feature engineering of atom chemical environment, which may consequently introduce domain bias. In this study, SuperAtomicCharge, a data-driven deep graph learning framework, was proposed to predict three important types of partial charges (i.e. RESP, DDEC4 and DDEC78) derived from high-level QM calculations based on the structures of molecules. SuperAtomicCharge was designed to simultaneously exploit the 2D and 3D structural information of molecules, which was proved to be an effective way to improve the prediction accuracy of the model. Moreover, a simple transfer learning strategy and a multitask learning strategy based on self-supervised descriptors were also employed to further improve the prediction accuracy of the proposed model. Compared with the latest baselines, including one GNN-based predictor and two ML-based predictors, SuperAtomicCharge showed better performance on all the three external test sets and had better usability and portability. Furthermore, the QM partial charges of new molecules predicted by SuperAtomicCharge can be efficiently used in drug design applications such as structure-based virtual screening, where the predicted RESP and DDEC4 charges of new molecules showed more robust scoring and screening power than the commonly used partial charges. Finally, two tools including an online server (http://cadd.zju.edu.cn/deepchargepredictor) and the source code command lines (https://github.com/zjujdj/SuperAtomicCharge) were developed for the easy access of the SuperAtomicCharge services.
The developmentally dynamic microRNA transcriptome of Glossina pallidipes tsetse flies, vectors of animal trypanosomiasis
Authors: Naitore Careen , Villinger Jandouwe , Kibet Caleb K , Kalayou Shewit , Bargul Joel L , Christoffels Alan , Masiga Daniel K
Published: December 2021

MicroRNAs (miRNAs) are single stranded gene regulators of 18–25 bp in length. They play a crucial role in regulating several biological processes in insects. However, the functions of miRNA in Glossina pallidipes, one of the biological vectors of African animal trypanosomosis in sub-Saharan Africa, remain poorly characterized. We used a combination of both molecular biology and bioinformatics techniques to identify miRNA genes at different developmental stages (larvae, pupae, teneral and reproductive unmated adults, gravid females) and sexes of G. pallidipes. We identified 157 mature miRNA genes, including 12 novel miRNAs unique to G. pallidipes. Moreover, we identified 93 miRNA genes that were differentially expressed by sex and/or in specific developmental stages. By combining both miRanda and RNAhybrid algorithms, we identified 5550 of their target genes. Further analyses with the Gene Ontology term and KEGG pathways for these predicted target genes suggested that the miRNAs may be involved in key developmental biological processes. Our results provide the first repository of G. pallidipes miRNAs across developmental stages, some of which appear to play crucial roles in tsetse fly development. Hence, our findings provide a better understanding of tsetse biology and a baseline for exploring miRNA genes in tsetse flies.

Availability and implementation

Raw sequence data are available from NCBI Sequence Read Archives (SRA) under Bioproject accession number PRJNA590626.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.
C5a receptor inhibitor avacopan in immunoglobulin A nephropathy—an open-label pilot study
Authors: Bruchfeld Annette , Magin Hasan , Nachman Patrick , Parikh Samir , Lafayette Richard , Potarca Antonia , Miao Shichang , Bekker Pirow
Published: December 2021

Background

Improvement of proteinuria as a marker for disease activity is associated with a better renal outcome in immunoglobulin A nephropathy (IgAN). Complement is an effector pathway in IgA-mediated kidney injury. Avacopan, a selective C5a receptor inhibitor, has previously shown efficacy in anti-neutrophil cytoplasmic antibody–associated vasculitis. The aim of this study was to evaluate the safety and efficacy of avacopan in patients with IgAN with persistent proteinuria despite a maximally tolerated dose of renin–angiotensin–aldosterone system blockade. The efficacy evaluation was based on the change in proteinuria.

Methods

This open-label pilot trial enrolled adult patients with biopsy-proven IgAN, urinary protein:creatinine ratio (UPCR) >1 g/g creatinine and an estimated glomerular filtration rate (eGFR) >60 mL/min/1.73 m2 or >45 mL/min/1.73 m2 if eGFR has not declined >10 mL/min/1.73 m2 over the previous 24 weeks. If the UPCR remained at >1 g/g creatinine after an 8-week run-in period, patients started avacopan 30 mg twice daily. The primary efficacy endpoint was the change in the slope of the UPCR from the 8-week run-in period to the slope in the 12-week avacopan dosing period.

Results

A total of 10 of 15 screened patients entered the run-in period. Seven patients with a UPCR >1 g/g creatinine received avacopan. Six of seven patients had numerical improvement in the UPCR during the avacopan treatment period, three of whom had a numerical improvement of ∼50% at week 12. At week 24, five of seven patients still showed numerical improvement in the UPCR compared with baseline. The urinary monocyte chemoattractant protein-1:creatinine ratio decreased numerically 30% by week 8, possibly reflecting the anti-inflammatory activity of avacopan. Avacopan was well tolerated. There was one serious adverse event of unstable angina, which was deemed to be unrelated to avacopan.

Conclusions

This short-term pilot study showed an improvement in the slope of the UPCR, with ∼50% improvement in three of seven patients with IgAN. Longer avacopan treatment duration may be indicated for maximal benefit.
Neoadjuvant chemoradiotherapy, chemotherapy, and radiotherapy do not significantly increase the incidence of anastomotic leakage after esophageal cancer surgery: a meta-analysis
Authors: Jin Zixian , Zhang Jian , Chen Dong , Wu Sikai , Xue Penglai , Zhu Kanghao , Xu Congcong , Zhu Chengchu , Zhang Bo
Published: December 2021

This study investigated whether neoadjuvant therapies, such as neoadjuvant chemoradiotherapy (NCRT), neoadjuvant chemotherapy (NCT), and neoadjuvant radiotherapy (NRT), would affect the incidence of anastomotic leakage (AL) after esophageal cancer surgery. Published randomized controlled trials were reviewed, and the incidence of AL after esophageal cancer was statistically analyzed in each study. Meta-analysis was performed using Revman and Stata software. A total of 17 randomized controlled trials with 2874 patients were reviewed showing that, in general, preoperative neoadjuvant therapies were not significant risk factors for AL after esophageal cancer surgery (relative risk [RR] = 0.82, 95% CI = 0.64–1.04). NCRT and NRT did not significantly increase the risk of postoperative AL in patients with esophageal cancer (RR = 0.81, 95% CI = 0.63–1.05; RR = 0.64, 95% CI = 0.14–2.97, respectively). Moreover, NCT has no significant correlation with the occurrence of AL (RR = 1.01, 95% CI = 0.57–1.80). NCRT, NCT, and NRT do not significantly increase the incidence of gastroesophageal AL after esophageal cancer surgery.
Assessing the Economic Viability of the Mechanized Removal of Understory Beech during a Shelterwood Harvest
Authors: Weyrens Josh , Germain Rene
Published: December 2021

Beech bark disease is a pathogenic complex that has been spreading throughout the American beech’s range since the 1800s. A litany of negative consequences have manifested from the infestation of this disease, many of which deteriorate the ecological functions of forestland. This case study sought to analyze the cost structure for removing a recalcitrant beech understory via mechanized shelterwood harvesting. High-resolution data regarding the day-to-day operation of harvesting equipment was collected using daily production journals. Interviews were conducted with the logging company owner and maintenance supervisor to gather additional information required to calculate machine costs, overhead, job specific costs, and trucking costs. The yield from this harvest was 527 metric tonnes of sawtimber and 4,893 tonnes of clean chips. The total harvesting cost equated to $4,651/ha, with the cost attributed to removing beech at $204/ha. Despite the additional cost of beech removal, the logger generated a total profit of $5,965 and a return on investment of 7.5%, allowing us to conclude that mechanized harvesting can be a viable beech removal strategy given the forest stocking and market conditions that are in place.
From Model Organisms to Humans, the Opportunity for More Rigor in Methodologic and Statistical Analysis, Design, and Interpretation of Aging and Senescence Research
Authors: Chusyd Daniella E , Austad Steven N , Brown Andrew W , Chen Xiwei , Dickinson Stephanie L , Ejima Keisuke , Fluharty David , Golzarri-Arroyo Lilian , Holden Richard , Jamshidi-Naeini Yasaman , Landsittel Doug , Lartey Stella , Mannix Edward , Vorland Colby J , Allison David B
Published: December 2021

This review identifies frequent design and analysis errors in aging and senescence research and discusses best practices in study design, statistical methods, analyses, and interpretation. Recommendations are offered for how to avoid these problems. The following issues are addressed: (a) errors in randomization, (b) errors related to testing within-group instead of between-group differences, (c) failing to account for clustering, (d) failing to consider interference effects, (e) standardizing metrics of effect size, (f) maximum life-span testing, (g) testing for effects beyond the mean, (h) tests for power and sample size, (i) compression of morbidity versus survival curve squaring, and (j) other hot topics, including modeling high-dimensional data and complex relationships and assessing model assumptions and biases. We hope that bringing increased awareness of these topics to the scientific community will emphasize the importance of employing sound statistical practices in all aspects of aging and senescence research.
Associations Between Life-Course Socioeconomic Conditions and the Pace of Aging
Authors: Schrempft Stephanie , Belsky Daniel W , Draganski Bogdan , Kliegel Matthias , Vollenweider Peter , Marques-Vidal Pedro , Preisig Martin , Stringhini Silvia
Published: December 2021

Background

Socioeconomic disadvantage is a well-established predictor of morbidity and mortality, and is thought to accelerate the aging process. This study examined associations between life-course socioeconomic conditions and the Pace of Aging, a longitudinal measure of age-related physiological decline.

Methods

Data were drawn from a Swiss population-based cohort of individuals originally recruited between 2003 and 2006, and followed up for 11 years (2 834 women, 2 475 men aged 35–75 years [mean 52]). Pace of Aging was measured using 3 repeated assessments of 12 biomarkers reflecting multiple body systems. Analysis tested associations of socioeconomic conditions with physiological status at baseline and with the Pace of Aging.

Results

Participants with more life-course socioeconomic disadvantage were physiologically older at baseline and experienced faster Pace of Aging. Effect sizes (β) for associations of childhood socioeconomic disadvantage with baseline physiological status ranged from 0.1 to 0.2; for adulthood socioeconomic disadvantage, effect sizes ranged from 0.2 to 0.3. Effect sizes were smaller for associations with the Pace of Aging (<0.05 for childhood disadvantage, 0.05–0.1 for adulthood disadvantage). Those who experienced disadvantaged socioeconomic conditions from childhood to adulthood aged 10% faster over the 11 years of follow-up as compared with those who experienced consistently advantaged socioeconomic conditions. Covariate adjustment for health behaviors attenuated associations, but most remained statistically significant.

Conclusions

Socioeconomic inequalities contribute to a faster Pace of Aging, partly through differences in health behaviors. Intervention to slow aging in at-risk individuals is needed by midlife, before etiology of aging-related diseases become established.
Two-step full waveform inversion of diving and reflected waves with the diffraction-angle-filtering-based scale-separation technique
Authors: Kim Donggeon , Hwang Jongha , Min Dong-Joo , Oh Ju-Won , Alkhalifah Tariq
Published: December 2021

Full waveform inversion (FWI) is a highly non-linear optimization problem that aims to reconstruct high-resolution subsurface structures. The success of FWI in reflection seismology relies on appropriate updates of low-wavenumber background velocity structures, which are generally driven by the diving waves in conventional FWI. On the other hand, the reflected waves mainly contribute to updating high-wavenumber components rather than low-wavenumber components. To extract low-wavenumber information from the reflected waves in addition to the diving waves, we propose a two-step FWI strategy that separates a given model into the reflectivity and background velocity models and then alternately update them using the scale-separation technique based on diffraction-angle filtering (DAF; which was proposed to effectively control wavenumber components of the FWI gradient). Our strategy first inverts the high-wavenumber reflectivity model by suppressing energy at large diffraction angles, which are necessary to compute the reflection wave paths (i.e. the rabbit-ears-shaped kernels) for low-wavenumber updates in the subsequent stage. Then, we extract low-wavenumber components due to the diving (banana-shaped kernels) and reflected waves (rabbit-ears-shaped kernels) from the gradient by suppressing energy at small diffraction angles. Our strategy is similar to reflection waveform inversion (RWI) in that it separates a given model into high- and low-wavenumber components and uses the rabbit-ears-shaped kernels for low-wavenumber updates. The main difference between our strategy and RWI is that our strategy adopts the DAF-based scale-separation technique in the space domain, which makes our algorithm of using both the banana-shaped and rabbit-ears-shaped kernels computationally attractive. By applying our two-step inversion strategy to the synthetic data for the Marmousi-II model and the real ocean-bottom cable data from the North sea, we demonstrate that our method properly reconstructs low-wavenumber structures even if initial models deviate from the true models.
Numerical simulation of the graphite effect on the electrical conductivity of the upper mantle
Authors: Guo Yingxing , Zheng Jun , Zhu Aiyu , Zhu Tao
Published: December 2021

The origin of high-conductivity anomalies in the deep Earth is one of the hot issues in geoscience research. The presence of graphite is a possible reason, but the effects of the volume fraction and geometry of graphite on the high-conductivity anomaly in the upper mantle are still controversial. Based on the possible morphology of graphite in the uppermost mantle, graphite–olivine–orthopyroxene assemblage models are constructed and their conductivities are calculated by a finite-element method. The results show that when graphite is isolated from each other, temperature is the main factor that leads to a change in electrical conductivity. When graphite is in contact with each other, increases in the diameter/thickness ratio (β), orientation arrangement along the direction of conduction, and a mixture of powdered and disc-shaped graphite can significantly cause an increase in electrical conductivity. We found that a threshold value of graphite content exists at which the model conductivity suddenly increases. The threshold decreases significantly with increasing β. A model with β larger than 25 could explain the high-conductivity anomaly in the upper mantle.
Neutralizing Response Against SARS-CoV-2 Variants 8 Months After BNT162b2 Vaccination in Naive and COVID-19–Convalescent Individuals
Authors: Luczkowiak Joanna , Labiod Nuria , Rivas Gonzalo , Rolo Marta , Lasala Fátima , Lora-Tamayo Jaime , Mancheno-Losa Mikel , Rial-Crestelo David , Pérez-Rivilla Alfredo , Folgueira María Dolores , Delgado Rafael
Published: December 2021

We have investigated the evolution of the neutralizing response against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants at 8 months after Pfizer-BNT162b2 vaccination in coronavirus disease 2019 (COVID-19)–naive (n = 21) and COVID-19–convalescent (n = 21) individuals. Neutralizing levels declined for all variants (range 2- to 3.7-fold). Eight months after vaccination, a significant proportion (4/21) of naive individuals lacked detectable neutralizing activity against the highly transmissible SARS-CoV-2 delta variant. In the convalescent group, the impressive high initial humoral response resulted in detectable neutralizing antibody levels against all variants throughout this period.
Nosological Diagnosis, Theories of Categorization, and Argumentations by Analogy
Authors: Gagliardi Francesco
Published: December 2021

The nosological diagnosis is a particular type of nontheoretical diagnosis consisting of identifying the disease that afflicts the patient without explaining the underlying etiopathological mechanisms. Its origins are within the essentialist point of view on the nature of diseases, which dates back at least to 18th-century taxonomy studies. In this article, we propose a model of nosological diagnosis as a two-phase process composed of the categorization of inductive inferences and argumentations by analogy. In the inductive phase, disease entities are identified by means of typicality-based categorization processes, and meaningful clinical samples are learned (abstract clinical cases, i.e., syndromes and actual cases); in the subsequent phase, those samples are used as the bases of argumentations by analogy to obtain a diagnosis for a given patient. This model extends the prototype resemblance theory of disease including also the exemplar theory proposed in cognitive science and, moreover, it frames the clinical activity of nosological diagnosis and how it can be explained within the theory of argumentation. According to it, diagnosis based on the recognition of a typical syndrome is explained in terms of the prototype theory of categorization and the antisymmetrical argumentation by analogy, while diagnosis based on a comparison with a previous clinical case is explained by the exemplar theory of categorization and by the symmetrical argumentation by analogy.
Engagement with risk-exposed neighbours: the track record of nuclear newbuild and newcomer states
Authors: Yao Lixia , Andrews-Speed Philip
Published: December 2021

Several international norms oblige governments of countries planning to build nuclear installations to proactively consult potentially affected countries in a timely manner. These norms arise from customary international law, the Convention on Nuclear Safety (CNS), the guidelines of the International Atomic Energy Agency (IAEA) and regional treaties and international environmental law. This study has examined 15 examples to assess (i) the extent to which such consultation has taken place and (ii) the effectiveness of measures taken by potentially affected countries in those cases where prior consultation had not taken place. Examples range in vintage from the 1960s to the present day and include both newbuild and newcomer countries. In only 3 of these 15 cases, prior consultation had taken place and all the involved nations had good bilateral relations and/or common interests in the project. Nevertheless, disputes arose later in two of these cases. In the other examples, the degree of success of the potentially affected state in changing the behaviour of the newbuild or newcomer state depended on a number of factors; for example, the state of bilateral relations, the availability of a regional organization to resolve the dispute, the validity of the arguments of both parties and the goodwill of the newbuild or newcomer state. Whilst the CNS and the actions of the IAEA have raised nuclear safety standards substantially over recent decades, the unwillingness of most nations to adhere to the obligation to consult would seem to be a significant weakness.
Computed Tomography of the Chest as a Screening Tool for Low Bone Mineral Density
Authors: Vanier Alan T , Colantonio Donald , Saxena Sameer K , Rodkey Daniel , Wagner Scott
Published: December 2021

Introduction

Computed tomography (CT) Hounsfield units (HU) recently emerged as a promising screening tool for low bone mineral density (BMD). We hypothesized that CT HU measurements of the thoracic spine would significantly and positively correlate with dual X-ray absorptiometry (DXA) BMD scans of the femoral neck.

Materials and methods

The study included patients with DXA scans and thoracic CT scans at the Walter Reed National Military Medical Center. One author, blinded to the DXA scans, measured HU from the cancellous bone in T4 vertebrae. Another author statistically compared femoral neck DXA T-scores to the CT HU measurements.

Results

The study included 145 patients with CT scans and femoral neck DXAs. The osteoporotic and osteopenic groups had a significant difference in HU measurements compared to the normal group within the study (P < .0001 and .002, respectively). A low BMD screening value of 231 HU provided a sensitivity of 90.1% and negative predictive value of 85.7%.

Conclusion

Thoracic vertebrae HU measurements correlate with a low BMD of the femoral neck as determined by DXA T-scores. A high sensitivity and negative predictive value was achieved with a screening value of 231 HU. Utilization of chest or thoracic spine CT imaging as a screening method provides a quick and available screening tool for assessing low BMD in patients with these scans.

Level of Evidence: III (Diagnostic)
Preparing the next gravitational million-body simulations: evolution of single and binary stars in
nbody6++gpu
,
mocca
, and
mcluster
Authors: Kamlah A W H , Leveque A , Spurzem R , Arca Sedda M , Askar A , Banerjee S , Berczik P , Giersz M , Hurley J , Belloni D , Kühmichel L , Wang L
Published: December 2021

We present the implementation of updated stellar evolution recipes in the codes nbody6++gpu, mocca, and mcluster. We test them through numerical simulations of star clusters containing 1.1 × 105 stars (with 2.0 × 104 in primordial hard binaries) performing high-resolution direct N-body (nbody6++gpu) and Monte Carlo (mocca) simulations to an age of 10 Gyr. We compare models implementing either delayed or core-collapse supernovae mechanisms, a different mass ratio distribution for binaries, and white dwarf (WD) natal kicks enabled/disabled. Compared to nbody6++gpu, the mocca models appear to be denser, with a larger scatter in the remnant masses, and a lower binary fraction on average. The mocca models produce more black holes (BHs) and helium WDs, while nbody6++gpu models are characterized by a much larger amount of WD–WD binaries. The remnant kick velocity and escape speed distributions are similar for the BHs and neutron stars (NSs), and some NSs formed via electron-capture supernovae, accretion-induced collapse, or merger-induced collapse escape the cluster in all simulations. The escape speed distributions for the WDs, on the other hand, are very dissimilar. We categorize the stellar evolution recipes available in nbody6++gpu into four levels: the one implemented in previous nbody6++gpu and mocca versions (level A), state-of-the-art prescriptions (level B), some in a testing phase (level C), and those that will be added in future versions of our codes.
Investigation of the orbital period and mass relations for W UMa-type contact systems
Authors: Poro A , Sarabi S , Zamanpour S , Fotouhi S , Davoudi F , Khakpash S , Salehian S Ranjbar , Madayen T , Foroutanfar A , Bakhshi E , Mahdavi N S , Alicavus F , Farahani A Mazidabadi , Sabbaghian G , Hosseini R S , Aryaeefar A , Hemati M
Published: December 2021

New relationships between the orbital period and some parameters of W Ursae Majoris (W UMa)-type systems are presented in this study. To investigate the relationships, we calculated the absolute parameters of a sample of 118 systems. For this purpose, we used the parallax values obtained from the Gaia Early Data Release 3 star catalogue for more precise calculations. The other required parameters, including the light-curve solutions and the orbital period, were derived from previous research. For some relationships, we added 86 systems from another study with an orbital period of less than 0.6 d to our sample, allowing us to increase the number of systems to 204. Therefore, the mass (M) values of each component along with all the other absolute parameters were recalculated for these contact systems. We used the Markov chain Monte Carlo approach in order to gain the new orbital period–mass relations (P–M) per component, and added the temperature (T) to the process to acquire the new orbital period–temperature (P–T1) relation. We presented the orbital period behaviour in terms of log(g) by new relations for each component. We have also obtained a model between the orbital period, the mass of the primary component, and temperature (P–M1–T1) using the artificial neural network method. Additionally, we present a model for the relationship between the orbital period and the mass ratio (P–q) by fitting a multilayer perceptron regression model to a sample of the data collected from the literature.
XMM–Newton detection of soft time lags in the TDE candidate AT 2018fyk
Authors: Zhang Wenda
Published: December 2021

In this letter, we report a tentative detection of soft time lags (i.e. variability of softer photons lags behind the variability of harder photons) in one XMM–Newton observation of the tidal disruption event (TDE) candidate AT 2018fyk while the source was in the hard spectral state. The lags are detected at $6.51\times 10^{-5}~\rm Hz$. The amplitude of the lags with respect to 0.5 − 1 keV monotonically decreases with the photon energy, from $\sim 1200~\rm s$ at 0.3 − 0.5 keV to $\sim -4200~\rm s$ at 3 − 5 keV (in our convention, a positive lag means lagging behind the reference band). We find that the amplitude is proportional to the logarithm of the energy separation between the examined band and the reference band. The energy-dependent covariance spectrum indicates that the correlated variability is more likely to be associated with the non-thermal radiation. The soft lags are difficult to reconcile with the reverberation scenario that are used to explain the soft lags in active galactic nuclei. On the other hand, the observed soft lags are consistent with the picture that the soft X-rays are down-scattered hard X-rays by the outflow as predicted by ‘unification’ models of TDEs.
Influencing Perceptions of Harm of Waterpipe Tobacco Smoking Among One Member of Couples Who Use Waterpipe
Authors: Lipkus Isaac M , Sanders Camilla , Mays Darren
Published: December 2021

Introduction

Waterpipe tobacco smoking (WTS) often occurs socially, increasing health risks for the smoker and others through secondhand smoke effects. While messages on WTS harms enhance perceived risks for self, whether these messages elevate perceived risks for others, such as one’s romantic partner who engages in WTS, is unclear. We tested this idea by surveying one member of dual-smoking couples who engages in WTS.

Aims and Methods

As part of an online study, we enrolled adults ages 18–30 who engaged in WTS and were in a committed relationship of at least 6 months whose partner engaged in WTS. Participants were randomized to a control arm or to one of two arms consisting of watching a brief video on health harms or overcoming myths about WTS, respectively. Outcomes were perceived harms and measures of desire and probability of quitting for self and partner.

Results

Participants (N = 238) who watched either video, compared with participants who did not watch a video, reported greater perceived health risks for self and partner and that their own WTS harmed their partner. Participants who watched either video reported a greater desire to quit for themselves, perceived that their partner had a greater desire to quit, and reported a higher likelihood of quitting together in the next 6 months.

Conclusions

Brief videos containing risk-based messaging increase young adult waterpipe tobacco smokers’ perceived harms and desire to quit for self and partner. This can be a useful strategy to motivate cessation in couples who engage in WTS.

Implications

This study shows for the first time that at least among one member of dual-smoking couples who engages in WTS, brief videos on harms of WTS influences perceived harms and motivation to quit for the self and one’s partner. This can be a useful strategy to promote cessation.
Classification of EEG Signals Reveals a Focal Aftereffect of 10 Hz Motor Cortex Transcranial Alternating Current Stimulation
Authors: Tzvi Elinor , Alizadeh Jalal , Schubert Christine , Classen Joseph
Published: December 2021

Transcranial alternating current stimulation (tACS) modulates oscillations in a frequency- and location-specific manner and affects cognitive and motor functions. This effect appears during stimulation as well as “offline,” following stimulation, presumably reflecting neuroplasticity. Whether tACS produces long-lasting aftereffects that are physiologically meaningful, is still of current debate. Thus, for tACS to serve as a reliable method for modulating activity within neural networks, it is important to first establish whether “offline” aftereffects are robust and reliable. In this study, we employed a novel machine-learning approach to detect signatures of neuroplasticity following 10-Hz tACS to two critical nodes of the motor network: left motor cortex (lMC) and right cerebellum (rCB). To this end, we trained a classifier to distinguish between signals following lMC-tACS, rCB-tACS, and sham. Our results demonstrate better classification of electroencephalography (EEG) signals in both theta (θ, 4–8 Hz) and alpha (α, 8–13 Hz) frequency bands to lMC-tACS compared with rCB-tACS/sham, at lMC-tACS stimulation location. Source reconstruction allocated these effects to premotor cortex. Stronger correlation between classification accuracies in θ and α in lMC-tACS suggested an association between θ and α efffects. Together these results suggest that EEG signals over premotor cortex contains unique signatures of neuroplasticity following 10-Hz motor cortex tACS.