bluuebunny/crossref_metadata_2025 huggingface dataset:
Two-Dimensional Transient Heat Transfer Model for High-Temperature Laser-Scanning Confocal Microscopy
Authors: Liyanage Dasith , Moon Suk-Chun , Jayasekare Ajith S. , Basu Abheek , Du Toit Madeleine , Dippenaar Rian
Published: September 2021

High-temperature laser-scanning confocal microscopy (HT-LSCM) has proven to be an excellent experimental technique through in situ observations of high temperature phase transformation to study kinetics and morphology using thin disk steel specimens. A 1.0 kW halogen lamp within the elliptical cavity of the HT-LSCM furnace radiates heat and imposes a nonlinear temperature profile across the radius of the steel sample. When exposed at the solid/liquid interface, this local temperature profile determines the kinetics of solidification and phase transformation morphology. A two-dimensional numerical heat transfer model for both isothermal and transient conditions is developed for a concentrically solidifying sample. The model can accommodate solid/liquid interface velocity as an input parameter under concentric solidification with cooling rates up to 100 K/min. The model is validated against a commercial finite element analysis software package, strand7, and optimized with experimental data obtained under near-to equilibrium conditions. The validated model can then be used to define the temperature landscape under transient heat transfer conditions.
Triggering Vortex Shedding for the Freestream Flow of Nanofluids Around Bluff Objects
Authors: Garai Sourav , Chatterjee Dipankar , Mondal Bittagopal
Published: September 2021

The freestream flow around a bluff object shows steady symmetric nature in the low Reynolds number laminar regime. However, when the Reynolds number increases to a critical value, the flow shows unsteadiness with alternate shedding of vortices. We show here numerically that the vortex shedding could be initiated for flow of a nanofluid over a bluff object even when the Reynolds number is lying in the steady regime (10≤Re≤30). Cu–H2O and Ag–H2O nanofluids are used and the volume fractions of Cu and Ag nanoparticles are gradually increased. At some critical values of the volume fractions, the flow shows unsteadiness with vortex shedding. The critical solid volume fraction is estimated from the convective stability analysis following the extended Landau model. The shedding phenomenon is established through contour plots, phase diagrams, and analysis of the time signals of lift coefficient. The critical volume fractions for the two different nanofluids for transition of steady to unsteady flow over circular and square-shaped bluff objects are observed to decrease with increasing Reynolds number.
Elasto-Hydrodynamic Model of Hybrid Journal Bearings for Aero-Engine Gear Fuel Pump Applications
Authors: Tacconi Jacopo , Shahpar Shahrokh , King Andrew , Olufeagba Johannes Paulus , Khan Raymarn , Sant Ian , Yates Martin
Published: September 2021

Gear pumps are largely employed in aero-engine fuel systems to provide the combustor with fuel at adequate pressure and flow rate. The radial load applied on the gears, as a consequence of the pump pressure rise, is entirely supported by the hybrid journal bearings. Lubrication of these is accomplished using low viscosity aviation fuel, which makes the design and analysis of journal bearings particularly challenging. A numerical model has been developed to support the analysis and future design of hybrid journal bearings for fuel pump applications. The primary objective of the tool is to characterise the equilibrium position of the journal during steady-state operation at part and full load, where the resultant elastic displacements are more significantly affecting the pressure distribution of the lubrication film. The developed method effectively combines Elrod's cavitation algorithm with the dimensionless pressure definition known as the Vogelpohl parameter, resulting in a simple and robust methodology to characterise the pressure distribution within the lubricant for different bearing designs and operating conditions. Six different multidimensional root-finding solvers have been implemented and their performance evaluated against robustness, accuracy and computational speed requirements. Newton-Raphson based methods have shown promising trade-offs for the problem at hand. Validation of the tool has been made comparing experimental film thickness measurements, performed on a fuel pump from a modern turbofan engine, with predicted data from the numerical model.
Loads on a Jacket-Supported Wind Turbine During Hurricane Sandy Simulation
Authors: Kim Eungsoo , Manuel Lance
Published: September 2021

The dynamic response of a jacket-supported offshore wind turbine under coupled wind, wave, and current fields during Hurricane Sandy is the subject of this study. To illustrate the detailed procedure related to the response evaluation of a 5-MW offshore wind turbine with a jacket support structure, we consider a single site where the water depth is 50 m. Loads are computed using two simulation tools, fast and abaqus, with partial coupling. Aerodynamic loads on the turbine rotor are first evaluated using a wind turbine model in fast with a fixed base; then, these rotor aerodynamic loads are applied as point loads at the top of a model of a tower that is supported by a jacket structure in abaqus. On the basis of stochastic simulations, we discuss the applicability of the abaqus jacket modeling and describe the characteristics and comparisons of the aerodynamic and hydrodynamic effects on loads on the jacket members. Details related to the structural model and soil–pile interaction model employed in the analyses are also discussed.
The Development of a Partially Averaged Navier–Stokes KSKL Model
Authors: Klapwijk Maarten , Lloyd Thomas , Vaz Guilherme
Published: September 2021

A new partially averaged Navier–Stokes (PANS) closure is derived based on the k−kL (KSKL) model. The aim of this new model is to incorporate the desirable features of the KSKL model, compared to the k−ω shear stress transport model, into the PANS framework. These features include reduced eddy-viscosity levels, a lower dependency on the cell height at the wall, well-defined boundary conditions, and improved iterative convergence. As well as the new model derivation, the paper demonstrates that these desirable features are indeed maintained, for a range of modeled-to-total turbulence kinetic energy ratios (fk), and even for multiphase flow.
Kinetics of the low-pressure chemical vapor deposited tungsten nitride process using tungsten hexafluoride and ammonia precursors
Authors: Hulkko Johan G. , Böőr Katalin , Qiu Ren , Bäcke Olof , Boman Mats , Halvarsson Mats , Lindahl Erik
Published: September 2021

Tungsten nitride (WNx) is a hard refractory material with low electrical resistance that can be deposited using multiple methods. This study focuses on the microstructrual development of low pressure chemical vapor deposition grown WNx coatings. Also, the growth kinetics is studied and discussed in terms of the resulting microstructures. Samples of WNx were deposited using WF6, NH3, and Ar at 592–887 K in a hot-wall reactor with variable gas mixture compositions (NH3:WF6 = 0.5–25). The coatings were nitrogen-rich (x ∼ 1.65) and oxygen-free as determined by time-of-flight-elastic recoil detection analysis. X-ray diffraction showed that the coatings transformed from being amorphous to crystallizing as β-W2N at 641–690 K. The morphologies changed with deposition temperature. Being very fine grained and nodular at deposition temperatures 740 K and below, increasing the deposition temperature to 789 K while employing a NH3:WF6 molar ratio of 1, large disc-shaped protrusions were formed. When increasing the NH3:WF6 molar ratio to 25, striped facets became increasingly dominant. Investigating the latter by transmission electron microscopy, a microstructure of smaller ridges formed by twinning, oriented as <211> in the out-of-plane direction, was revealed across the facet surfaces. Transmission Kikuchi diffraction confirmed that <211> was the texture of these coatings. The partial reaction order of WF6 and NH3 at 740 K was determined to be close to 1/6 and 1/2, respectively. The apparent activation energy ranged from 82 to 12 kJ/mol corresponding to deposition temperatures from 592 to 887 K.
Improving the abrasive wear resistance of biomass briquetting machine components using cathodic arc physical vapor deposition coatings: A comparative study
Authors: Miryalkar Pooja , Chavitlo Sekhar , Tandekar Nitin , Valleti Krishna
Published: September 2021

Abrasive wear of biomass briquetting machine components, such as shedder blades, hammer blades, dies and rams, etc., is the primary limiting factor that affects the economic viability of the biomass briquetting process. In order to overcome this issue, attempts were undertaken in this work to evaluate the applicability of commercially well-established Ti-based metal nitride wear-resistant coatings to reduce abrasive wear. The TiN, TiCrN, and TiAlN coatings were deposited on D3 hard steel using the cathodic arc physical vapor deposition technique. A dry sand rubber wheel tester was used to assess the abrasive wear characteristics of the coatings and bare D3 hard steel. Coating properties, such as hardness, adhesion strength, surface roughness, and residual stress, were also evaluated. The results demonstrated that coating defects (microdroplets and pull-outs/craters), coating hardness, and elastic modulus play a major role in abrasive wear performance. The TiCrN coating has shown the highest abrasion resistance due to high H3/E2 ratio compared to other coatings. The abrasive wear mechanism of the TiAlN coating majorly followed coating spallation due to high compressive residual stress and low adhesion strength. The TiN coating exhibited the worst abrasive wear resistance among the three coatings due to localized ploughing at coating microdroplet and crater sites. Therefore, based on the results, the TiCrN coating has the potential to enhance the service life of briquetting machine components by orders of magnitude compared to uncoated ones
Mental Health Literacy and Confidence in a Sample of Student Athletic Therapists
Authors: Sullivan Philip , Tennant Laura
Published: September 2021

Intercollegiate student-athletes appear to be a high-risk population with respect to mental health. Student athletic therapists are one of the groups with whom these athletes may be comfortable disclosing concerns. The current study investigated the relationship between mental health literacy and mental health referral efficacy in a sample of intercollegiate student therapists. One hundred and eleven student athletic therapists (81 female, 29 male, 1 nondiscloure) competed a revised version of the multicomponent mental health literacy measure and a four-item measure of mental health referral efficacy. T tests revealed statistically significant differences in mental health literacy by gender and personal history, and a multiple linear regression revealed a significant model predicting referral efficacy from mental health literacy. There are several implications of these results, particularly when working with a high-risk population of student-athletes.
Targeting lysophospholipid acid receptor 1 and ROCK kinases promotes antiviral innate immunity
Authors: Zhang Chi , Li Weiyun , Lei Xiaobo , Xie Zhenfei , Qi Linlin , Wang Hui , Xiao Xia , Xiao Jun , Zheng Yuxiao , Dong Chen , Zheng Xin , Chen Shiyang , Chen Jianfeng , Sun Bing , Qin Jun , Zhai Qiwei , Li Jinsong , Wei Bin , Wang Jianwei , Wang Hongyan
Published: September 2021

Inhibition of LPA1/ROCK enhances IFN-I/III production in multiple cell types against virus infection.
High- and low-latitude forcings drive Atacama Desert rainfall variations over the past 16,000 years
Authors: González-Pinilla Francisco J. , Latorre Claudio , Rojas Maisa , Houston John , Rocuant M. Ignacia , Maldonado Antonio , Santoro Calogero M. , Quade Jay , Betancourt Julio L.
Published: September 2021

Variations in rodent fecal pellet sizes from fossil middens reveal past rainfall episodes in the central Atacama Desert.
KIR3DS1 directs NK cell–mediated protection against human adenovirus infections
Authors: Jung Johannes M. , Ching Wilhelm , Baumdick Martin E. , Hofmann-Sieber Helga , Bosse Jens B. , Koyro Tobias , Möller Kimberly J. , Wegner Lucy , Niehrs Annika , Russu Kristina , Ohms Mareike , Zhang Wenli , Ehrhardt Anja , Duisters Kevin , Spierings Eric , Hölzemer Angelique , Körner Christian , Jansen Suze A. , Peine Sven , Königs Ingo , Lütgehetmann Marc , Perez Daniel , Reinshagen Konrad , Lindemans Caroline A. , Altfeld Marcus , Belderbos Mirjam , Dobner Thomas , Bunders Madeleine J.
Published: September 2021

KIR3DS1
+
NK cells execute enhanced killing of adenovirus-infected cells, providing protection against severe infection in immunocompromised hosts.
Exercise training in paediatric congenital heart disease: fit for purpose?
Authors: Amir Nurul Hidayah , Dorobantu Dan M , Wadey Curtis A , Caputo Massimo , Stuart A. Graham , Pieles Guido E , Williams Craig A
Published: September 2021

Exercise and physical activity (PA) have been shown to be effective, safe and feasible in both healthy children and children with congenital heart disease (CHD). However, implementing exercise training as an intervention is still not routine in children with CHD despite considerable evidence of health benefits and well-being. Understanding how children with CHD can safely participate in exercise can boost participation in PA and subsequently reduce inactivity-related diseases. Home-based exercise intervention, with the use of personal wearable activity trackers, and high-intensity interval training have been beneficial in adults’ cardiac rehabilitation programmes. However, these remain underutilised in paediatric care. Therefore, the aims of this narrative review were to synthesise prescribed exercise interventions in children with CHD, identify possible limitation to exercise training prescription and provide an overview on how to best integrate exercise intervention effectively for this population into daily practice.
Categorising high-cost high-need children and young people
Authors: Punjabi Nikita , Marszalek Kathryn , Beaney Thomas , Shah Rakhee , Nicholls Dasha , Deeny Sarah , Hargreaves Dougal
Published: September 2021

Objectives

To describe the characteristics of high-cost high-need children and young people (CYP) (0–24 years) in England.

Methods

Retrospective observational study using data from the Clinical Practice Research Database linked to Hospital Episode Statistics in 2014/2015 and 2015/2016. Healthcare utilisation of primary and secondary care services were calculated, and costs were estimated using Healthcare Resource Group for secondary care and Personal Social Services Research Unit for primary care. High-cost high-need CYP were defined as the top 5% of users by cost.

Results

3891 of 73 392 CYP made up the top 5% that were classified as high-cost high-need, and this group accounted for 54% of total annual costs. In this population, 7.3% were males <5 years and 11.0% were females 20–24 years. Inpatient care (acute) accounted for 63% of known spending in high-cost high-need patients. Total mean monthly cost per patient was 22.7 times greater in the high-cost high-need group compared with all other patients (£4417 vs £195). 29% of CYP in the high-cost high-need group in 2014/2015 were also classified as high-cost high-need in the following year.

Conclusions

These findings indicate the importance of further understanding and anticipating trends in CYP health spending to optimise care, reduce costs and inform new models of care. This includes integrated services, a further look into societal factors in reducing health inequalities and a particular focus of mental health services, the demand of which increases with age.
Willingness of tobacco farmers to accept compensation for tobacco crop substitution in Lichuan City, China
Authors: Wan Xinyu , Jin Jianjun , Ran Shenghong
Published: September 2021

Objective

This study, conducted in China, explores tobacco farmers’ willingness to accept (WTA) compensation for tobacco crop substitution.

Methods

The contingent valuation method was used to elicit farmers’ WTA compensation. A face-to-face survey was conducted with 280 tobacco farmers in Lichuan City, China. The standard logit regressions were used to identify the factors that influence farmers’ WTA.

Results

Without compensation, most of the respondents were unwilling to implement tobacco crop substitution. However, if the government provided compensation, the proportion of respondents’ willingness for substitution increased to 86.7%. Male tobacco farmers are more likely to accept a given compensation value than female farmers. Older tobacco farmers have a higher probability of accepting compensation. The number of farmers engaged in tobacco growing in a family is negatively associated with the probability of accepting a given compensation amount. Tobacco farmers with greater confidence in the expected benefits of tobacco crop substitution tend to be more willing to accept compensation. The mean WTA estimate was achieved as US$2020.35/ha/year.

Conclusions

If appropriate compensation is provided for tobacco farmers, there is a potential to implement the tobacco crop substitution policy in the study area.
Probing dark matter clumps, strings and domain walls with gravitational wave detectors
Authors: Jaeckel Joerg , Schenk Sebastian , Spannowsky Michael
Published: September 2021

Gravitational wave astronomy has recently emerged as a new way to study our Universe. In this work, we survey the potential of gravitational wave interferometers to detect macroscopic astrophysical objects comprising the dark matter. Starting from the well-known case of clumps we expand to cosmic strings and domain walls. We also consider the sensitivity to measure the dark matter power spectrum on small scales. Our analysis is based on the fact that these objects, when traversing the vicinity of the detector, will exert a gravitational pull on each node of the interferometer, in turn leading to a differential acceleration and corresponding Doppler signal, that can be measured. As a prototypical example of a gravitational wave interferometer, we consider signals induced at LISA. We further extrapolate our results to gravitational wave experiments sensitive in other frequency bands, including ground-based interferometers, such as LIGO, and pulsar timing arrays, e.g. ones based on the Square Kilometer Array. Assuming moderate sensitivity improvements beyond the current designs, clumps, strings and domain walls may be within reach of these experiments.
Evolution of virial clouds-I: from surface of last scattering up to the formation of population-III stars
Authors: Tahir Noraiz , Qadir Asghar , Sakhi Muhammad , De Paolis Francesco
Published: September 2021

The analysis of WMAP and Planck CMB data has shown the presence of temperature asymmetries towards the halos of several galaxies, which is probably due to the rotation of clouds present in these halos about the rotational axis of the galaxies. It had been proposed that these are hydrogen clouds that should be in equilibrium with the CMB. However, standard theory did not allow equilibrium of such clouds at the very low CMB temperature, but it was recently shown that the equilibrium could be stable. This still does not prove that the cloud concentration and that the observed temperature asymmetry is due to clouds in equilibrium with the CMB. To investigate the matter further, it would be necessary to trace the evolution of such clouds, which we call “virial clouds”, from their formation epoch to the present, so as to confront the model with the observational data. The task is to be done in two steps: (1) from the cloud formation before the formation of first generation of stars; (2) from that time to the present. In this paper we deal with the first step leaving the second one to a subsequent analysis.
ℤ3-actions on Horikawa surfaces
Authors: Lorenzo Vicente
Published: September 2021

Minimal algebraic surfaces of general type [Formula: see text] such that [Formula: see text] are called Horikawa surfaces. In this note, [Formula: see text]-actions on Horikawa surfaces are studied. The main result states that given an admissible pair [Formula: see text] such that [Formula: see text], all the connected components of Gieseker’s moduli space [Formula: see text] contain surfaces admitting a [Formula: see text]-action. On the other hand, the examples considered allow us to produce normal stable surfaces that do not admit a [Formula: see text]-Gorenstein smoothing. This is illustrated by constructing non-smoothable normal surfaces in the KSBA-compactification [Formula: see text] of Gieseker’s moduli space [Formula: see text] for every admissible pair [Formula: see text] such that [Formula: see text]. Furthermore, the surfaces constructed belong to connected components of [Formula: see text] without canonical models.
Quantum-inspired firefly algorithm integrated with cuckoo search for optimal path planning
Authors: Kundra Harish , Khan Wasim , Malik Meenakshi , Rane Kantilal Pitambar , Neware Rahul , Jain Vishal
Published: September 2021

The firefly algorithm and cuckoo search are the meta-heuristic algorithms efficient to determine the solution for the searching and optimization problems. The current work proposes an integrated concept of quantum-inspired firefly algorithm with cuckoo search (IQFACS) that adapts both algorithms’ expedient attributes to optimize the solution set. In the IQFACS algorithm, the quantum-inspired firefly algorithm (QFA) ensures the diversification of fireflies-based generated solution set using the superstitions quantum states of the quantum computing concept. The cuckoo search (CS) algorithm uses the Lévy flight attribute to escape the QFA from the premature convergence and stagnation stage more effectively than the quantum principles. Here, the proposed algorithm is applied for the application of optimal path planning. Before using the proposed algorithm for path planning, the algorithm is tested on different optimization benchmark functions to determine the efficacy of the proposed IQFACS algorithm than the firefly algorithm (FA), CS, and hybrid FA and CS algorithm. Using the proposed IQFACS algorithm, path planning is performed on the satellite images with vegetation as the focused region. These satellite images are captured from Google Earth and belong to the different areas of India. Here, satellite images are converted into morphologically processed binary images and considered as maps for path planning. The path planning process is also executed with the FA, CS, and QFA algorithms. The performance of the proposed algorithm and other algorithms are accessed with the evaluation of simulation time and the number of cycles to attain the shortest path from defined source to destination. The error rate measure is also incorporated to analyze the overall performance of the proposed IQFACS algorithm over the other algorithms.
Efficacy and Safety of Chinese Herbal Medicine on Treatment of Breast Cancer: A Meta-analysis of Randomized Controlled Trials
Authors: Ho Venice Wing-Tung , Tan Hor-Yue , Guo Wei , Li Sha , Wang Ning , Meng Wei , So Tsz-him , Yu Edwin Chau-Leung , Feng Yibin
Published: September 2021

Breast cancer is currently the most common cancer in women, and it accounts for 11.6% of all cancer diagnoses in 2018. Breast cancer patients frequently resort to alternative medicine in addition to conventional Western therapy. This study is to evaluate clinical effectiveness of Chinese herbal medicine (CHM) on breast cancer by conducting meta-analyses on 81 randomized controlled trials (RCTs) with a total of 7215 subjects from eight databases. All RCTs compared patients using Western therapy alone and those using additional CHM therapy to evaluate the difference of primary (tumor response, mean time to progression (mTTP), overall survival (OS) and progression free survival (PFS)) and secondary outcome measures (tumor markers). Results showed that under the RECIST1.1 criteria, 52% patients with additional CHM therapy (67%, under WHO criteria) achieved either a complete response (CR) or a partial response (PR), compared to 38% patients with Western therapy alone (53%, under the WHO criteria). The risk ratio was 1.31 ([Formula: see text] < 0.00001, 95% CI = 1.15–1.50) for patients with CHM plus Western therapy and 1.25 ([Formula: see text] < 0.00001, 95% CI = 1.18–1.98) for those with Western therapy. Moreover, patients with complementary CHM therapy were associated with an mTTP of 2.79 months longer ([Formula: see text] < 0.00001) and an OS of 1.90 months longer ([Formula: see text] < 0.00001); they also had an increase in 3-year PFS ([Formula: see text]= 0.002), 2- ([Formula: see text]= 0.0002) and 5-year ([Formula: see text]= 0.006) OS rates. Therefore, complementary CHM therapy might demonstrate clinical benefits for breast cancer patients in terms of tumor response and survival. Clinical studies with further stratification of tumor stages and intervention types are highly warranted.
Revisiting neutron yield in table-top nuclear fusion driven by an intense femtosecond laser pulse interaction with the gas clusters
Authors: Chen Guanglong , Cao Yunjiu , Ren Li , Huang Jiehui , He Jianping
Published: September 2021

With the development of femtosecond (fs) laser technology, an fs laser pulse with 10s of Joule, even 100s of Joule energy is available and the focused laser intensity can be expected to induce the pure Coulomb explosion of the cluster with a much larger average radius than before. Meanwhile, the production of gas cluster with an average radius of upto 10s of nanometer has been possible. In this case, it is necessary to reinvestigate the feasibility of 109 n/shot neutron yield for the practical application in the intense fs laser-driven nuclear fusion. In this work, the neutron yield from the explosions of the D2 clusters of 6–20 nm average radius at the 0.5–100 J pulse energy and the CD4 clusters was investigated theoretically. It is found that the optimum neutron yield of 109 n/shot can be obtained at the laser energy and the cluster radius currently available. However, a clustered-gas jet with a large cross-section is demanded to match the proper plasma diameter.
Impact of Labeling Schemes on Dense Crowd Counting Using Convolutional Neural Networks with Multiscale Upsampling
Authors: Olmschenk Greg , Wang Xuan , Tang Hao , Zhu Zhigang
Published: September 2021

Gatherings of thousands to millions of people frequently occur for an enormous variety of educational, social, sporting, and political events, and automated counting of these high-density crowds is useful for safety, management, and measuring significance of an event. In this work, we show that the regularly accepted labeling scheme of crowd density maps for training deep neural networks may not be the most effective one. We propose an alternative inverse k-nearest neighbor (i[Formula: see text]NN) map mechanism that, even when used directly in existing state-of-the-art network structures, shows superior performance. We also provide new network architecture mechanisms that we demonstrate in our own MUD-i[Formula: see text]NN network architecture, which uses multi-scale drop-in replacement upsampling via transposed convolutions to take full advantage of the provided i[Formula: see text]NN labeling. This upsampling combined with the i[Formula: see text]NN maps further improves crowd counting accuracy. We further analyze several variations of the i[Formula: see text]NN labeling mechanism, which apply transformations on the [Formula: see text]NN measure before generating the map, in order to consider the impact of camera perspective views, image resolutions, and the changing rates of the mapping functions. To alleviate the effects of crowd density changes in each image, we also introduce an attenuation mechanism in the i[Formula: see text]NN mapping. Experimentally, we show that inverse square root [Formula: see text]NN map variation (iR[Formula: see text]NN) provides the best performance. Discussions are provided on computational complexity, label resolutions, the gains in mapping and upsampling, and details of critical cases such as various crowd counts, uneven crowd densities, and crowd occlusions.
A Novel Method to Control Leakage and Noise in Domino Circuit for Wide Fan-In OR Logic
Authors: Kumar Ankur , Nagaria R. K.
Published: September 2021

This paper proposes a novel method to control leakage and noise in domino circuits for wide fan-in OR logic with low power consumption, low process variation, and higher noise margin under the similar delay condition. In the proposed method, output and dynamic nodes are isolated from the PDN (Pull-Down Network) to improve the noise immunity and reduce switching activity. Further, with the aid of a transistor in the stack, the sub-threshold current is reduced. Thus, the proposed domino is applicable for high-speed and low-power applications in deep sub-micro-range. Simulation results show that the proposed domino improves the noise immunity and figure of merit (FOM) by factors of 1.95 and 2.34, respectively, with respect to the conventional domino with a footer. Along with this improvement, 26% reduction is also observed in power consumption. The entire simulations for all the domino circuits are done at 45-nm CMOS technology by using SPECTRE simulator under the Cadence Virtuoso environment.
MEAN LI–YORKE CHAOTIC SET WITH FULL HAUSDORFF DIMENSION FOR CONTINUED FRACTIONS
Authors: LIU WEIBIN , WANG SHUAILING
Published: September 2021

In this paper, we consider the mean Li–Yorke chaotic property for continued fraction dynamical system. Every measurable mean Li–Yorke scrambled set along any given sequence is of zero Lebesgue measure. Meanwhile, we construct one with full Hausdorff dimension for the sequence with some mild condition.
STUDY ON PORTFOLIO MODEL UNDER BACKGROUND RISK AND FRACTAL MARKET
Authors: LI HESEN , GU JINGCHENG , CHUN ZHENGJIE , LUO LAN , WU XU
Published: September 2021

In view of the necessity of optimizing portfolio models under a combination of the fractal market and the background risk, this paper incorporates the fractal correlations and background risk into the research framework of portfolio model optimization. Then the portfolio model under background risk and fractal market (PBF) is constructed, and the analytical formula of the model is given. Based on this, the empirical results not only illustrate the efficiency of PBF but also show that PBF can improve the yield and risk-adjusted portfolio performance. According to the research results, PBF can provide a more efficient reference for people to make decisions on the investment portfolio.
RELATIONSHIP OF UPPER BOX DIMENSION BETWEEN CONTINUOUS FRACTAL FUNCTIONS AND THEIR RIEMANN–LIOUVILLE FRACTIONAL INTEGRAL
Authors: XIAO WEI
Published: September 2021

This paper considers the relationship of box dimension between a continuous fractal function and its Riemann–Liouville fractional integral. For an arbitrary fractal function [Formula: see text] it is proved that the upper box dimension of the graph of Riemann–Liouville fractional integral [Formula: see text] does not exceed the upper box dimension of [Formula: see text], i.e. [Formula: see text]. This estimate shows that [Formula: see text]order Riemann–Liouville fractional integral [Formula: see text] does not increase the fractal dimension of the integrand [Formula: see text], which means that Riemann–Liouville fractional integration does not decrease the smoothness at least that is obvious known result for classic integration. Our result partly answers fractal calculus conjecture in [F. B. Tatom, The relationship between fractional calculus and fractals, Fractals 2 (1995) 217–229] and [Y. S. Liang and W. Y. Su, Riemann–Liouville fractional calculus of one-dimensional continuous functions, Sci. Sin. Math. 4 (2016) 423–438].
COUPLED HYDRO-MECHANICAL MODELING OF GAS FLOW IN SHALE MATRIX CONSIDERING THE FRACTAL CHARACTERISTICS OF NANOPORES
Authors: GAO QI , CHENG YUANFANG , HAN SONGCAI , LI YANG , YAN CHUANLIANG , HAN ZHONGYING
Published: September 2021

To economically develop shale gas reservoirs, hydraulic fracturing treatments must be applied to artificially introduce pathways for gas to flow out. After hydraulic fracturing, both the induced hydraulic fractures and activated natural fractures provide high permeable channels for gas transport. However, the long-term production performance of shale gas reservoirs is determined by the physical properties of matrix instead of the fractures. In this work, a coupled hydro-mechanical model is developed to investigate gas flow in heterogeneous shale matrix at the microscale. This model considers the mechanical interaction and gas mass transfer between organic matter (OM) and inorganic matter (iOM) during gas depletion. The interesting results show that due to matrix heterogeneity, i.e. co-existence of OM and iOM, the gas flow and mechanical deformation behaviors in shale exhibit regional differences. Specifically, during reservoir depletion, pore pressure, Knudsen number and volumetric strain in iOM are smaller than that in OM while the intrinsic and apparent permeability of OM are smaller than that of iOM. Thus, matrix heterogeneity should be taken into account when characterizing shale gas flow. In addition, sensitivity analysis is conducted to study the influence of fractal parameters on shale apparent permeability evolution. These fractal parameters include nanopore radius fractal dimension, tortuosity fractal dimension and maximum nanopore radius. The analysis indicates that the variation of fractal parameters in iOM results in the change of apparent permeability of both OM and iOM, while the variation of fractal parameters in OM only leads to the change of apparent permeability of OM. The modeling results offer new insights into gas flow behaviors in shale matrix.
A Survey on Resilience in the IoT
Authors: Berger Christian , Eichhammer Philipp , Reiser Hans P. , Domaschka Jörg , Hauck Franz J. , Habiger Gerhard
Published: September 2021

Internet-of-Things (IoT) ecosystems tend to grow both in scale and complexity, as they consist of a variety of heterogeneous devices that span over multiple architectural IoT layers (e.g., cloud, edge, sensors). Further, IoT systems increasingly demand the resilient operability of services, as they become part of critical infrastructures. This leads to a broad variety of research works that aim to increase the resilience of these systems. In this article, we create a systematization of knowledge about existing scientific efforts of making IoT systems resilient. In particular, we first discuss the taxonomy and classification of resilience and resilience mechanisms and subsequently survey state-of-the-art resilience mechanisms that have been proposed by research work and are applicable to IoT. As part of the survey, we also discuss questions that focus on the practical aspects of resilience, e.g., which constraints resilience mechanisms impose on developers when designing resilient systems by incorporating a specific mechanism into IoT systems.
Synergistically Exploiting CNN Pruning and HLS Versioning for Adaptive Inference on Multi-FPGAs at the Edge
Authors: Korol Guilherme , Jordan Michael Guilherme , Rutzig Mateus Beck , Beck Antonio Carlos Schneider
Published: September 2021

FPGAs, because of their energy efficiency, reconfigurability, and easily tunable HLS designs, have been used to accelerate an increasing number of machine learning, especially CNN-based, applications. As a representative example, IoT Edge applications, which require low latency processing of resource-hungry CNNs, offload the inferences from resource-limited IoT end nodes to Edge servers featuring FPGAs. However, the ever-increasing number of end nodes pressures these FPGA-based servers with new performance and adaptability challenges. While some works have exploited CNN optimizations to alleviate inferences’ computation and memory burdens, others have exploited HLS to tune accelerators for statically defined optimization goals. However, these works have not tackled both CNN and HLS optimizations altogether; neither have they provided any adaptability at runtime, where the workload’s characteristics are unpredictable. In this context, we propose a hybrid two-step approach that, first, creates new optimization opportunities at design-time through the automatic training of CNN model variants (obtained via pruning) and the automatic generation of versions of convolutional accelerators (obtained during HLS synthesis); and, second, synergistically exploits these created CNN and HLS optimization opportunities to deliver a fully dynamic Multi-FPGA system that adapts its resources in a fully automatic or user-configurable manner. We implement this two-step approach as the AdaServ Framework and show, through a smart video surveillance Edge application as a case study, that it adapts to the always-changing Edge conditions: AdaServ processes at least 3.37× more inferences (using the automatic approach) and is at least 6.68× more energy-efficient (user-configurable approach) than original convolutional accelerators and CNN Models (VGG-16 and AlexNet). We also show that AdaServ achieves better results than solutions dynamically changing only the CNN model or HLS version, highlighting the importance of exploring both; and that it is always better than the best statically chosen CNN model and HLS version, showing the need for dynamic adaptability.
MARS: mmWave-based Assistive Rehabilitation System for Smart Healthcare
Authors: An Sizhe , Ogras Umit Y.
Published: September 2021

Rehabilitation is a crucial process for patients suffering from motor disorders. The current practice is performing rehabilitation exercises under clinical expert supervision. New approaches are needed to allow patients to perform prescribed exercises at their homes and alleviate commuting requirements, expert shortages, and healthcare costs. Human joint estimation is a substantial component of these programs since it offers valuable visualization and feedback based on body movements. Camera-based systems have been popular for capturing joint motion. However, they have high-cost, raise serious privacy concerns, and require strict lighting and placement settings. We propose a millimeter-wave (mmWave)-based assistive rehabilitation system (MARS) for motor disorders to address these challenges. MARS provides a low-cost solution with a competitive object localization and detection accuracy. It first maps the 5D time-series point cloud from mmWave to a lower dimension. Then, it uses a convolution neural network (CNN) to estimate the accurate location of human joints. MARS can reconstruct 19 human joints and their skeleton from the point cloud generated by mmWave radar. We evaluate MARS using ten specific rehabilitation movements performed by four human subjects involving all body parts and obtain an average mean absolute error of 5.87 cm for all joint positions. To the best of our knowledge, this is the first rehabilitation movements dataset using mmWave point cloud. MARS is evaluated on the Nvidia Jetson Xavier-NX board. Model inference takes only 64

s and consumes 442

J energy. These results demonstrate the practicality of MARS on low-power edge devices.
SAGE: A Split-Architecture Methodology for Efficient End-to-End Autonomous Vehicle Control
Authors: Malawade Arnav , Odema Mohanad , Lajeunesse-degroot Sebastien , Al Faruque Mohammad Abdullah
Published: September 2021

Autonomous vehicles (AV) are expected to revolutionize transportation and improve road safety significantly. However, these benefits do not come without cost; AVs require large Deep-Learning (DL) models and powerful hardware platforms to operate reliably in real-time, requiring between several hundred watts to one kilowatt of power. This power consumption can dramatically reduce vehicles’ driving range and affect emissions. To address this problem, we propose SAGE: a methodology for selectively offloading the key energy-consuming modules of DL architectures to the cloud to optimize edge, energy usage while meeting real-time latency constraints. Furthermore, we leverage Head Network Distillation (HND) to introduce efficient
bottlenecks
within the DL architecture in order to minimize the network overhead costs of offloading with almost no degradation in the model’s performance. We evaluate SAGE using an Nvidia Jetson TX2 and an industry-standard Nvidia Drive PX2 as the AV edge, devices and demonstrate that our offloading strategy is practical for a wide range of DL models and internet connection bandwidths on 3G, 4G LTE, and WiFi technologies. Compared to edge-only computation, SAGE reduces energy consumption by an average of
36.13%
,
47.07%
, and
55.66%
for an AV with one low-resolution camera, one high-resolution camera, and three high-resolution cameras, respectively. SAGE also reduces upload data size by up to
98.40%
compared to direct camera offloading.
MSYNC: A Generalized Formal Design Pattern for Virtually Synchronous Multirate Cyber-physical Systems
Authors: Bae Kyungmin , Ölveczky Peter Csaba
Published: September 2021

TTA and PALS are two prominent formal design patterns—with different strengths and weaknesses—for virtually synchronous distributed cyber-physical systems (CPSs). They greatly simplify the design and verification of such systems by allowing us to design and verify their underlying synchronous designs. In this paper we introduce and verify MSYNC as a formal design (and verification) pattern/synchronizer for hierarchical multirate CPSs that generalizes, and combines the advantages of, both TTA and (single-rate and multirate) PALS. We also define an extension of TTA to multirate CPSs as a special case. We show that MSYNC outperforms both TTA and PALS in terms of allowing shorter periods, and illustrate the MSYNC design and verification approach with a case study on a fault-tolerant distributed control system for turning an airplane.
HMDS: A Makespan Minimizing DAG Scheduler for Heterogeneous Distributed Systems
Authors: Senapati Debabrata , Sarkar Arnab , Karfa Chandan
Published: September 2021

The problem of scheduling Directed Acyclic Graphs in order to minimizemakespan(schedule length), is known to be a challenging and computationally hard problem. Therefore, researchers have endeavored towards the design of various heuristic solution generation techniques both for homogeneous as well as heterogeneous computing platforms. This work first presentsHMDS-Bl, a list-based heuristicmakespanminimization algorithm for task graphs on fully connected heterogeneous platforms. Subsequently,HMDS-Blhas been enhanced by empowering it with a low-overhead depth-first branch and bound based search approach, resulting in a new algorithm calledHMDS.HMDShas been equipped with a set of novel tunable pruning mechanisms, which allow the designer to obtain a judicious balance between performance (makespan) and solution generation times, depending on the specific scenario at hand. Experimental analyses using randomly generated DAGs as well as benchmark task graphs, have shown thatHMDSis able to comprehensively outperform state-of-the-art algorithms such asHEFT,PEFT,PPTS, etc., in terms of archivedmakespanswhile incurring bounded additional computation time overhead.
Architecture and Dynamics of Meiotic Chromosomes
Authors: Ur Sarah N. , Corbett Kevin D.
Published: September 2021

The specialized two-stage meiotic cell division program halves a cell's chromosome complement in preparation for sexual reproduction. This reduction in ploidy requires that in meiotic prophase, each pair of homologous chromosomes (homologs) identify one another and form physical links through DNA recombination. Here, we review recent advances in understanding the complex morphological changes that chromosomes undergo during meiotic prophase to promote homolog identification and crossing over. We focus on the structural maintenance of chromosomes (SMC) family cohesin complexes and the meiotic chromosome axis, which together organize chromosomes and promote recombination. We then discuss the architecture and dynamics of the conserved synaptonemal complex (SC), which assembles between homologs and mediates local and global feedback to ensure high fidelity in meiotic recombination. Finally, we discuss exciting new advances, including mechanisms for boosting recombination on particular chromosomes or chromosomal domains and the implications of a new liquid crystal model for SC assembly and structure.
Drosophila sechellia: A Genetic Model for Behavioral Evolution and Neuroecology
Authors: Auer Thomas O. , Shahandeh Michael P. , Benton Richard
Published: September 2021

Defining the mechanisms by which animals adapt to their ecological niche is an important problem bridging evolution, genetics, and neurobiology. We review the establishment of a powerful genetic model for comparative behavioral analysis and neuroecology, Drosophila sechellia. This island-endemic fly species is closely related to several cosmopolitan generalists, including Drosophila melanogaster, but has evolved extreme specialism, feeding and reproducing exclusively on the noni fruit of the tropical shrub Morinda citrifolia. We first describe the development and use of genetic approaches to facilitate genotype/phenotype associations in these drosophilids. Next, we survey the behavioral, physiological, and morphological adaptations of D. sechellia throughout its life cycle and outline our current understanding of the genetic and cellular basis of these traits. Finally, we discuss the principles this knowledge begins to establish in the context of host specialization, speciation, and the neurobiology of behavioral evolution and consider open questions and challenges in the field.
Chemogenetic Approaches to Probe Redox Pathways: Implications for Cardiovascular Pharmacology and Toxicology
Authors: Steinhorn Benjamin , Eroglu Emrah , Michel Thomas
Published: September 2021

Chemogenetics refers to experimental systems that dynamically regulate the activity of a recombinant protein by providing or withholding the protein's specific biochemical stimulus. Chemogenetic tools permit precise dynamic control of specific signaling molecules to delineate the roles of those molecules in physiology and disease. Yeast d-amino acid oxidase (DAAO) enables chemogenetic manipulation of intracellular redox balance by generating hydrogen peroxide only in the presence of d-amino acids. Advances in biosensors have allowed the precise quantitation of these signaling molecules. The combination of chemogenetic approaches with biosensor methodologies has opened up new lines of investigation, allowing the analysis of intracellular redox pathways that modulate physiological and pathological cell responses. We anticipate that newly developed transgenic chemogenetic models will permit dynamic modulation of cellularredox balance in diverse cells and tissues and will facilitate the identification and validation of novel therapeutic targets involved in both physiological redox pathways and pathological oxidative stress.
Overexpression of dimethylarginine dimethylaminohydrolase 1 protects from angiotensin II-induced cardiac hypertrophy and vascular remodeling
Authors: Kopaliani Irakli , Jarzebska Natalia , Billoff Silke , Kolouschek Anne , Martens-Lobenhoffer Jens , Bornstein Stefan R. , Bode-Böger Stefanie M. , Ragavan Vinitha N. , Weiss Norbert , Mangoni Arduino A. , Deussen Andreas , Rodionov Roman N.
Published: September 2021

We showed that overexpression of dimethylarginine dimethylaminohydrolase 1 (DDAH1) protects from angiotensin II-induced cardiovascular damage, progression of hypertension, and adverse vascular remodeling in vivo. This protective effect strongly depends on the dose and duration of angiotensin II infusion and is associated with decreased levels of asymmetric dimethylarginine (ADMA), preservation of endothelial function, inhibition of cardiovascular inflammation, as well as lower activity of matrix metalloproteinase-2 (MMP2). Our findings are highly clinically relevant, because they suggest that upregulation of DDAH1 might be a promising therapeutic approach against angiotensin II-induced end organ damage.