bluuebunny/crossref_metadata_2025 huggingface dataset:
Practical Aspects of Making Expanded Joints
Authors: Maxwell C. A.
Published: December 2022

As one of three current papers on the general subject of rolling-in boiler, heat-exchanger, and condenser tubes, this presentation deals more particularly with the practical application of recent tube-expanding equipment and methods largely developed by The Babcock & Wilcox Company. Progress in the solution of tube-rolling problems from 1924, when axial movement of tubes in their seats became particularly acute, down to the present time is noted by the author; accomplishments in this direction being the work of comparatively few engineers who have devoted their attention to the various aspects. Only since 1940, when a new expander was developed, have the weaknesses of the standard expander been overcome, making possible the expanding of tubes in seats of unlimited width. There are three basic tools for producing expanded joints from which all others are derived, the roll, the prosser, and the ball-drift expander. Details of each are given. The procedures followed are explained comprehensively, as is also the function of the ball-drift expander used for relatively small tubes in thick seats.
Effectiveness of Shear-Stressed Rubber Compounds in Isolating Machinery Vibration
Authors: Madden Baxter C.
Published: December 2022

This paper is concerned with determining the effectiveness of rubber compounds in resilient mountings in the isolation of vibrating machinery where the rubber compound is stressed principally in shear. Seven rubber compounds were investigated. Certain considerations to be taken into account when appraising the effectiveness of a resilient mounting are stated. A dimensionless criterion is developed for the effectiveness of a rubber compound in terms of physical properties measurable by testing apparatus. The criterion is evaluated for each of the seven compounds. The results indicate that the criterion is worthy of consideration.
Chemical Removal of Scale from Heat-Exchange Equipment
Authors: Alquist F. N. , Groom C. H. , Williams G. F.
Published: December 2022

The use of inhibited hydrochloric-acid-base solvents to remove scale from various commercial units, chiefly boilers and other heat-exchange equipment, is comparatively new. A sample of the scale to be removed is subjected to X-ray and spectroscopic analysis and solubility tests as an aid in determining the conditions of treatment. Four treatments of commercial equipment and results obtained are described, the mobile equipment used in chemical cleaning is illustrated, and tables of scales and their occurrence are presented.
Estimating Discretization Error With Prescribed Orders of Accuracy and Fractional Refinement Ratios
Authors: Lo Sharp Chim Yui
Published: December 2022

Solution verification is crucial for establishing the reliability of simulations. A central challenge is to estimate the discretization error accurately and reliably. Many approaches to this estimation are based on the observed order of accuracy; however, it may fail when the numerical solutions lie outside the asymptotic range. Here we propose a grid refinement method that adopts constant orders given by the user, called the prescribed orders expansion method (POEM). Through an iterative procedure, the user is guaranteed to obtain the dominant orders of the discretization error. The user can also compare the corresponding terms to quantify the degree of asymptotic convergence of the numerical solutions. These features ensure that the estimation of the discretization error is accurate and reliable. Moreover, the implementation of POEM is the same for any dimensions and refinement paths. We demonstrate these capabilities using some advection and diffusion problems and standard refinement paths. The computational cost of using POEM is lower if the refinement ratio is larger; however, the number of shared grid points where POEM applies also decreases, causing greater uncertainty in the global estimates of the discretization error. We find that the proportion of shared grid points is maximized when the refinement ratios are in a certain form of fractions. Furthermore, we develop the method of interpolating differences between approximate solutions (MIDAS) for creating shared grid points in the domain. These approaches allow users of POEM to obtain a global estimate of the discretization error of lower uncertainty at a reduced computational cost.
Development of a Customized Mask Frame Using a Three-Dimensional Facial Scan for an Airtight Seal for Disposable Surgical Face Masks
Authors: Park Jangwoon , Mehrubeoglu Mehrube
Published: December 2022

Disposable surgical face masks are designed to block the airborne transmission of infectious viruses between patients and healthcare personnel; however, there are limitations to a surgical mask's ability to prevent transmissions because the mask does not provide an airtight seal around the face. This study focuses on the design and development of a custom mask frame, using individuals' three-dimensional (3D) facial scans, to improve the seal of the existing surgical masks. Three participants' facial scans with a wide range of facial dimensions were collected using a 3D hand-held scanner. During design, the contact area between the custom frame and the wearer's skin was determined based on the individual's 3D facial shape. To evaluate the effectiveness of the airtight seal, a qualitative fit (smell/taste) test kit and thermal imaging camera were utilized. When the participants wore the surgical masks without the customized mask frames, the participants smelled the saccharine scent from the test kit. However, while wearing the surgical masks fitted with the custom mask frame that held the mask in place, none of the participants could smell the scent. In addition, thermal images showed ambient temperature changes in the surgical mask suggesting air leakage around the boundary of the mask while the subject was inhaling and exhaling. With the mask frame, thermal images confirmed the effectiveness of the custom frame to block the inflow/outflow of air potentially carrying the virus. The results indicate that the custom-built mask frames are effective in providing a proper and much improved seal compared to a surgical mask without the frame. The developed custom mask frame will be particularly beneficial for frontline medical staff members who treat patients with infectious viruses transmitted through aerosols as part of their PPE.
Large-area 1D selective emitter for thermophotovoltaic applications in the mid-infrared
Authors: Oh Minsu , Grossklaus Kevin , Vandervelde Thomas E.
Published: December 2022

Two- or three-dimensionally patterned subwavelength structures, also known as metamaterials, have the advantage of arbitrarily engineerable optical properties. In thermophotovoltaic (TPV) applications, metamaterials are commonly used to optimize the emitter’s radiation spectrum for various source temperatures. The output power of a TPV device is proportional to the photon flux, which is proportional to the emitter size. However, using 2D or 3D metamaterials imposes challenges to realizing large emitters since fabricating their subwavelength features typically involves complicated fabrication processes and is highly time-consuming. In this work, we demonstrate a large-area (78 cm2) thermal emitter. This emitter is simply fabricated with one-dimensional layers of silicon (Si) and chromium (Cr), and therefore, it can be easily scaled up to even larger sizes. The emissivity spectrum of the emitter is measured at 802 K, targeting an emission peak in the mid-infrared. The emissivity peak is ∼0.84 at the wavelength of 3.75 μm with a 1.2 μm bandwidth. Moreover, the emission spectrum of our emitter can be tailored for various source temperatures by changing the Si thickness. Therefore, the results of this work can lead to enabling TPV applications with higher output power and lower fabrication cost.
β-Endorphin mediates radiation therapy fatigue
Authors: Hermann Andrea L. , Fell Gillian L. , Kemény Lajos V. , Fung Claire Y. , Held Kathryn D. , Biggs Peter J. , Rivera Phillip D. , Bilbo Staci D. , Igras Vivien , Willers Henning , Kung Jong , Gheorghiu Liliana , Hideghéty Katalin , Mao Jianren , Woolf Clifford J. , Fisher David E.
Published: December 2022

Fatigue is a common adverse effect of external beam radiation therapy in cancer patients. Mechanisms causing radiation fatigue remain unclear, although linkage to skin irradiation has been suggested. β-Endorphin, an endogenous opioid, is synthesized in skin following genotoxic ultraviolet irradiation and acts systemically, producing addiction. Exogenous opiates with the same receptor activity as β-endorphin can cause fatigue. Using rodent models of radiation therapy, exposing tails and sparing vital organs, we tested whether skin-derived β-endorphin contributes to radiation-induced fatigue. Over a 6-week radiation regimen, plasma β-endorphin increased in rats, paralleled by opiate phenotypes (elevated pain thresholds, Straub tail) and fatigue-like behavior, which was reversed in animals treated by the opiate antagonist naloxone. Mechanistically, all these phenotypes were blocked by opiate antagonist treatment and were undetected in either β-endorphin knockout mice or mice lacking keratinocyte p53 expression. These findings implicate skin-derived β-endorphin in systemic effects of radiation therapy. Opioid antagonism may warrant testing in humans as treatment or prevention of radiation-induced fatigue.
Widespread transposon co-option in the
Caenorhabditis
germline regulatory network
Authors: Carelli Francesco Nicola , Cerrato Chiara , Dong Yan , Appert Alex , Dernburg Abby , Ahringer Julie
Published: December 2022

The movement of selfish DNA elements can lead to widespread genomic alterations with potential to create novel functions. We show that transposon expansions in
Caenorhabditis
nematodes led to extensive rewiring of germline transcriptional regulation. We find that about one-third of
Caenorhabditis elegans
germline-specific promoters have been co-opted from two related miniature inverted repeat transposable elements (TEs), CERP2 and CELE2. These promoters are regulated by HIM-17, a THAP domain–containing transcription factor related to a transposase. Expansion of CERP2 occurred before radiation of the
Caenorhabditis
genus, as did fixation of mutations in HIM-17 through positive selection, whereas CELE2 expanded only in
C. elegans
. Through comparative analyses in
Caenorhabditis briggsae
, we find not only evolutionary conservation of most CERP2 co-opted promoters but also a substantial fraction that are species-specific. Our work reveals the emergence and evolutionary conservation of a novel transcriptional network driven by TE co-option with a major impact on regulatory evolution.
Topologically reconfigurable magnetic polaritons
Authors: Li Min , Hu Guangwei , Chen Xuan , Qiu Cheng-Wei , Chen Hongsheng , Wang Zuojia
Published: December 2022

Hyperbolic polaritons in extremely anisotropic materials have attracted intensive attention due to their exotic optical features. Recent advances in optical materials reveal unprecedented dispersion engineering of polaritons, resulting in twistronics for photons, canalized phonon polaritons, shear polaritons, and tunable topological polaritons. However, the on-demand reconfigurability of polaritons, especially with magnetic anisotropic dispersions, is restricted by weak natural magnetic anisotropy and hence remains largely unexplored. Here, we show how origami fused with artificial magnetism unveils a versatile pathway to topologically reconfigure magnetic polaritons. We experimentally demonstrate that the three-dimensional origami deformation allows to reconfigure hyperbolic or elliptic topology of polariton dispersion and modulate group velocity. With group velocity transitioning from positive to negative directions, we further report reconfigurable origami polariton circuitry in which the polariton propagation and phase distribution can be tailored. Our findings provide alternative perspectives on on-chip polaritonics, with potential applications in energy transfer, sensing, and information transport.
Development and psychometric evaluation of the Implementation Science Research Project Appraisal Criteria (ImpResPAC) tool: a study protocol
Authors: Sweetnam Chloe , Goulding Lucy , Davis Rachel E , Khadjesari Zarnie , Boaz Annette , Healey Andy , Sevdalis Nick , Bakolis Ioannis , Hull Louise
Published: December 2022

Introduction

The need for quantitative criteria to appraise the quality of implementation research has recently been highlighted to improve methodological rigour. The Implementation Science Research development (ImpRes) tool and supplementary guide provide methodological guidance and recommendations on how to design high-quality implementation research. This protocol reports on the development of the Implementation Science Research Project Appraisal Criteria (ImpResPAC) tool, a quantitative appraisal tool, developed based on the structure and content of the ImpRes tool and supplementary guide, to evaluate the conceptual and methodological quality of implementation research.

Methods and analysis

This study employs a three-stage sequential mixed-methods design. During stage 1, the research team will map core domains of the ImpRes tool, guidance and recommendations contained in the supplementary guide and within the literature, to ImpResPAC. In stage 2, an international multidisciplinary expert group, recruited through purposive sampling, will inform the refinement of ImpResPAC, including content, scoring system and user instructions. In stage 3, an extensive psychometric evaluation of ImpResPAC, that was created in stage 1 and refined in stage 2, will be conducted. The scaling assumptions (inter-item and item-total correlations), reliability (internal consistency, inter-rater) and validity (construct and convergent validity) will be investigated by applying ImpResPAC to 50 protocols published inImplementation Science. We envisage developing ImpResPAC in this way will provide implementation research stakeholders, primarily grant reviewers and educators, a comprehensive, transparent and fair appraisal of the conceptual and methodological quality of implementation research, increasing the likelihood of funding research that will generate knowledge and contribute to the advancement of the field.

Ethics and dissemination

This study will involve human participants. This study has been registered and minimal risk ethical clearance granted by The Research Ethics Office, King’s College London (reference number MRA-20/21-20807). Participants will receive written information on the study via email and will provide e-consent if they wish to participate. We will use traditional academic modalities of dissemination (eg, conferences and publications).
From hearing to seeing: medical dispatchers’ experience with use of video streaming in medical emergency calls − a qualitative study
Authors: Idland Siri , Iversen Emil , Brattebø Guttorm , Kramer-Johansen Jo , Hjortdahl Magnus
Published: December 2022

Objectives

Video streaming has recently been introduced as an additional tool for communication between medical dispatchers and caller. Research implies that video streaming may be a useful tool for the dispatchers, but more knowledge is needed. With this study, we wanted to explore how the dispatchers experience using video streaming as an additional tool in medical emergency calls.

Design

An explorative, qualitative study using semi-structured focus group interviews.

Setting

Two emergency medical communications centres in Norway where video streaming recently had been introduced. Interviews were conducted during 24 June 2020 and 26 June 2020.

Participants

We recruited 25 medical dispatchers, either nurses or emergency medical technicians who worked at the two centres.

Results

The results are categorised into three themes: (1) change in dispatcher’s perception of the patient and the situation, (2) reassurance for the dispatcher and (3) worries about increased time consumption and the possibility of unpleasant images.

Conclusion

The dispatchers experienced that the use of video streaming in medical emergency calls might contribute to a better comprehension of the situation and following more precise resource allocation, as well as greater reassurance for the dispatcher and improved relationship between the dispatcher and the caller. Further research with an aim to measure effects and safety of video streaming during medical emergency calls is needed.
Pharmacist and Homeless Outreach Engagement and Non-medical Independent prescribing Rx (PHOENIx): a study protocol for a pilot randomised controlled trial
Authors: Lowrie Richard , McPherson Andrew , Mair Frances , Maguire Donogh , Paudyal Vibhu , Blair Becky , Brannan David , Moir Jane , Hughes Fiona , Duncan Clare , Stock Kate , Farmer Natalia , Ramage Rebekah , Lombard Cian , Ross Steven , Scott Ailsa , Provan George , Sills Laura , Hislop Jenni , Reilly Frank , Williamson Andrea E
Published: December 2022

Introduction

The number of people experiencing homelessness (PEH) is increasing worldwide. Systematic reviews show high levels of multimorbidity and mortality. Integrated health and social care outreach interventions may improve outcomes. No previous studies have targeted PEH with recent drug overdose despite high levels of drug-related deaths and few data describe their health/social care problems. Feasibility work suggests a collaborative health and social care intervention (Pharmacist andHomelessOutreachEngagement andNon-medicalIndependent prescribing Rx, PHOENIx) is potentially beneficial. We describe the methods of a pilot randomised controlled trial (RCT) with parallel process and economic evaluation of PEH with recent overdose.

Methods and analysis

Detailed health and social care information will be collected before randomisation to care-as-usual plus visits from a pharmacist and a homeless outreach worker (PHOENIx) for 6–9 months or to care-as-usual. The outcomes are the rates of presentations to emergency department for overdose or other causes and whether to progress to a definitive RCT: recruitment of ≥100 participants within 4 months, ≥60% of patients remaining in the study at 6 and 9 months, ≥60% of patients receiving the intervention, and ≥80% of patients with data collected. The secondary outcomes include health-related quality of life, hospitalisations, treatment uptake and patient-reported measures. Semistructured interviews will explore the future implementation of PHOENIx, the reasons for overdose and protective factors. We will assess the feasibility of conducting a cost-effectiveness analysis.

Ethics and dissemination

The study was approved by South East Scotland National Health Service Research Ethics Committee 01. Results will be made available to PEH, the study funders and other researchers.

Trial registration number

ISRCTN10585019.
Multidimensional pain profiling in people living with obesity and attending weight management services: a protocol for a longitudinal cohort study
Authors: Smart Keith M , Hinwood Natasha S , Dunlevy Colin , Doody Catherine M , Blake Catherine , Fullen Brona M , Le Roux Carel W , O’Connell Jean , Gilsenan Clare , Finucane Francis M , O'Donoghue Grainne
Published: December 2022

Introduction

Pain is prevalent in people living with overweight and obesity. Obesity is associated with increased self-reported pain intensity and pain-related disability, reductions in physical functioning and poorer psychological well-being. People living with obesity tend to respond less well to pain treatments or management compared with people living without obesity. Mechanisms linking obesity and pain are complex and may include contributions from and interactions between physiological, behavioural, psychological, sociocultural, biomechanical and genetic factors. Our aim is to study the multidimensional pain profiles of people living with obesity, over time, in an attempt to better understand the relationship between obesity and pain.

Methods and analysis

This longitudinal observational cohort study will recruit (n=216) people living with obesity and who are newly attending three weight management services in Ireland. Participants will complete questionnaires that assess their multidimensional biopsychosocial pain experience at baseline and at 3, 6, 12 and 18 months post-recruitment. Quantitative analyses will characterise the multidimensional pain experiences and trajectories of the cohort as a whole and in defined subgroups.

Ethics and dissemination

The study protocol has been approved by the Ethics and Medical Research Committee of St Vincent’s Healthcare Group, Dublin, Ireland (reference no: RS21-059), the Galway Clinical Research Ethics Committee for Galway University Hospitals (refrence no: C.A. 2865), and the University College Dublin Human Research Ethics Committee (reference no: LS-E-22-41-Hinwood-Smart). Findings will be disseminated through peer-reviewed journals, conference presentations, public and patient advocacy groups, and social media.

Study registration

Open Science Framework Registration DOI:https://doi.org/10.17605/OSF.IO/QCWUE.
Equation of state of the running vacuum
Authors: Moreno-Pulido Cristian , Peracaula Joan Solà
Published: December 2022

Recent studies of quantum field theory in FLRW spacetime suggest that the cause of the speeding up of the universe is the running vacuum (RV), see Moreno-Pulido and Solà Peracaula (Eur Phys J C 82(6):551, 2022; Eur Phys J C 80(8):692, 2020). Appropriate renormalization of the energy-momentum tensor shows that the vacuum energy density is a smooth function of the Hubble rate and its derivatives: $$\rho _\textrm{vac}=\rho _\textrm{vac}(H, {\dot{H}},\ddot{H},\ldots )$$

ρ
vac

=

ρ
vac

(
H
,

H
˙

,

H
¨

,
…
)

. This is because in QFT the quantum scaling of $$\rho _\textrm{vac}$$

ρ
vac

with the renormalization point turns into cosmic evolution with H. As a result, any two nearby points of the cosmic expansion during the standard FLRW epoch are smoothly related through $$\delta \rho _\textrm{vac}\sim \mathcal{O}(H^2)$$

δ

ρ
vac

∼
O

(

H
2

)

. In our approach, what we call the ‘cosmological constant’ $$\Lambda $$
Λ
is just the nearly sustained value of $$8\pi G(H)\rho _\textrm{vac}(H)$$

8
π
G

(
H
)

ρ
vac

(
H
)

around (any) given epoch, where G(H) is the running gravitational coupling. In the present study, after summarizing the main QFT calculations supporting the RV approach, we focus on the calculation of the equation of state (EoS) of the RV for the entire cosmic history within such a QFT framework. In particular, in the very early universe, where higher (even) powers $$\rho _\textrm{vac}\sim \mathcal{O}(H^N)$$

ρ
vac

∼
O

(

H
N

)

($$N=4,6,\dots $$

N
=
4
,
6
,
⋯

) triggered inflation during a short period in which $$H=$$

H
=

const, the vacuum EoS is very close to $$w_\textrm{vac}=-1$$

w
vac

=
-
1

. This ceases to be true during the FLRW era, where it adopts the EoS of matter during the relativistic ($$w_\textrm{vac}=1/3$$

w
vac

=
1
/
3

) and non-relativistic ($$w_\textrm{vac}=0$$

w
vac

=
0

) epochs. Interestingly enough, we find that in the late universe the EoS becomes mildly dynamical and mimics quintessence, $$w_\textrm{vac}\gtrsim -1$$

w
vac

≳
-
1

. It finally asymptotes to $$-1$$

-
1

in the remote future, but in the transit the RV helps alleviating the $$H_0$$

H
0

and $$\sigma _8$$

σ
8

tensions.
Control Algorithm and Realization of Adaptive Two-Wheeled Robot
Authors: Zhao Jianlin
Published: December 2022

This system selects STC12C5A60S2 single chip microcomputer as the core processor to control the algorithm and balance state of the balance robot. The robot body is loaded with a gyroscope accelerometer sensor mpu6050 and a magnetoelectric encoder motor 330. The single chip microcomputer filters the data collected by the gyroscope and accelerometer, and processes the upper limit of the integral of the motor output value. Through the conditioning circuit, the sensor collects the horizontal offset angle of the robot body and the wheel rotation speed, and corrects the signal noise and zero offset, so as to complete the attitude monitoring. Using proportional integral differential algorithm, the positive feedback of speed loop and the negative feedback of angle loop are adjusted comprehensively to realize the robot body attitude correction. After debugging, the trolley can achieve self-regulation and balance without the severe impact of the external environment.
Intelligent Hyperparameter-Tuned Deep Learning-Based Android Malware Detection and Classification Model
Authors: Raphael Rincy , Mathiyalagan P.
Published: December 2022

Recently, Android applications have been playing a vital part in the everyday life as several services are offered via mobile applications. Due of its market dominance, Android is more at danger from malicious software, and this threat is growing. The exponential growth of malicious Android apps has made it essential to develop cutting-edge methods for identifying them. Despite the prevalence of a number of security-based approaches in the research, feature selection (FS) methods for Android malware detection methods still have to be developed. In this research, researchers provide a method for distinguishing malicious Android apps from legitimate ones by using a intelligent hyperparameter tuned deep learning based malware detection (IHPT-DLMD). Extraction of features and preliminary data processing are the main functions of the IHPT-DLMD method. The proposed IHPT-DLMD technique initially aims to determine the considerable permissions and API calls using the binary coyote optimization algorithm (BCOA)-based FS technique, which aids to remove the unnecessary features. Besides, bidirectional long short-term memory (Bi-LSTM) model is employed for the detection and classification of Android malware. Finally, the glowworm swarm optimization (GSO) algorithm is applied to optimize the hyperparameters of the BiLSTM model to produce effectual outcomes for Android application classification. This IHPT-DLMD method is checked for quality using a benchmark dataset and evaluated in several ways. The test data demonstrated overall higher performance of the IHPT-DLMD methodology in comparison to the most contemporary methods that are currently in use.
Two-dimensional quantum Bernoulli process and the related central limit theorem
Authors: Lu Yungang
Published: December 2022

In this paper, we introduce a quantum decomposition of a two-dimensional Bernoulli random variable [Formula: see text], where [Formula: see text], [Formula: see text] and [Formula: see text]. Based on this quantum decomposition, we defined the two-dimensional quantum Bernoulli process and set a corresponding central limit theorem, both in the sense of quantum moments and in the sense of characteristic function.
Insulator-to-metal transition in RCoO3 (R = Pr, Nd)
Authors: Saha Sujoy , Chanda Sadhan , Dutta Alo , Sinha T. P.
Published: December 2022

We report a straightforward tool to investigate insulator-metal transition in RCo[Formula: see text] (R = Pr, and Nd) nanoparticles prepared by a sol–gel technique. Thermogravimetric analysis (TGA) of the as-prepared gel is performed to get the lowest possible calcination temperature of RCo[Formula: see text] nanoparticles. The Rietveld refinement of the powder X-ray diffraction (XRD) patterns for both samples shows that the samples crystallize in the orthorhombic (Pnma) phase at room temperature. The particle size of the sample is determined by scanning electron microscopy. Ac conductivity of the materials is analyzed in the temperature range from 303 K to 673 K and in the frequency range from 42 Hz to 1.1 MHz. The insulator-to-metal transition of PrCo[Formula: see text] and NdCo[Formula: see text] is analyzed by ac impedance spectroscopy. DC resistivity measurement is also done to cross check the insulator-metal transition in RCo[Formula: see text] system.
Silicon-Containing Additives in Encapsulation of Phase Change Materials for Thermal Energy Storage
Authors: Lee Johnathan Joo Cheng , Lim Natalie Jia Xin , Wang Pei , Liu Hongfei , Wang Suxi , Lee Chi-Lik Ken , Kai Dan , Wei Fengxia , Ji Rong , Tan Beng Hoon , Ge Shaozhong , Suwardi Ady , Xu Jianwei , Loh Xian Jun , Zhu Qiang
Published: December 2022

Microencapsulated phase change materials (MEPCMs) are effective solutions for addressing the issue of leakage that phase change materials (PCMs) face in thermal energy storage devices. Their applications are ubiquitous as PCMs are utilized in industries such as logistics, construction, electronics, etc., thus, an efficient method to prevent problems such as leakage and poor thermal conductivity is to encapsulate the PCM which not only renders it leakage-proof but also impart mechanical strength and enhanced thermal properties. The application of silicon-based additives is one of the most studied methods to impart such desired properties. We discuss the silicon-containing compounds which are commonly employed in core-shell matrix of encapsulated PCMs, namely, siloxanes and silicone, silicon nitride, silicon carbide, silica/SiO2, and other silicon-containing additives as they are able to provide synergistic improvements and exhibit enhanced physical properties. In this review, the different silicon compounds used as additives or main shell matrix are discussed, the general fabrication of the MEPCM and its thermophysical properties will be briefly highlighted. Lastly, we also examine its application and performance in thermal storage and thermal management. We hope to provide a broader perspective of silicon-containing MEPCM for those who are working in the similar field of research.
Exports and Income Distribution: Is There a Kuznets Curve?
Authors: Yuhn Ky-hyang , Venturelli Henry
Published: December 2022

This study investigates the effects of exports on income per capita using a panel data set of 150 countries from 1990 to 2012. We have found that exports have differing effects on income distribution depending on different phases of economic development. As exports (measured as the percent of gross domestic product (GDP)) increase by a one percentage point, income per capita increases in low-income countries with an annual level of income per capita up to $5,000, but as a country’s income per capita increases beyond that level, the marginal effect of exports on income per capita becomes negative. The negative effect is strongest in middle-income countries with an annual level of income per capita between $5,000 and $10,000. Thus, our finding confirms the existence of a Kuznets curve in the relationship between exports and income distribution. We have further found that an increase in exports lead to an increase in income per capita until a country’s exports reach approximately 28% of GDP, after which a further increase in exports leads to a decrease in the marginal effect of exports on income per capita. We can conclude that exports benefit poorer countries more than richer countries.
WH
2
D
2
N
2
: Distributed AI-enabled OK-ASN Service for Web of Things
Authors: Liang Kun , Ma Ruhui , Hua Yang , Wang Hao , Hu Ningxin , Song Tao , Gao Honghao , Guan Haibing
Published: December 2022

Model data-driven ontology and knowledge presentation for evolving semantic Asian social networks (OK-ASN) is a critical strategy for web of things (WoT) services. Meanwhile, Deep Neural Network (DNN)-based OK-ASN service in WoT is growing rapidly. However, most DNN-based services cannot utilize the potential of WoT fully, as heterogeneity exists in WoT. Therefore, this article proposes a novel framework called Web-based Heterogeneous Hierarchical Distributed Deep Neural Network (

WH
2
D
2
N
2

) to deploy the DNNs for OK-ASN services on WoT, overcoming the heterogeneity. The architecture of the system and the designed Edge-Cloud-Joint execute scheme utilize heterogeneous devices to make DNN inference ubiquitous and output two types of results to meet various requirements. To bring robustness to OK-ASN services, a global scheduling is designed to arrange the workflow dynamically. The results of our experiments prove the efficiency of the execute scheme and the global scheduling in the system.
Occam: Optimal Data Reuse for Convolutional Neural Networks
Authors: Gondimalla Ashish , Liu Jianqiao , Thottethodi Mithuna , Vijaykumar T. N.
Published: December 2022

Convolutional neural networks (CNNs) are emerging as powerful tools for image processing in important commercial applications. We focus on the important problem of improving the latency of image recognition. While CNNs are highly amenable to prefetching and multithreading to avoid memory latency issues, CNNs’ large data – each layer’s input, filters, and output – poses a memory bandwidth problem. While previous work captures only some of the enormous data reuse,
full reuse
implies that the initial input image and filters are read once from off-chip and the final output is written once off-chip without spilling the intermediate layers’ data to off-chip. We propose
Occam
to capture full reuse via four contributions. First, we identify the necessary conditions for full reuse. Second, we identify the
dependence closure
as the sufficient condition to capture full reuse using the least on-chip memory. Third, because the dependence closure is often too large to fit in on-chip memory, we propose a dynamic programming algorithm that optimally partitions a given CNN to guarantee the least off-chip traffic at the partition boundaries for a given on-chip capacity. While tiling is well-known, our contribution determines the optimal cross-layer tiles. Occam’s partitions reside on different chips, forming a pipeline so that a partition’s filters and dependence closure remain on-chip as different images pass through (i.e., each partition incurs off-chip traffic only for its inputs and outputs). Finally, because the optimal partitions may result in an unbalanced pipeline, we propose
staggered asynchronous pipelines (STAPs)
that replicate bottleneck stages to improve throughput by staggering mini-batches across replicas. Importantly, STAPs achieve balanced pipelines
without
changing Occam’s optimal partitioning. Our simulations show that, on average, Occam cuts off-chip transfers by 21× and achieves 2.04× and 1.21× better performance, and 33% better energy than the base case, respectively. Using a field-programmable gate array (FPGA) implementation, Occam performs 6.1× and 1.5× better, on average, than the base case and Layer Fusion, respectively.
Resource Management in Cloud and Cloud-influenced Technologies for Internet of Things Applications
Authors: Jeyaraj Rathinaraja , Balasubramaniam Anandkumar , M.A. Ajay Kumara , Guizani Nadra , Paul Anand
Published: December 2022

The trend of adopting Internet of Things (IoT) in healthcare, smart cities, Industry 4.0, and so on is increasing by means of cloud computing, which provides on-demand storage and computation facilities over the Internet. To meet specific requirements of IoT applications, the cloud has also shifted its service offering platform to its next-generation models, such as fog, mist, and dew computing. As a result, the cloud and IoT have become part and parcel of smart applications that play significant roles in improving the quality of human life. In addition to the inherent advantages of advanced cloud models, to improve the performance of IoT applications further, it is essential to understand how the resources in the cloud and cloud-influenced platforms are managed to support various phases in the end-to-end IoT deployment. Considering this importance, in this article, we provide a brief description, a systematic review, and possible research directions on every aspect of resource management tasks, such as workload modeling, resource provisioning, workload scheduling, resource allocation, load balancing, energy management, and resource heterogeneity in such advanced platforms, from a cloud perspective. The primary objective of this article is to help early researchers gain insight into the underlying concepts of resource management tasks in the cloud for IoT applications.
DAGSizer: A Directed Graph Convolutional Network Approach to Discrete Gate Sizing of VLSI Graphs
Authors: Cheng Chung-Kuan , Holtz Chester , Kahng Andrew B. , Lin Bill , Mallappa Uday
Published: December 2022

The objective of a leakage recovery step is to make use of positive slack and reduce power by performing appropriate standard-cell swaps such as threshold-voltage (

V
th

) or channel-length reassignments. The resulting engineering change order netlist needs to be timing clean. Because this recovery step is performed several times in a physical design flow and involves long runtimes and high tool-license usage, previous works have proposed graph neural network–based frameworks that restrict feature aggregation to three-hop neighborhoods and do not fully consider the directed nature of netlist graphs. As a result, the intermediate node embeddings do not capture the complete structure of the timing graph. In this article, we propose
DAGSizer
, a framework that exploits the
directed acyclic
nature of timing graphs to predict cell reassignments in the discrete
gate sizing
task. Our DAGSizer (Sizer for DAGs) framework is based on a node ordering-aware recurrent message-passing scheme for generating the latent node embeddings. The generated node embeddings absorb the complete information from the fanin cone (predecessors) of the node. To capture the fanout information into the node embeddings, we enable a bidirectional message-passing mechanism. The concatenated latent node embeddings from the forward and reverse graphs are then translated to nodewise delta-delay predictions using a
teacher sampling
mechanism. With eight possible cell-assignments, the experimental results demonstrate that our model can accurately estimate design-level leakage recovery with an absolute relative error ε

model

under 5.4%. As compared to our previous work, GRA-LPO, we also demonstrate a significant improvement in the model mean squared error.
From the Editor: The Power of Overcoming Fear
Authors: Kelly Rob
Published: December 2022

Iis often via the scariest challenges that we grow the most (except those involving snakes). We often face them because we want something that is on the other side of them. It is during those times that we should be brave and scared. We need to believe in ourselves like we believe in others.
Understanding Surface and Bulk Electronic Structure of Li-ion Battery Cathodes Operated at Extreme Environment
Authors: Nagarajan Sudhan
Published: December 2022

Li-ion and Li metal batteries are widely used for portable devices due to their high gravimetric and volumetric energy densities and cyclability. However, overcharging and extreme discharging of the battery can lead to overheating and thermal runaway, while improper use can lead to fires and explosions. The volatility and flammability of the organic solvents (ethylene carbonate/dimethyl carbonate) used as electrolytes are the major sources of these thermal stability issues. Therefore, an alternative to flammable electrolytes, room temperature ionic liquids (RTILs) electrolyte chemistry is investigated due to its high thermal and electrochemical stability. Here, the fundamental understanding of developing high temperature Liion battery materials is evaluated using electrochemistry and depth-dependent the X-ray spectroscopy techniques.
Tech Highlights - Winter 2022
Authors: Pile Donald , McNulty David , Liu Zenghe , Liu Chao , Karuppaiah Chock , Gallaway Joshua
Published: December 2022

A collection of technology highlights pulled from recent papers published in ECS journals.
Acute sedentary behavior and cardiovascular disease research: standardizing the methodological posture
Authors: Paterson Craig , Higgins Simon , Sikk Merilin , Stone Keeron , Fryer Simon , Stoner Lee
Published: December 2022

Sedentary behavior has been identified as an independent predictor of future cardiovascular disease risk and all-cause mortality. To explain this association, a growing body of literature has sought to investigate the physiological underpinnings of this association with the goal of developing a biologically plausible model. In time, this biologically plausible model can be tested, and effective, translatable public health guidelines can be developed. However, to ensure that evidence across studies can be effectively synthesized, it is necessary to ensure their congruency and comparability. Although there are several key factors that should be considered and controlled across prolonged sitting studies, one pertinent issue is that of participant posture. There is currently a discourse within the literature regarding the posture that cardiovascular assessments are performed in and rest periods between posture transitions and subsequent measures. This perspectives piece makes the case for standardizing approaches across the research area and offers practical recommendations for future work.
Knowledge, Attitudes, and Beliefs about Relapse Prevention Research Involving Bupropion among Current and Former Pregnant Individuals Who Smoke
Authors: Adkins-Hempel Melissa , Japuntich Sandra J. , Thomas Janet , Fang Pearl , Harrison Katherine , Tavernier Rebecca L. Emery , Winickoff Jonathan P. , Kotlyar Michael , Allen Sharon , Ward Kenneth
Published: December 2022

Introduction. While many individuals quit smoking during pregnancy, most relapse within one year postpartum. Research into methods to decrease smoking relapse postpartum has been hampered by difficulties with recruitment. Method. We conducted individual interviews with pregnant women (N = 22) who were interested in quitting smoking while pregnant about their attitudes regarding smoking and quitting during pregnancy, clinical trial participation, and smoking cessation medication use. Results. Participants were aware of the risks of smoking while pregnant. Many wanted to quit smoking before delivery. Few used empirically supported treatments to quit. While research was viewed positively, interest in taking on new commitments postpartum and taking a medication to prevent relapse was low. Medication concerns were evident among most participants, especially among those planning to breastfeed. Further, several women noted medication was unnecessary, as they did not believe they would relapse postpartum. Financial incentives, childcare, and fewer and/or remote visits were identified as facilitators to participating in research. However, these factors did not outweigh women’s concerns about medication use and time commitments. Conclusions. Women are aware that quitting smoking during pregnancy and remaining smoke-free postpartum are important. However, beliefs that personal relapse risk is low and that medications are dangerous reduced enthusiasm for taking medication for postpartum relapse prevention. Future medication trials should educate women about the high likelihood of relapse, prepare to answer detailed questions about risks of cessation medications, and connect with participants’ clinicians. For new mothers, studies conducted remotely with few scheduled appointments would reduce barriers to participation.
Aircraft Trajectory Prediction Based on Bayesian Optimised Temporal Convolutional Network–Bidirectional Gated Recurrent Unit Hybrid Neural Network
Authors: Huang Jin , Ding Weijie
Published: December 2022

Efficient and accurate flight trajectory prediction is a key technology for promoting intelligent and informative air traffic management and improving the operational capabilities and predictability of air traffic. To address the problems in extracting hidden information from historical trajectory information, the approach must accurately select high-dimensional features related to the prediction target and overcome the short-term memory of the time series. Herein, we present a novel trajectory prediction model based on a dual-self-attentive (DSA)-temporal convolutional network (TCN)-bidirectional gated recurrent unit (BiGRU) neural network. In this model, the TCN provides highly stable training, high parallelism, and a flexible perceptual domain. The self-attentive mechanism of the TCN structure can focus on features that contribute the most to the output. After the TCN, the BiGRU network combined with the self-attentive mechanism is used to further bidirectionally mine the connections between the features and outputs of the trajectory sequence, and a Bayesian algorithm is used to optimise the hyperparameters of the model for optimal performance. A comparison and validation based on current well-known neural network models (i.e., CNN, TCN, GRU, and their variants) shows that the DSA-TCN-BiGRU model based on Bayesian hyperparameter optimisation has the best performance. Therefore, the improved predictive model is applicable and valuable, providing a basis for future decision trajectory-based operations.
Study of the Indoor Model Test and CEL Simulation of Jacking Force in the Vertical Tunnelling Method
Authors: Wei Xinjiang , Zhang Shuyuan , Wang Xiao , Lu Liangliang , Ding Zhi
Published: December 2022

The jacking force is one of the important parameters affecting the construction process in the vertical tunnelling method. To study the dynamic changing process of jacking force with the jacked distance and the influencing factors of the maximum jacking force, both the indoor model test and numerical simulation were conducted. In the model test, we investigated the influence of the height of the soil and water content. The results indicated that the higher the overburden height was, the greater the jacking force. Moreover, the water content enhanced the compressibility of the soil and had little effect on the maximum jacking force. Additionally, the coupled Eulerian–Lagrangian (CEL) approach was used to simulate the vertical jacking construction. In the numerical simulation, we investigated two construction factors (jacking speed and the standpipe outer diameter) and four soil parameters (cohesion, internal friction angle, elastic modulus, and Poisson’s ratio). Before that, the CEL simulation results were compared with test data to prove the rationality of the CEL approach, and the two were in good agreement. The results showed that among the six influence parameters, according to the influence degree on the maximum jacking force from large to low, the outer diameter of the standpipe, internal friction angle, cohesion, elastic modulus, jacking speed, and Poisson’s ratio were ranked. In addition, the jacking speed of numerical analysis was suggested to be 0.2 m/s. The research results in this paper can provide a reference for the construction of the vertical tunnelling method.
Towards Public Opinion Digital Twin: A Conceptual Prototype
Authors: He Jing , Qi Yuanbo , Feng Jie , Xiang Anling
Published: December 2022

This paper proposes a novel modeling concept, the “public opinion digital twin,” for public opinion analysis. The public opinion digital twin can be regarded as an experimental sandbox for social science. By digitalizing public data acquired from cyberspace into digital models, the modeling enables practical simulation, data analytics, scenario reflection, and decision support in a digital space with fine controllability, so that all possible evolutions of the research target can be analyzed. By simply inputting or filtering variables, any number of future scenarios are simulated, the effect models of each strategy for coping with public opinion are presented, and the optimized solution can be derived from continuous deep learning. If a robust digital twin is established and the required digital replicas are constantly updated, the system can perform risk assessments and trend predictions for social events. In this case, public opinion information can provide intelligent decision support for governments or enterprises and significantly facilitate social loss aversion, which will greatly advance the revolution in production, dissemination, and guidance.