bluuebunny/crossref_metadata_2025 huggingface dataset:
Cilostazol and isosorbide mononitrate for the prevention of progression of cerebral small vessel disease: baseline data and statistical analysis plan for the Lacunar Intervention Trial-2 (LACI-2) (ISRCTN14911850)
Authors: Bath Philip M , Mhlanga Iris , Woodhouse Lisa J , Doubal Fergus , Oatey Katherine , Montgomery Alan A , Wardlaw Joanna M
Published: September 2022

Background

Cerebral small vessel disease (SVD) causes lacunar strokes (25% of all ischaemic strokes), physical frailty and cognitive impairment and vascular and mixed dementia. There is no specific treatment to prevent progression of SVD.

Methods

The LACunar Intervention Trial-2 is an investigator-initiated prospective randomised open-label blinded-endpoint phase II feasibility study assessing cilostazol and isosorbide mononitrate for preventing SVD progression. We aimed to recruit 400 patients with clinically evident lacunar ischaemic stroke and randomised to cilostazol, isosorbide mononitrate, both or neither, in addition to guideline secondary ischaemic stroke prevention, in a partial factorial design. The primary outcome is feasibility of recruitment and adherence to medication; key secondary outcomes include: drug tolerability; recurrent vascular events, cognition and function at 1 year after randomisation; and safety (bleeding, falls, death). Data are number (%) and median (IQR).

Results

The trial commenced on 5 February 2018 and ceased recruitment on 31 May 2021 with 363 patients randomised, with the following baseline characteristics: average age 64 (56.0, 72.0) years, female 112 (30.9%), stroke onset to randomisation 79.0 (27.0, 244.0) days, hypertension 267 (73.6%), median blood pressures 143.0 (130.0, 157.0)/83.0 (75.0, 90.0) mm Hg, current smokers 67 (18.5%), educationally achieved end of school examinations (A-level) or higher 118 (32.5%), modified Rankin scale 1.0 (0.0, 1.0), National Institutes Health stroke scale 1.0 (1.4), Montreal Cognitive Assessment 26.0 (23.0, 28.0) and total SVD score on brain imaging 1.0 (0.0, 2.0). This publication summarises the baseline data and presents the statistical analysis plan.

The trial is currently in follow-up which will complete on 31 May 2022 with results expected in October 2022.

Trial registration number

ISRCTN14911850.
Point of care biliary ultrasound in the emergency department (BUSED) predicts final surgical management decisions
Authors: Hilsden Richard , Mitrou Nicholas , Hawel Jeff , Leeper Rob , Thompson Drew , Myslik Frank
Published: September 2022

Objectives

Gallstone disease is a common reason for emergency department (ED) presentation. Surgeons often prefer radiology department ultrasound (RUS) over point of care ultrasound (POCUS) because of perceived of unreliability. Our study was designed to test the hypothesis that POCUS is sufficient to guide the management of surgeons treating select cases of biliary disease as compared to RUS.

Methods

This was a prospective cohort study. Patients who presented to the ED with abdominal pain and findings of biliary disease on POCUS were included. The surgeon was then presented the case with POCUS only and recorded their management decision. Patients then proceeded to RUS, were followed through their stay, and analysis was performed to analyze the proportion of patients where the introduction of the RUS changed the management plan.

Results

100 patients were included in this study, and all received both POCUS and RUS. Depending on the surgeons’ POCUS based management decisions, the patients were divided into three groups: (1) surgery, (2) duct clearance, (3) no surgery. Total bilirubin was 34±22 mmol/L in the duct clearance group vs 8.4±6.5 mmol/L and 16±12 mmol/L in the surgery and no surgery groups, respectively (p<0.05). POCUS results showed 68 patients would have been offered surgery, 21 offered duct clearance, and 11 no surgery. In 90% of cases, the introduction of RUS did not change management. The acute care surgeons elected to operate on patients more frequently than other surgical subspecialties (p<0.05).

Conclusions

This study showed that fewer than 10% of patients with biliary disease seen on POCUS had a change in surgical decision-making based on the addition of RUS imaging. In uncomplicated cases of biliary disease, relying on POCUS imaging for surgical decision-making has the potential to improve patient flow.

Level of evidence

II Prospective Cohort Study.
Influence of aerially seeded Pinus massoniana plantations on soil quality in severely eroded and degraded land of subtropical China
Authors: Zhan Changyan , Pan Ping , Ouyang Xunzhi , Ning Jinkui , Xu Li , Ju Linjing
Published: September 2022

Vegetation restoration is widely used to reduce soil erosion and control soil degradation, which is conducive to improving soil quality. Aerial seeding is an effective vegetation recovery method that has been applied in large areas with severe soil erosion in China. Pinus massoniana is not only a typical native coniferous tree species, but also a pioneer tree species for vegetation recovery in subtropical China. This study evaluates the soil quality of aerially seeded P. massoniana plantations of different stand ages and examines the vegetation factors affecting soil quality. Principal component analysis and Pearson correlation analysis were used to determine the minimum data set (MDS) for developing a soil quality index. The relationship between soil quality and vegetation factors was analyzed using redundancy analysis. The MDS was established with soil bulk density, field water capacity, non-capillary porosity, total nitrogen, soil organic matter, and pH. The results showed that the soil quality significantly increased with vegetation recovery age at 0–20 and 20–50 cm soil depths. The soil quality of the surface layer was mainly affected by understory vegetation and litter, whereas that of the deep layer was mainly affected by trees. Therefore, the appropriate management of P. massoniana forest, achieved by appropriately extending forest management rotation, replanting broad-leaved trees, and minimizing the damage to understory vegetation and litter, is essential for effectively improving soil quality.
Impact of the free-streaming neutrinos to the second order induced gravitational waves
Authors: Zhang Xukun , Zhou Jing-Zhi , Chang Zhe
Published: September 2022

The damping effect of the free-streaming neutrinos on the second order gravitational waves is investigated in detail. We solve the Boltzmann equation and give the anisotropic stress induced by neutrinos to second order. The first order tensor and its coupling with scalar perturbations induced gravitational waves are considered. We give the analytic equations of the damping kernel functions and finally obtain the energy density spectrum. The results show that the free-streaming neutrinos suppress the density spectrum significantly for low frequency gravitational waves and enlarge the logarithmic slopenin the infrared region ($$k \ll k_*$$k≪k∗) of the spectrum. For the spectrum of$$k_*\sim 10^{-7}\,\hbox {Hz}$$k∗∼10-7Hz, the damping effect in the range of$$k<k_*$$k<k∗is significant. The combined effect of the first and second order could reduce the amplitude by$$30\%$$30%and makenjump from 1.54 to 1.63 at$$k\sim 10^{-9}\,\hbox {Hz}$$k∼10-9Hz, which may be probed by the pulsar timing arrays (PTA) in the future.
The structure of the ultrarelativistic prompt emission phase and the properties of the black hole in GRB 180720B
Authors: Rastegarnia F. , Moradi R. , Rueda J. A. , Ruffini R. , Li Liang , Eslamzadeh S. , Wang Y. , Xue S. S.
Published: September 2022

In analogy with GRB 190114C, we here analyze the ultrarelativistic prompt emission (UPE) of GRB 180720B observed in the rest-frame time interval $$t_{\mathrm{rf}}=4.84$$

t
rf

=
4.84

–10.89 s by Fermi-GBM. We reveal the UPE hierarchical structure from the time-resolved spectral analysis performed in time sub-intervals: the spectrum in each shorter time interval is always fitted by a composite blackbody plus cutoff power-law model. We explain this structure with the inner engine of binary-driven hypernova (BdHN) model operating in a quantum electrodynamics (QED) regime. In this regime, the electric field induced by the gravitomagnetic interaction of the newborn Kerr BH with the surrounding magnetic field is overcritical, i.e., $$|\mathbf{E}|\ge E_c$$

|
E
|

≥

E
c

, where $$E_c=m_e^2 c^3/(e\hbar )$$

E
c

=

m
e
2

c
3

/

(
e
ħ
)

. The overcritical field polarizes the vacuum leading to an $$e^+~e^-$$

e
+

e
-

pair plasma that loads baryons from the surroundings during its expansion. We calculate the dynamics of the self-acceleration of the pair-electromagnetic-baryon (PEMB) pulses to their point of transparency. We characterize the quantum vacuum polarization process in the sequences of decreasing time bins of the UPE by determining the radiation timescale, Lorentz factors, and transparency radius of the PEMB pulses. We also estimate the strength of the surrounding magnetic field $$\sim 10^{14}$$

∼

10
14

G, and obtain a lower limit to the BH mass, $$M=2.4~M_\odot $$

M
=
2.4

M
⊙

, and correspondingly an upper limit to the spin, $$\alpha = 0.6$$

α
=
0.6

, from the conditions that the UPE is powered by the Kerr BH extractable energy and its mass is bound from below by the NS critical mass.
A Composite Indicator Methodology to Rank National Olympic Committees
Authors: Xu Yang , Fu Yelin , Lai Kin Keung
Published: September 2022

This paper proposes a composite indicator methodology to rank National Olympic Committees (NOCs) by considering only the medals won at both Summer and Winter Olympic games. The lexicographic and sum ranking systems at both Summer and Winter Olympics are comprehensively investigated to create the preliminary decision matrix for constructing composite indicators. Then we investigate the preferential difference and preferential priority for better reflecting the preference structures of the sub-indicators, and thereby obtain a revised decision matrix. The SMAA-2 is employed to implement the composite indicator construction based upon the revised decision matrix. An empirical study is performed to demonstrate the applicability of our methodology, using the data set that is composed of 28 NOCs who have participated in both the Rio 2016 Summer Olympic Games and the PyeongChang 2018 Winter Olympics. The Spearman’s rank correlation coefficient and the satisfaction index are calculated to justify the merits of the proposed methodology.
Consensus formation in first-order graphon models with time-varying topologies
Authors: Bonnet Benoît , Duteil Nastassia Pouradier , Sigalotti Mario
Published: September 2022

In this paper, we investigate the asymptotic formation of consensus for several classes of time-dependent cooperative graphon dynamics. After motivating the use of this type of macroscopic models to describe multi-agent systems, we adapt the classical notion of scrambling coefficient to this setting, and leverage it to establish sufficient conditions ensuring the exponential convergence to consensus with respect to the [Formula: see text]-norm topology. We then shift our attention to consensus formation expressed in terms of the [Formula: see text]-norm, and prove three different results for symmetric, balanced and strongly connected topologies, which involve a suitable generalisation of the notion of algebraic connectivity to this infinite-dimensional framework. We then show that, just as in the finite-dimensional setting, the notion of algebraic connectivity that we propose encodes information about the connectivity properties of the underlying interaction topology. We finally use the corresponding results to shed some light on the relation between [Formula: see text]- and [Formula: see text]-consensus formation, and illustrate our contributions by a series of numerical simulations.
A stochastic model of grain boundary dynamics: A Fokker–Planck perspective
Authors: Epshteyn Yekaterina , Liu Chun , Mizuno Masashi
Published: September 2022

Many technologically useful materials are polycrystals composed of small monocrystalline grains that are separated by grain boundaries of crystallites with different lattice orientations. The energetics and connectivities of the grain boundaries play an essential role in defining the effective properties of materials across multiple scales. In this paper we derive a Fokker–Planck model for the evolution of the planar grain boundary network. The proposed model considers anisotropic grain boundary energy which depends on lattice misorientation and takes into account mobility of the triple junctions, as well as independent dynamics of the misorientations. We establish long time asymptotics of the Fokker–Planck solution, namely the joint probability density function of misorientations and triple junctions, and closely related the marginal probability density of misorientations. Moreover, for an equilibrium configuration of a boundary network, we derive explicit local algebraic relations, a generalized Herring Condition formula, as well as formula that connects grain boundary energy density with the geometry of the grain boundaries that share a triple junction. Although the stochastic model neglects the explicit interactions and correlations among triple junctions, the considered specific form of the noise, under the fluctuation–dissipation assumption, provides partial information about evolution of a grain boundary network, and is consistent with presented results of extensive grain growth simulations.
Neurons-Samples Theorem
Authors: Liu G. R.
Published: September 2022

Artificial neural network (NN) has become one of the most widely used machine learning (ML) models for problems in science and engineering, including the fast-developing artificial intelligence (AI) technology. In training an NN model for a problem, one of the most frequently asked questions is how many neurons or layers of neurons should be used for a given dataset with a number of samples (or data points). This paper provides an answer to this critical question, by presenting a Neurons-Samples Theorem, which states, in short, that the number of neurons should be equal or less than the number of samples used to train the NN.
How Does Climate Policy Uncertainty Affect Excessive Corporate Debt? The Case of China
Authors: Ren Xiaohang , Qin Jianing , Dong Kangyin
Published: September 2022

This paper explores the direct and indirect relationship between climate policy uncertainty and excessive corporate debt, and focuses on the moderating effect of financing constraints. We use the climate policy uncertainty index to represent climate policy uncertainty, and use the Kaplan and Zingales (KZ) index to represent financing constraints. Our study employs data from Chinese non-financial listed companies for the period 2007–2020. The results show that climate policy uncertainty not only directly curbs excessive debt, but also indirectly reduces excessive debt by increasing financing constraints. This direct weakening effect is more pronounced in non-state-owned enterprises, high-tech enterprises, and high-carbon enterprises. Moreover, the financing constraints channel is more effective in state-owned enterprises, high-tech enterprises, and high-carbon enterprises. Furthermore, due to the actual situation in China, the direct weakening effect of climate policy uncertainty is very obvious in the central region, while the indirect effect through the financing constraints channel is most obvious in the western region. These empirical findings will help policymakers, managers, and financial institutions to reconsider financing risk under climate policy uncertainty.
Soft Directed Graphs, Their Vertex Degrees, Associated Matrices and Some Product Operations
Authors: Jose Jinta , George Bobin , Thumbakara Rajesh K.
Published: September 2022

D. Molodtsov proposed soft set theory in 1999 as a general mathematical framework for dealing with uncertain data. Many academics are now applying soft set theory in decision-making problems. In graph theory, a directed graph is a graph made up of vertices connected by directed edges, also known as arcs. Electrical circuits, shortest routes, social links and a variety of other problems can all be analyzed and solved using directed graphs. In this paper, we introduce soft directed graphs by applying the concept of soft set to directed graphs. Soft directed graphs provide a parameterized point of view for directed graphs. We define and investigate the degrees and matrices associated with a soft directed graph. We also introduce several product operations in soft directed graphs and analyze some of their features.
Robust Revenue Maximization Under Minimal Statistical Information
Authors: Giannakopoulos Yiannis , Poças Diogo , Tsigonias-Dimitriadis Alexandros
Published: September 2022

We study the problem of multi-dimensional revenue maximization when selling
m
items to a buyer that has additive valuations for them, drawn from a (possibly correlated) prior distribution. Unlike traditional Bayesian auction design, we assume that the seller has a very restricted knowledge of this prior: they only know the mean μ

j

and an upper bound σ

j

on the standard deviation of each item’s marginal distribution. Our goal is to design mechanisms that achieve good revenue against an ideal optimal auction that has
full
knowledge of the distribution in advance. Informally, our main contribution is a tight quantification of the interplay between the dispersity of the priors and the aforementioned robust approximation ratio. Furthermore, this can be achieved by very simple selling mechanisms.

More precisely, we show that selling the items via separate price lotteries achieves an
O
(log
r
) approximation ratio where
r
= max

j

(σ

j

/μ

j

) is the maximum coefficient of variation across the items. To prove the result, we leverage a price lottery for the single-item case. If forced to restrict ourselves to deterministic mechanisms, this guarantee degrades to
O
(
r
2
). Assuming independence of the item valuations, these ratios can be further improved by pricing the full bundle. For the case of identical means and variances, in particular, we get a guarantee of
O
(log (
r/m
)) that converges to optimality as the number of items grows large. We demonstrate the optimality of the preceding mechanisms by providing matching lower bounds. Our tight analysis for the single-item deterministic case resolves an open gap from the work of Azar and Micali (ITCS’13).

As a by-product, we also show how one can directly use our upper bounds to improve and extend previous results related to the
parametric auctions
of Azar et al. (SODA’13).
Self-supervised Discriminative Representation Learning by Fuzzy Autoencoder
Authors: Yang Wenlu , Wang Hongjun , Zhang Yinghui , Liu Zehao , Li Tianrui
Published: September 2022

Representation learning based on autoencoders has received great concern for its potential ability to capture valuable latent information. Conventional autoencoders pursue minimal reconstruction error, but in most machine learning tasks such as classification and clustering, the discrimination of feature representation is also important. To address this limitation, an enhanced self-supervised discriminative fuzzy autoencoder (FAE) is innovatively proposed, which focuses on exploring information within data to guide the unsupervised training process and enhancing feature discrimination in a self-supervised manner. In FAE, fuzzy membership is applied to provide a means of self-supervised, which allows FAE can not only utilize AE’s outstanding representation learning capabilities but can also transform the original data into another space with improved discrimination. First, the objective function corresponding to FAE is proposed by reconstruction loss and clustering oriented loss simultaneously. Subsequently, Mini-Batch Gradient Descent is applied to infer the objective function and the detailed process is illustrated step by step. Finally, empirical studies on clustering tasks have demonstrated the superiority of FAE over the state of the art.
AutoML Loss Landscapes
Authors: Pushak Yasha , Hoos Holger
Published: September 2022

As interest in machine learning and its applications becomes more widespread, how to choose the best models and hyper-parameter settings becomes more important. This problem is known to be challenging for human experts, and consequently, a growing number of methods have been proposed for solving it, giving rise to the area of automated machine learning (AutoML). Many of the most popular AutoML methods are based on Bayesian optimization, which makes only weak assumptions about how modifying hyper-parameters effects the loss of a model. This is a safe assumption that yields robust methods, as the
AutoML loss landscapes
that relate hyper-parameter settings to loss are poorly understood. We build on recent work on the study of one-dimensional slices of algorithm configuration landscapes by introducing new methods that test
n
-dimensional landscapes for statistical deviations from uni-modality and convexity, and we use them to show that a diverse set of AutoML loss landscapes are highly structured. We introduce a method for assessing the significance of hyper-parameter partial derivatives, which reveals that most (but not all) AutoML loss landscapes only have a small number of hyper-parameters that interact strongly. To further assess hyper-parameter interactions, we introduce a simplistic optimization procedure that assumes each hyper-parameter can be optimized independently, a single time in sequence, and we show that it obtains configurations that are statistically tied with optimal in all of the
n
-dimensional AutoML loss landscapes that we studied. Our results suggest many possible new directions for substantially improving the state of the art in AutoML.
Elastically Augmenting the Control-path Throughput in SDN to Deal with Internet DDoS Attacks
Authors: Dai Yuanjun , Wang An , Guo Yang , Chen Songqing
Published: September 2022

Distributed denial of service (DDoS) attacks have been prevalent on the Internet for decades. Albeit various defenses, they keep growing in size, frequency, and duration. The new network paradigm, Software-defined networking (SDN), is also vulnerable to DDoS attacks. SDN uses logically centralized control, bringing the advantages in maintaining a global network view and simplifying programmability. When attacks happen, the control path between the switches and their associated controllers may become congested due to their limited capacity. However, the data plane visibility of SDN provides new opportunities to defend against DDoS attacks in the cloud computing environment. To this end, we conduct measurements to evaluate the throughput of the software control agents on some of the hardware switches when they are under attacks. Then, we design a new mechanism, called
Scotch
, to enable the network to scale up its capability and handle the DDoS attack traffic. In our design, the congestion works as an indicator to trigger the mitigation mechanism.
Scotch
elastically scales up the control plane capacity by using an Open vSwitch-based overlay.
Scotch
takes advantage of both the high control plane capacity of a large number of vSwitches and the high data plane capacity of commodity physical switches to increase the SDN network scalability and resiliency under abnormal (e.g., DDoS attacks) traffic surges. We have implemented a prototype and experimentally evaluated
Scotch
. Our experiments in the small-scale lab environment and large-scale GENI testbed demonstrate that
Scotch
can elastically scale up the control channel bandwidth upon attacks.
Decentralized Online Learning: Take Benefits from Others’ Data without Sharing Your Own to Track Global Trend
Authors: Wu Wendi , Li Zongren , Zhao Yawei , Yu Chen , Zhao Peilin , Liu Ji , He Kunlun
Published: September 2022

Decentralized online learning (online learning in decentralized networks) has been attracting more and more attention, since it is believed that decentralized online learning can help data providers cooperatively better solve their online problems without sharing their private data to a third party or other providers. Typically, the cooperation is achieved by letting the data providers exchange their models between neighbors, e.g., recommendation model. However, the best regret bound for a decentralized online learning algorithm is 𝒪(
n
√
T
), where
n
is the number of nodes (or users) and
T
is the number of iterations. This is clearly insignificant, since this bound can be achieved
without
any communication in the networks. This reminds us to ask a fundamental question:
Can people really get benefit from the decentralized online learning by exchanging information?
In this article, we studied when and why the communication can help the decentralized online learning to reduce the regret. Specifically, each loss function is characterized by two components: the adversarial component and the stochastic component. Under this characterization, we show that decentralized online gradient enjoys a regret bound

\( {\mathcal {O}(\sqrt {n^2TG^2 + n T \sigma ^2})} \)

, where
G
measures the magnitude of the adversarial component in the private data (or equivalently the local loss function) and σ measures the randomness within the private data. This regret suggests that people can get benefits from the randomness in the private data by exchanging private information. Another important contribution of this article is to consider the dynamic regret—a more practical regret to track users’ interest dynamics. Empirical studies are also conducted to validate our analysis.
A New Similarity Space Tailored for Supervised Deep Metric Learning
Authors: Barros Pedro , Queiroz Fabiane , Figueiredo Flávio , Santos Jefersson A. Dos , Ramos Heitor
Published: September 2022

We propose a novel deep metric learning method. Differently from many works in this area, we define a novel latent space obtained through an autoencoder. The new space, namely S-space, is divided into different regions describing positions where pairs of objects are similar/dissimilar. We locate makers to identify these regions and estimate the similarities between objects through a kernel-based Cauchy distribution to measure the markers’ distance and the new data representation. In our approach, we simultaneously estimate the markers’ position in the S-space and represent the objects in the same space. Moreover, we propose a new regularization function to prevent similar markers from collapsing altogether. Our method emphasizes the group property (separability) while preserving instance representativity. We present evidence that our proposal can represent complex spaces, for instance, when groups of similar objects are located in disjoint regions. We compare our proposal to nine different distance metric learning approaches (four of them are based on deep learning) on 28 real-world heterogeneous datasets. According to the four quantitative metrics used, our method overcomes all of the nine strategies from the literature.
APTHunter: Detecting Advanced Persistent Threats in Early Stages
Authors: Mahmoud Moustafa , Mannan Mohammad , Youssef Amr
Published: September 2022

We propose APTHunter, a system for prompt detection of Advanced and Persistent Threats (APTs) in early stages. We provide an approach for representing the indicators of compromise that appear in the cyber threat intelligence reports and the relationships among them as provenance queries that capture the attacker’s malicious behavior. We use the kernel audit log as a reliable source for system activities and develop an optimized whole system provenance graph that provides the causal relationships and information flows among system entities in a compact format. Then, we model the threat hunting as a behavior match problem by applying provenance queries to the optimized provenance graph to find any hits as indicators of an APT attack. We evaluate APTHunter on adversarial engagements from DARPA over different OS platforms, as well as real-world APT campaigns. Based on our experimental results, APTHunter promptly and reliably detects attack artifacts in early stages.
One Health for All: Advancing Human and Ecosystem Health in Cities by Integrating an Environmental Justice Lens
Authors: Murray Maureen H. , Buckley Jacqueline , Byers Kaylee A. , Fake Kimberly , Lehrer Elizabeth W. , Magle Seth B. , Stone Christopher , Tuten Holly , Schell Christopher J.
Published: September 2022

We are facing interwoven global threats to public health and ecosystem function that reveal the intrinsic connections between human and wildlife health. These challenges are especially pressing in cities, where social-ecological interactions are pronounced. The One Health concept provides an organizing framework that promotes the health and well-being of urban communities and ecosystems. However, for One Health to be successful, it must incorporate societal inequities in environmental disamenities, exposures, and policy. Such inequities affect all One Health interfaces, including the distribution of ecosystem services and disservices, the nature and frequency ofhuman–wildlife interactions, and legacies of land use. Here, we review the current literature on One Health perspectives, pinpoint areas in which to incorporate an environmental justice lens, and close with recommendations for future work. Intensifying social, political, and environmental unrest underscores a dire need for One Health solutions informed by environmental justice principles to help build healthier, more resilient cities.
Transcription-Translation Coupling in Bacteria
Authors: Blaha Gregor M. , Wade Joseph T.
Published: September 2022

In bacteria, transcription and translation take place in the same cellular compartment. Therefore, a messenger RNA can be translated as it is being transcribed, a process known as transcription-translation coupling. This process was already recognized at the dawn of molecular biology, yet the interplay between the two key players, the RNA polymerase and ribosome, remains elusive. Genetic data indicate that an RNA sequence can be translated shortly after it has been transcribed. The closer both processes are in time, the less accessible the RNA sequence is between the RNA polymerase and ribosome. This temporal coupling has important consequences for gene regulation. Biochemical and structural studies have detailed several complexes between the RNA polymerase and ribosome. The in vivo relevance of this physical coupling has not been formally demonstrated. We discuss how both temporal and physical coupling may mesh to produce the phenomenon we know as transcription-translation coupling.
Bio-Waste Derived Honeycomb Structured Activated Carbons as Anode Materials for Lead-Carbon Hybrid Ultracapacitors
Authors: Muduli Sadananda , Das Chakraborty Rupan , Verma Pramod , Martha Surendra K.
Published: September 2022

Lead-carbon hybrid ultracapacitors (Pb-C HUC) are the solution to the sulfation issue of lead-acid batteries. The Pb-C HUCs are of much interest due to the aqueous system with longer cycle life and higher power density. Here, honeycomb structured porous activated carbons with 1790 m2 g−1 of surface area were synthesized from Carica papaya biowaste by chemical treatment followed by carbonization at 800 °C (PAC-800). PAC-800 composite electrode delivers a specific capacitance of 250 F g−1 at 1 Ag−1 and has 10000 stable cycle life in 4.5 M H2SO4. Further, a kinetic study of the PAC-800 electrode illustrates that at 2 mV s−1, they show 61% of capacitive and 39% of pseudocapacitive charge storage. Pb-C HUCs fabricated using in situ activated PbO2 sheet as cathode and PAC-800 composite electrode as anode delivers 390 F g−1 at 1 A g−1 and have 93% capacitance retention over 15000 cycles at 5 A g−1. Further, the current Pb-C HUC results are compared with commercially available high surface area (2484 m2 g−1) carbons based Pb-C HUCs. This work illustrates an easy, scalable synthesis root for biowaste carbons and their electrochemical performance in Pb-C HUCs, which is on par with commercial high surface area carbons.
Facile One-Pot Synthesis of α–MnO2/CeO2 Nanowires for Mg-Air Batteries
Authors: Liu Hui , Song Juemin , Zhang Jiaxi , Li Zheng , Fang Hongjie , Zhang Qian , He Xuehua , Lu Changbo , Xu Wanli , Yu Kun
Published: September 2022

In this work, we synthesized MnO2/CeO2 electrocatalysts by in situ decoration of α–MnO2 with CeO2 particles during a one-step hydrothermal process. The morphology, composition, and electrochemical properties were studied in the context of application to the oxygen reduction reaction (ORR) and Mg-air battery. According to the results, α–MnO2/CeO2 microfibres exhibited better ORR performance than α–MnO2 microfibres due to the synergistic result between the introduction of Ce3+ in CeO2 lattice and the enhancement of Mn3+ content in MnO2 lattice. α–MnO2/CeO2 microfibres provided a higher surface area and more catalytic active sites than α–MnO2 microfibres by controlling the molar ratio of Ce3+/Mn7+ for the precursor. When the mole ratio of Ce3+ and Mn7+ in the precursors was 10%, the four-electron transfer process of the MnO2/CeO2 microfibres (MC-140-12-10) was found to be similar to that of the 20 wt% Pt/C commercial catalysts. MC-140-12-10 microfibres also showed the excellent long-term stability after 25,000 s and superior Mg–air battery performances than α–MnO2. Hence, the work paves the way for developing Mg-air batteries through a simple synthesis and cost-effective ORR catalyst.
A Polak-Ribière-Polyak Conjugate Gradient Algorithm Optimized Broad Learning System for Lithium-ion Battery State of Health Estimation
Authors: Gu Tianyu , Wang Dongqing , Li Yuxiang
Published: September 2022

Accurate state of health (SOH) estimation plays a significant role in the battery management system. This paper investigates a Polak-Ribière-Polyak conjugate gradient (PRPCG) algorithm optimized broad learning system (BLS) for lithium-ion battery SOH estimation. Firstly, effective health indicators (HIs) are extracted from the voltage curve in the constant current charge process. Secondly, a hybrid four layers BLS structure with mapped feature nodes and enhancement nodes connecting to the output is established to build both the linear and nonlinear relationships between the HIs and SOH, in which only the output weights require to be trained. Again, the PRPCG algorithm is adopted for searching optimal output weights without matrix inverse calculation during the training process. Furthermore, certain Gaussian noises are added to enhance the training data for solving the locally low accuracy problem. Finally, under the Oxford battery degradation data set, experiments validate the investigated algorithm has high accuracy in SOH estimation with the mean absolute error below 1%. The enhanced data can efficiently improve the model generalization ability.
Electrochemical models: methods and applications for safer lithium-ion battery operation
Authors: Sarkar Sankhadeep , Zohra Halim S. , El-Halwagi Mahmoud M. , Khan Faisal I.
Published: September 2022

Emphasis on clean energy has led to a widespread focus on lithium-ion batteries. However, a major obstacle is their degradation with several cycles or calendar aging. Battery Management System relies on an essential model-based algorithm to protect the battery from operating outside the safety limit. Thus, this work attempts to answer important research questions on battery models: (1) Are physics-based electrochemical models (EM) robust enough to identify internal cell degradation and abnormal battery behavior? (2) How are the structural simplifications and mathematical order reductions imposed on the EMs and what are their trade-offs? (3) How to apply simplified EM for safer and more efficient battery operation? (4) What are the prospects and obstacles of employing EM-based algorithms in the future? This paper presents a detailed analysis of EM from a modeling and application perspective. The paper introduces battery operating mechanisms, typical failures, and their effects. Followed by an analysis of full order EM (Pseudo 2-Dimensional), and further classification into simpler and advanced reduced-order models. The study demonstrates the gaps in theoretical understanding and their implementation for real-time battery operations such as in thermal management, energy utilization, and fault diagnosis and prognosis.
Mathematical Model for SEI Growth under Open-Circuit Conditions
Authors: Madi Reddy Shiv Krishna , Shang Wei , White Ralph E.
Published: September 2022

A solid electrolyte interphase (SEI) growth model is developed in a mixed mode that contains solvent diffusion through the SEI layer and corresponding solvent reduction kinetics at the SEI/electrode interface. The governing equations are solved by the Landau transformation, which makes the moving layer fixed to predict the open circuit potential, SEI layer thickness, and capacity loss. The estimated parameters fitted with experimental data from the literature are computed using COMSOL and MATLAB. Results show that the mixed mode model predicts lower capacity loss and thinner SEI layer due to its growth under open circuit conditions than previously reported by others.
Comparative Electrochemical Study of Li+, Na+ and Mg2+-ion Insertion into VO2(B) from Aqueous Nitrate Solutions
Authors: Cvjetićanin Nikola , Simatović Ivana Stojković
Published: September 2022

The insertion of Li+, Na+ and Mg2+ into nanostructured VO2(B) from aqueous nitrate solutions was sudied by using cyclic voltammetry (CV) and galvanostaic (GS) cycling. CV experiments demonstrated fast and very stable insertion/deinsertion process of all three ions at scan rates 10–50 mV·s−1, but showed that extraction of Na+ and Mg2+ ion happens in wider voltage range and is more complex. GS cycling of nanostructured VO2(B), at current rates 200, 500 and 1000 mA·g−1, showed fairly large capacity values for all cations, with the highest Coulombic efficiency at the highest current rate. The GS cycling confirmed the two-step extraction of Mg2+-ions, while in the case of Na+-ions the extraction occurred more like a one step process.
Epitaxial Electrodeposition of Wide Bandgap Cuprous Bromide on Silver via a Silver Bromide Buffer Layer
Authors: Luo Bin , Zhang Xiaoting , Tubbesing John Z. , Banik Avishek , Switzer Jay A.
Published: September 2022

Cuprous halides are an important class of wide bandgap p-type semiconductors used in opto-electronics. Cuprous bromide (CuBr) shows potential for short-wavelength devices due to a large exciton binding energy (108 meV) and near-ultraviolet bandgap (3.1 eV). However, the growth of high-quality epitaxial CuBr films by electrodeposition has remained a challenge. Here, we introduce a low-cost electrochemical procedure for producing epitaxial CuBr(111) on a Ag(111) substrate by a [111]-oriented silver bromide (AgBr) buffer layer. The AgBr buffer layer forms during the electrodeposition of the CuBr. The mismatch between CuBr(111) and AgBr(111) is −1.3%. A plausible mechanism for nucleation and growth of the epitaxial CuBr is proposed. X-ray techniques including high resolution X-ray diffraction and X-ray pole figures are used to determine the epitaxial relationship. CuBr(100) is also produced on a Ag(100) surface by a AgBr(100) buffer layer that is rotated in-plane 45° relative to the Ag(100) surface. This in-plane rotation reduces the lattice mismatch from +39.5% for an unrotated film to −1.4% for a 45° rotated film.
Effect of Chloride and Sulfate Ions on Electrodeposition and Surface Properties of Alloys Produced from Zinc-Nickel-Manganese Gluconate Baths
Authors: Chat-Wilk Karolina , Rudnik Ewa , Włoch Grzegorz
Published: September 2022

Alloys were potentiostatically codeposited from gluconate baths containing zinc, nickel and manganese chlorides and/or sulfates. The electrodeposits were characterized in terms of their chemical (XRF, EDS) and phase (XRD, ASA) compositions, surface morphology (SEM), wettability (WCA, SFE) and corrosion resistance in neutral and acid media (linear polarization, immersion test). Morphology and composition of the alloys were mainly dependent on deposition potential, while effect of bath speciation was less emphasized. Multiphase ternary alloys were produced only at potentials more negative than −1.5 V (Ag/AgCl). Codeposition of the metals was anomalous and run according to instantaneous nucleation model, but at more electronegative potentials and in a presence of chloride ions transition progressive-instantaneous nucleation stages were observed. Comparison of surface wettability of as-plated and air-stored alloys showed improved (super)hydrophobicity caused by spontaneous oxidation of zinc-rich alloys. Surface free energies of the deposits were discussed. It was found that sulfate anions exhibited distinct effect on cathodic processes demonstrated by higher deposit masses, lower manganese percentages in the alloys, formation of more coarse and compact hydrophobic deposits of high corrosion resistance in neutral solution.
Mechanical response of cardiac microtissues to acute localized injury
Authors: Das Shoshana L. , Sutherland Bryan P. , Lejeune Emma , Eyckmans Jeroen , Chen Christopher S.
Published: September 2022

We report an in vitro cardiac injury model that uses a high-powered laser to induce regional cell death and a focal fibrotic response within a human-engineered cardiac microtissue. The model captures the effects of acute injury on tissue response, remodeling, and electromechanical recovery in both the damaged region and surrounding healthy tissue, modeling similar changes to contractile function observed in vivo following myocardial infarction.
Pain Management of Hallux Valgus Surgery Is Achieved by Cocktail Therapy
Authors: Xie Jiewei , Zhu Junlang , Xu Yiyin , Chen Mengli , Chen Haiyun , Yuan Kaiping , Lin Dingkun
Published: September 2022

Background. Hallux valgus is a relatively common forefoot disease in clinical practice. The aim of our study was to assess the role of local cocktail drugs and postoperative pain after hallux valgus surgery. Methods. A retrospective case-control study was conducted to analyze 75 moderate to severe hallux valgus patients from June 1, 2018 to December 1, 2019. All patients were divided into cocktail and control groups according to whether the cocktail therapy was used or not after the operation. The anesthesiologist did not provide analgesic treatment other than nerve block anesthesia and intravenous anesthesia, such as analgesic pumps. The operative region of the cocktail group received a mixture of 10 ml of 0.75% ropivacaine, 10 ml of flurbiprofen axetil injection, and 1 ml of compound betamethasone injection, whereas the control group received nothing in the surgical spot. We recorded patients’ VAS scores preoperatively and at 6, 24 hours postoperatively; the length of hospital stay and the number of hospitalization expenses; the scores of Kolcaba comfort level; and the scores of Pittsburgh sleep quality. Result. There was no significant difference in age or sex between the two groups. The VAS scores at 6 and 24 hours postoperatively were significantly lower in the cocktail group. The average length of hospital stay was 8.24 days in the control group and 3.73 days in the cocktail group. The average total hospitalization cost of the control group was ¥28285.16, and that of the cocktail group was ¥22366.31. In expenses of total hospitalization costs, the cocktail group was lower than the control group. Kolcaba’s comfort various scores and the total score of the cocktail group were higher than the control group. The total score of PSQI and all dimensions in the experimental group were lower than those in the control group. Conclusion. We found a significant difference in the results of postoperative pain management except for age, sex, and hospitalization expenses. After hallux valgus surgery, inject cocktail drugs around the first metatarsophalangeal joint did reduce postoperative pain level. Level of Evidence. Level III, case-control study.
Animation Narrative on Stress Relief and Psychological Cognitive Development in Adolescents
Authors: Jiang Qian , Ma Li , Yue Min
Published: September 2022

As the atmosphere of domestic animation is getting stronger and stronger in recent years, its proportion in the process of public aesthetics, entertainment, and consumption is increasing; thus, the relationship between the audience and works has become an important academic focus. The theatrical animation in the animation industry has become the category that needs to be focused on and changed in the development process of domestic animation because of its characteristics of receiving attention from all-age audiences. Because of the diversified audience levels faced by theatrical animation, it is particularly difficult to coordinate the needs of each audience level, coupled with the long-term influence of Japanese and American animation; the trend of pop culture led by network culture; the inheritance, excavation, and reconstruction of national culture; and other cultural environment and creative thinking intertwined, making the construction of the independence of domestic animation appear more and more difficult. The purpose of this paper is to analyze the theoretical study of the healing elements of Natsume Yojimbo and to analyze the creation of Chinese traditional ink and wash in the creation of our own works. It is concluded that the thematic choices are based on two categories: emotions and dreams, which focus on personal life experience and universal concern for human life. The character construction is divided into three aspects: self-resistance and self-reflection, self-vision and self-actualization, and traumatic experience and self-rescue to explain the complexity and diversity of the characters’ growth connotation. The narrative perspective constitutes the perspective from which the issues are viewed. The omniscient perspective allows for the coexistence of complex character relationships and a clear storyline, while the limited perspective reveals certain emotional tendencies. The narrative mode presents the moral of the text with cause-and-effect narrative, embellished group narrative, and dreamlike polyphony narrative. Finally, the article discusses the realistic dilemma of the growth narrative of domestic online animation and tries to put forward feasible development suggestions in response to the problems at this stage.