bluuebunny/crossref_metadata_2025 huggingface dataset:
Cluster analysis of transcriptomic datasets to identify endotypes of idiopathic pulmonary fibrosis
Authors: Kraven Luke M , Taylor Adam R , Molyneaux Philip L , Maher Toby M , McDonough John E , Mura Marco , Yang Ivana V , Schwartz David A , Huang Yong , Noth Imre , Ma Shwu Fan , Yeo Astrid J , Fahy William A , Jenkins R Gisli , Wain Louise V
Published: May 2022

Background

Considerable clinical heterogeneity in idiopathic pulmonary fibrosis (IPF) suggests the existence of multiple disease endotypes. Identifying these endotypes would improve our understanding of the pathogenesis of IPF and could allow for a biomarker-driven personalised medicine approach. We aimed to identify clinically distinct groups of patients with IPF that could represent distinct disease endotypes.

Methods

We co-normalised, pooled and clustered three publicly available blood transcriptomic datasets (total 220 IPF cases). We compared clinical traits across clusters and used gene enrichment analysis to identify biological pathways and processes that were over-represented among the genes that were differentially expressed across clusters. A gene-based classifier was developed and validated using three additional independent datasets (total 194 IPF cases).

Findings

We identified three clusters of patients with IPF with statistically significant differences in lung function (p=0.009) and mortality (p=0.009) between groups. Gene enrichment analysis implicated mitochondrial homeostasis, apoptosis, cell cycle and innate and adaptive immunity in the pathogenesis underlying these groups. We developed and validated a 13-gene cluster classifier that predicted mortality in IPF (high-risk clusters vs low-risk cluster: HR 4.25, 95% CI 2.14 to 8.46, p=3.7×10−5).

Interpretation

We have identified blood gene expression signatures capable of discerning groups of patients with IPF with significant differences in survival. These clusters could be representative of distinct pathophysiological states, which would support the theory of multiple endotypes of IPF. Although more work must be done to confirm the existence of these endotypes, our classifier could be a useful tool in patient stratification and outcome prediction in IPF.
Lifetime hormone profiles for a long-lived teleost: opercula reveal novel estimates of age-specific reproductive parameters and stress trends in yelloweye rockfish (Sebastes ruberrimus)
Authors: Charapata Patrick , Oxman Dion , McNeel Kevin , Keith Alexa , Mansouri Farzaneh , Trumble Stephen
Published: May 2022

Fisheries management relies on accurate population models for estimating biomass and setting harvest goals; however, physiological data for estimating reproductive parameters in population models are difficult to acquire. Here, lifetime reproductive (progesterone and estradiol) and stress-related (cortisol) hormones were measured in annually deposited growth increments in female yelloweye rockfish ( Sebastes ruberrimus) opercula ( N = 22 females, sampled ages 1–90 years). Analyses of these profiles (∼1-year resolution) provided estimates of physiological (complete puberty) and functional age of sexual maturity (females spawn and contribute larvae to the population) and spawning frequency, with lifetime trends of reproduction and stress. The descriptive mean age of physiological sexual maturity was 11 ± 1 years (standard error (SE)), whereas functional age of maturity was 17 ± 2 years. The estimate of marginal mean spawning frequency was 45.1% ± 5.1%. Stress data (∼15% of females experienced distress events) suggested that females were potentially resilient or not exposed to chronic stressors. Although preliminary, we provide a novel method to estimate age-specific reproductive parameters for proper age-based population modeling of a human-targeted teleost.
Non-invasive measurement of nuclear relative stiffness from quantitative analysis of microscopy data
Authors: Villa Stefano , Palamidessi Andrea , Frittoli Emanuela , Scita Giorgio , Cerbino Roberto , Giavazzi Fabio
Published: May 2022

The connection between the properties of a cell tissue and those of the single constituent cells remains to be elucidated. At the purely mechanical level, the degree of rigidity of different cellular components, such as the nucleus and the cytoplasm, modulates the interplay between the cell inner processes and the external environment, while simultaneously mediating the mechanical interactions between neighboring cells. Being able to quantify the correlation between single-cell and tissue properties would improve our mechanobiological understanding of cell tissues. Here we develop a methodology to quantitatively extract a set of structural and motility parameters from the analysis of time-lapse movies of nuclei belonging to jammed and flocking cell monolayers. We then study in detail the correlation between the dynamical state of the tissue and the deformation of the nuclei. We observe that the nuclear deformation rate linearly correlates with the local divergence of the velocity field, which leads to a non-invasive estimate of the elastic modulus of the nucleus relative to the one of the cytoplasm. We also find that nuclei belonging to flocking monolayers, subjected to larger mechanical perturbations, are about two time stiffer than nuclei belonging to dynamically arrested monolayers, in agreement with atomic force microscopy results. Our results demonstrate a non-invasive route to the determination of nuclear relative stiffness for cells in a monolayer.

Graphic abstract
A novel quantum-behaved binary firefly algorithm with gravitational search algorithm to optimize the features for human activity recognition
Authors: Jindal Sonika , Sachdeva Monika , Kushwaha Alok Kumar Singh
Published: May 2022

This paper proposes a novel optimization approach of the quantum-behaved binary firefly algorithm with a gravitational search algorithm (QBFA-GSA) for discrete feature optimization, which is utilized for the application of human activity recognition. The firefly algorithm (FA) and gravitational search algorithm (GSA) are recently introduced meta-heuristic algorithms that are efficient for optimizing the continuous solution set. The binarized version of the proposed approach enables it to optimize the discrete features and quantum behavior ensures the better diversity of the final optimized features. In the proposed QBFA-GSA approach, the features are optimized by following the combined advantageous attributes of FA and GSA in which the search space is initially explored by firefly agents until the current firefly finds the brighter firefly and further these agents adapt the attributes of GSA to complete the process. These optimized features are passed to deep neural networks (DNN) for the classification of human activities. Here, DNN models of deep convolutional neural networks (DCNN) and DCNN extended with residual blocks (DCNN-RB) are incorporated. The evaluation experiments for human activity recognition are conducted on a benchmark dataset of UCF-101, which is a composition of 101 different activities. The experimental results of the proposed QBFA-GSA approach are superlative to state-of-art techniques, which indicate that the proposed approach is efficient to optimize the features.
A Novel Design of High-Performance Hybrid Multiplier
Authors: Bhandari Jugal Kishore , Verma Yogesh Kumar , Singh Laxman , Gupta Santosh Kumar
Published: May 2022

In this brief, a novel design of hybrid multiplier is proposed. The hybrid multiplier is a combination of two different types of multipliers. The latest computing systems require low-power, area, and delay multipliers. In this work, we extend a new idea of high-performance hybrid multiplier by using Wallace–Dadda and Vedic multipliers. The addition of partial products is done by dividing them into smaller groups to obtain faster results. The proposed method is illustrated by designing an 8-bit hybrid multiplier in which the partial products are divided into four subgroups. In this analysis, two different multipliers are applied to alternative groups. Finally, the carry look ahead adder (CLA) is used to reduce carry propagation delay in the proposed hybrid multiplier. The proposed hybrid multiplier has been synthesized using the Cadence virtuoso tool using a 45-nm CMOS technology. This hybrid multiplier is faster, consumes less power, and occupies less area as compared to the conventional hybrid multipliers.
Optical multi-wave, M-shaped rational solution, homoclinic breather, periodic cross-kink and various rational solutions with interactions for Radhakrishnan–Kundu–Lakshmanan dynamical model
Authors: Batool Tahira , Seadawy Aly R. , Rizvi Syed T. R. , Naqvi Syed K.
Published: May 2022

This paper retrieves different types of solutions such as [Formula: see text]-shaped rational solutions with one and two kinks, homoclinic breather, multi-waves, periodic cross-kink and kink-cross rational solutions for Radhakrishnan–Kundu–Lakshmanan equation (RKLE). We will study the [Formula: see text]-shaped interaction with rogue and kink, we will also obtain the [Formula: see text]-shaped interaction with periodic and kink, periodic cross-rational solutions. At the end, we will express the graphical representation for our newly achieved solutions.
Research of fiber nonlinear effects in WDM-PON based 5G fronthaul networks
Authors: Saleem Asad , Xu Yan , Wang Shuai
Published: May 2022

In fifth-generation (5G) fronthaul networks, the wavelength division multiplexing passive optical network (WDM-PON) is considered as an important tool to address the advanced transmission requirements. The nonlinear effects occur when multiple wavelengths are transmitted simultaneously in the same optical fiber. In this paper, we investigate the four-wave mixing (FWM) and the cross-phase modulation (XPM) effects by using non-return-to-zero (NRZ), 4-level pulse amplitude modulation (PAM4), and optical duobinary (ODB) modulation formats in WDM-PON-based 5G fronthaul networks. The results show that ODB performs better when it comes to limiting the FWM and XPM effects because of its precoded attribute. Compared to the unpredictable sensitivity penalty based on NRZ and PAM4, the FWM-induced sensitivity penalty using ODB is reduced to 2[Formula: see text]dB. Moreover, the XPM-induced sensitivity penalty is measured as 1[Formula: see text]dB by adopting ODB, which is almost 5[Formula: see text]dB better than NRZ and PAM4 modulation formats.
Unitary inner product graphs and their automorphisms
Authors: Zhao Shouxiang , Nan Jizhu
Published: May 2022

Let [Formula: see text] be a finite field of order [Formula: see text] and [Formula: see text] be an integer with [Formula: see text] or [Formula: see text], where [Formula: see text] is a power of a prime. We introduce the concept of the unitary inner product graph [Formula: see text] over [Formula: see text] and determine its automorphism group. We obtain two necessary and sufficient conditions for two vertices of [Formula: see text] and two edges of [Formula: see text], respectively, are in the same orbit under the action of the automorphism group of [Formula: see text]
Infrared and visible image fusion using multi-scale pyramid network
Authors: Zuo Fengyuan , Huang Yongdong , Li Qiufu , Su Weijian
Published: May 2022

Deep networks have been widely applied in infrared and visible image fusion. However, the current deep networks cannot well extract and fuse multi-scale information and high-frequency texture features of the source images. In this paper, a deep multi-scale pyramid network, termed MSPFNet, is proposed for infrared and visible image fusion by combining image Laplacian pyramid and deep network. Infrared and visible images are first decomposed into their Laplacian pyramids. For each source image, its Laplacian pyramid consists of a low-frequency component and a series of multi-scale high-frequency components containing texture details. Then, the Laplacian pyramid components of two source images in the same level are fused using convolutional neural networks (CNN). Finally, the final fused image is reconstructed on the fused Laplacian pyramid components using inverse Laplacian pyramid transform. The experimental results on publicly available datasets show that MSPFNet can efficiently extract and fuse the multi-scale detail information of source images, and the fused images of MSPFNet preserve more texture details of infrared and visible images than that of the previous state-of-the-art methods.
Global existence of solutions to a two-species predator–prey parabolic chemotaxis system
Authors: Shanmugasundaram Gnanasekaran , Arumugam Gurusamy , Erhardt André H. , Nagarajan Nithyadevi
Published: May 2022

We consider the following two-species parabolic predator–prey chemotaxis system: [Formula: see text] under the homogeneous Neumann boundary conditions in a bounded domain [Formula: see text], [Formula: see text] with smooth boundary [Formula: see text]. We assume that the parameters [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] are positive and the non-negative initial data [Formula: see text], where [Formula: see text] is the function of [Formula: see text] and defined as [Formula: see text] for some [Formula: see text] and all [Formula: see text]. Assume that there exists [Formula: see text] such that [Formula: see text] and let [Formula: see text], where [Formula: see text], then the system has a unique globally bounded classical solution [Formula: see text] in [Formula: see text].
Recent Development and Applications of the ABEEM/MM Polarizable Force Field
Authors: Zhang Jing , Gong Li-Dong , Yang Zhong-Zhi
Published: May 2022

In this paper, we review both development and applications of the atom-bond electronegativity equalization method fused into molecular mechanics, i.e., ABEEM/MM polarizable force field (FF). We will focus on the applications of the ABEEM/MM in pure water systems, chemical and biomolecular ion-containing systems, small molecules and biomolecules, etc. The results show that the performance of ABEEM/MM is generally better than that of the commonly used nonpolarizable force fields.
U–Pb age constraints on the protolith, cooling and exhumation of a Variscan middle crust migmatite complex from the Central Iberian Zone: insights into the Variscan metamorphic evolution and Ediacaran palaeogeographic implications
Authors: Ferreira Joana Alexandra , Pereira Inês , Bento dos Santos Telmo , Mata João
Published: May 2022

The Figueira de Castelo Rodrigo–Lumbrales Anatectic Complex (FCR-LAC) located in the Central Iberian Zone of the European Variscan Belt is delimited by two shear zones, which have been interpreted as constraining its exhumation. New U–Pb zircon and apatite ages for the migmatites allowed us to obtain a peak metamorphic age of the anatectic complex (316.8 ± 2.0 Ma), and to estimate fast cooling (7–54°C Ma
–1
) and fast exhumation (0.2–1.3 mm a
−1
) after a vertical displacement of
c.
6–9 km.

Our results show a similar zircon age distribution between migmatites and the Excomungada Formation from the host Ediacaran–Cambrian Douro–Beiras Supergroup. Although the existence of an inherited zircon population lasting
c.
500 Ma, absent in the metasedimentary units, suggests the contribution of
Ollo de Sapo
magmatic rocks during the Lower–Middle Pennsylvanian melting events.

Detrital zircon ages of the Pinhão Formation (Douro Group) have contrasting sources to units from the Beiras Group, which may indicate the presence of a barrier that prevented older detrital components from reaching the Douro basin. However, at odds with what has been postulated before, such a barrier must have been placed farther south of the FRC-LAC, and thus not coincident with the Juzbado–Penalva do Castelo shear zone.

Supplementary material:
A full description of the stratigraphy and lithologies (Supplementary 1 and 2, respectively); the analytical conditons of the LA-ICP-MS analyses (Supplementary Material 3); the U–Pb zircon and apatite data of the FCR-LAC migmatites and the U–Pb detrital zircon data of the DBSG (Supplementary Material 4) are available at
https://doi.org/10.6084/m9.figshare.c.6002006
Paleogene drainage system evolution in the NE Faroe–Shetland Basin
Authors: Walker Faye , Schofield Nick , Millett John , Jolley David , Planke Sverre , Holford Simon
Published: May 2022

Incised drainage systems can provide a record of the timing, duration and magnitude of ancient vertical crustal motion. The NE Atlantic underwent rapid uplift at
c.
56 Ma, resulting in widespread incision and the formation of Paleogene unconformities across the Faroe–Shetland Basin. We used 3D seismic data to map a newly identified incised drainage system in the northern Faroe–Shetland Basin that formed during this period of uplift and compared it with similar incision surfaces in the region. The
c.
30 km × 50 km erosional surface is a composite feature, comprising the Upper Thanetian Unconformity, which was rejuvenated and eroded by the younger Flett Unconformity, and records prolonged regional uplift during the late Thanetian–earliest Ypresian punctuated by a phase of subsidence. The drainage system was influenced by igneous intrusions, resulting in the diversion of channels around forced fold structures. Several preserved palaeoshorelines occur close to the basinward limit of the incision surface, recording progressive back-stepping of the shoreline and marine transgression during early Ypresian subsidence. The drainage system may have supplied ‘clean’ sand, eroded from the North Shetland Platform, to the Flett Sub-basin, with the potential to form high-quality reservoir units. Such sands may have been concentrated along shorelines coeval with the drainage system, but potentially were also delivered further out into the basin.
Stress state in parts of NE India: borehole collapse modelling with sensitivity analysis
Authors: Alam Jenifer , Chatterjee Rima , Dasgupta Sohini , Das Baisakhi
Published: May 2022

Structural heterogeneities and tectonic forces in NE India give rise to changeable
in situ
stresses with varying orientations in this part of India. Wells located in the seismic gap in Upper Assam, the Naga Thrust and the Chittagong–Mizoram–Tripura fold belt of Mizoram are used to study stress state and borehole collapse models for the area. The absence of stress studies in the Mizoram area acts as an impetus to undertake stress studies. Poroelastic modelling shows the average ratio of maximum horizontal to vertical stress to be 0.79 for normal-faulted, 1.18 for thrust-faulted and 1.12 for strike-slip-faulted regimes. The
S
H
direction varies from 193°N in Upper Assam to 213°N in Mizoram areas. The image log from a well in the Mizoram area shows the rotation of
S
H
direction (
c
. 85°) to vary from 500 to 3707 m due to structural heterogeneity. The thrust and strike-slip regimes in the study area pose the major threat for safe borehole drilling in this complex terrain. To mitigate this issue, Mohr–Coulomb (MC) and Mogi–Coulomb (MG) rock failure criteria are discussed to predict the minimum mud weight required for borehole drilling. MG-predicted mud weight (MW) ensures borehole stability in wells in normal-faulted sediments, while MC-predicted MW prevents shear failure in wells in thrust and strike-slip regimes. A disc plot is used to model a stable wellbore drilling path with a minimum MW. A vertical well is shown to be stable in a normal-faulted regime, whereas horizontal drilling is preferable in the fold–thrust belt. Sensitivity analysis of geomechanical input parameters on MW using Monte Carlo simulation shows that
S
H
has the maximum effect on MW regardless of the faulting regimes.
Late Holocene climate variability and its impact on cultural dynamics in central India
Authors: Behera Diptimayee , Mishra Praveen K. , Sabale Pandurang , Bhattacharya Sharmila , Anoop Ambili
Published: May 2022

An understanding of long-term climate variability may provide a valuable perspective on the possible response of human societies to modern climate change. The present study, based on geochemical and sedimentological analyses on well dated (using AMS
14
C and optically stimulated luminescence (OSL) dates) alluvial sediments from Sina River basin (in Maharashtra, central India), provides a detailed understanding of the complex interplay between climate and cultural dynamics during the Late Holocene. The radiocarbon dates of the organic residues from the potsherds represent the Medieval period (
c.
1.6–0.95 cal ka BP), whereas the OSL sample shows an age of
c.
7.5 ± 0.4 ka. Further, several cultural objects (e.g. potsherds, shell bangles, and copper artefacts) available at the site were also investigated in order to understand the extent of human activity in the region. The temporal changes in the proxies along with the abundance of cultural materials in the fluvial section during the Medieval period suggest that the human population attempted to adapt against the fluctuating climate conditions. The regional comparison of geo-archaeological datasets shows that the pronounced weakening of the monsoonal rainfall during the Late Holocene coincides with the disruption, migration and resettlement of indigenous societies, deciphering the possible impact of climate on human settlement.
Persistent Summaries
Authors: Zeng Tianjing , Wei Zhewei , Luo Ge , Yi Ke , Du Xiaoyong , Wen Ji-Rong
Published: May 2022

A
persistent data structure
, also known as a
multiversion data structure
in the database literature, is a data structure that preserves all its previous versions as it is updated over time. Every update (inserting, deleting, or changing a data record) to the data structure creates a new version, while all the versions are kept in the data structure so that any previous version can still be queried.

Persistent data structures aim at recording all versions accurately, which results in a space requirement that is at least linear to the number of updates. In many of today’s big data applications, in particular, for high-speed streaming data, the volume and velocity of the data are so high that we cannot afford to store everything. Therefore, streaming algorithms have received a lot of attention in the research community, which uses only sublinear space by sacrificing slightly on accuracy.

All streaming algorithms work by maintaining a small data structure in memory, which is usually called a
sketch
,
summary
, or
synopsis
. The summary is updated upon the arrival of every element in the stream, thus it is
ephemeral
, meaning that it can only answer queries about the current status of the stream. In this article, we aim at designing persistent summaries, thereby giving streaming algorithms the ability to answer queries about the stream at any prior time.
Parallel QR Factorization of Block Low-rank Matrices
Authors: Apriansyah M. Ridwan , Yokota Rio
Published: May 2022

We present two new algorithms for Householder QR factorization of Block Low-Rank (BLR) matrices: one that performs block-column-wise QR and another that is based on tiled QR. We show how the block-column-wise algorithm exploits BLR structure to achieve arithmetic complexity of 𝒪(
mn
), while the tiled BLR-QR exhibits 𝒪(
mn
1.5
complexity. However, the tiled BLR-QR has finer task granularity that allows parallel task-based execution on shared memory systems. We compare the block-column-wise BLR-QR using fork-join parallelism with tiled BLR-QR using task-based parallelism. We also compare these two implementations of Householder BLR-QR with a block-column-wise Modified Gram–Schmidt (MGS) BLR-QR using fork-join parallelism and a state-of-the-art vendor-optimized dense Householder QR in Intel MKL. For a matrix of size 131k × 65k, all BLR methods are more than an order of magnitude faster than the dense QR in MKL. Our methods are also robust to ill conditioning and produce better orthogonal factors than the existing MGS-based method. On a CPU with 64 cores, our parallel tiled Householder and block-column-wise Householder algorithms show a speedup of 50 and 37 times, respectively.
Multi-Scale Multi-Technique Characterization Approach for Analysis of PEM Electrolyzer Catalyst Layer Degradation
Authors: Zaccarine Sarah F. , Shviro Meital , Weker Johanna Nelson , Dzara Michael J. , Foster Jayson , Carmo Marcelo , Pylypenko Svitlana
Published: May 2022

Polymer electrolyte membrane water electrolyzers (PEMWEs) are devices of paramount importance, enabling the large-scale storage of hydrogen from intermittent renewable energy sources such as wind and solar. But a transition towards lower noble metal catalyst loadings and intermittent operation is needed for the widespread utilization of this technology. Although kinetic losses tend to dominate in membrane electrode assembly (MEA) results, it has been suggested that morphological changes and interfaces between the catalyst, ionomer, and membrane will also contribute to overall degradation. Moreover, the combination of degradation to the catalyst layer (CL) constituents will further lead to structural changes that have not been widely explored. The multitude and complexity of degradation mechanisms, which likely occur simultaneously, require a characterization approach that can explore surfaces and interfaces at a range of length-scales to probe chemical, morphological, and structural changes of constituents within the catalyst later. This paper presents a comprehensive characterization approach that features scanning electron microscopy (SEM), scanning transmission electron microscopy with energy-dispersive X-Ray spectroscopy (STEM/EDS), X-Ray photoelectron spectroscopy (XPS), X-Ray absorption spectroscopy (XAS), and transmission X-Ray microscopy (TXM) with X-Ray absorption near-edge structure (XANES) chemical mapping to study degradation of the catalyst layer with a focus on MEAs after intermittent and steady-state operation. Catalyst changes including dissolution, oxidation, and agglomeration were observed, as well as redistribution and dissociation of the ionomer. These smaller-scale changes were found to have a large influence on overall stability of the electrodes: they caused the formation of voids and segregation of constituents within regions of the film. Delamination and collapse of the overall catalyst layer were observed in some instances. Greater changes were observed after an extended 2 V hold compared to IV cycling, but similar degradation mechanisms were detected, which suggests the larger issues would likely also be experienced during intermittent PEMWE operation. These findings would not be possible without such a systematic, multi-scale, multi-technique characterization approach, which highlights the critical importance of detailed analysis of catalyst layer degradation to propose mitigation strategies and improve long-term PEM water electrolyzer performance.
Heat Generation and Temperature Rise Characteristics of Single Overcharged Lithium-Ion Batteries
Authors: Zhang Qiaoping , Li Pengzhao , Liu Chenhui , Wei Fanglin , Wang Miao , Li Jiaxin , Zhu Shihao , Shao Guosheng , Mao Jing
Published: May 2022

It’s critical to quantitatively investigate the thermal characteristics of single overcharged lithium-ion batteries to realize security alert before thermal runaway occurs. In this work, various (LiCoO2 + LiMn2O4)/graphite soft pack cells overcharged under different cut-off voltages, temperatures and C-rates are tested electrochemically to calculate the heat generation rate and distinguish the dominating heat resource. The results show that overcharged cells with higher cut-off voltage, overcharge temperature and the lower overcharge C-rate exhibit higher heat generation and temperature rise rate as well as poorer state of healthy. Among nonexplosive tested cells, the cell overcharged to 4.8 V at 0.1 C rate and 40 °C exhibits the highest heat generation and temperature rise rates of 9.17 W·l−1 and 4.60 °C·h−1 during 1 C charging at 25 °C. For overcharged cells, lithium plating, increased resistance and gas generation are observed, which are the reason for the accelerated total heat generation rate compared to baseline cells. Comparing with reversible heat, the irreversible heat resulting from diffusion overpotential and the sum of ohmic and charge transfer overpotential is dominating for overcharged cells working under high current. It’s recommended to comprehensively monitor the temperature change of each cell of battery pack.
Electrochemical zirconia-based sensor for measuring hydrogen diffusion in inert gases
Authors: Kalyakin A. S. , Medvedev D. A. , Volkov A. N.
Published: May 2022

Solid-state electrochemical sensors represent a convenient way for solving various electroanalytical tasks. In this work, we present a comprehensive analysis of binary gases composed of hydrogen mixed with an inert gas (He, Ar, N2). Using the fabricated aerometric-type YSZ-based electrolyte, diffusion coefficients for these binary gases were successfully determined in an electrochemical way in a temperature range of 550 °C–750 °C. The obtained results agree well with literature data, showing that the He+H2 gas mixture with highly volatile components exhibit the highest diffusion coefficients, which are around 2 times higher than that for Ar+H2 and N2 + H2.
Performance Characteristics of Polymer Electrolyte Membrane CO2 Electrolyzer: Effect of CO2 Dilution, Flow Rate and Pressure
Authors: Karimi Parisa , Alihosseinzadeh Amir , Ponnurangam Sathish , Karan Kunal
Published: May 2022

CO2 electrolyzer designed to operate on dilute CO2 feed and low stoichiometric ratio would alleviate the separation costs for CO2 purification and electrolyzer exit gas processing, respectively. The effect of CO2 concentration, CO2 flow rate, and CO2 pressure on current density and faradaic efficiency of a solid polymer electrolyte membrane CO2 electrolyzer was quantified. An approach for estimating voltage breakdown into activation overpotential for CO2 reduction reaction as well as oxygen evolution reaction, ohmic losses, and concentration overpotential is introduced. No enhancement in current density (∼160 mA cm−2) was observed above stoichiometry ratio of 4 whereas reducing the stoichiometric ratio to 2.7 still yielded a current density of ∼100 mA cm−2. Dilution of CO2 in the feed from 100 mol% to 30 mol%, at ∼90kPa of cell pressure, resulted in a monotonically decreasing current density. A square root dependency on CO2 partial pressure was observed under these conditions. Operation with pure CO2 at different total pressure yielded only a minor increase in current density indicating some form of saturation-limited behavior. Long-term potentiostatic operation over 85 h revealed continuous drop in current density and a corresponding increase in electrode resistance, observed in electrochemical impedance response.
The superoxide radical switch in the biology of nitric oxide and peroxynitrite
Authors: Piacenza Lucía , Zeida Ari , Trujillo Madia , Radi Rafael
Published: May 2022

The free radical nitric oxide (·NO) is a key mediator in different physiological processes such as vasodilation, neurotransmission, inflammation, and cellular immune responses, and thus preserving its bioavailability is essential. In several disease conditions, superoxide radical (O2·−) production increases and leads to the rapid “inactivation” of ·NO by a diffusion-controlled radical termination reaction that yields a potent and short-lived oxidant, peroxynitrite. This reaction not only limits ·NO bioavailability for physiological signal transduction but also can divert and switch the biochemistry of ·NO toward nitrooxidative processes. Indeed, since the early 1990s peroxynitrite (and its secondary derived species) has been linked to the establishment and progression of different acute and chronic human diseases and also to the normal aging process. Here, we revisit an earlier and classical review on the role of peroxynitrite in human physiology and pathology (Pacher P, Beckman J, Liaudet L. Physiol Rev 87: 315–424, 2007) and further integrate, update, and interpret the accumulated evidence over 30 years of research. Innovative tools and approaches for the detection, quantitation, and sub- or extracellular mapping of peroxynitrite and its secondary products (e.g., protein 3-nitrotyrosine) have allowed us to unambiguously connect the complex biochemistry of peroxynitrite with numerous biological outcomes at the physiological and pathological levels. Furthermore, our current knowledge of the ·NO/O2·− and peroxynitrite interplay at the cell, tissue, and organ levels is assisting in the discovery of therapeutic interventions for a variety of human diseases.
JSTC: Travel Time Prediction with a Joint Spatial-Temporal Correlation Mechanism
Authors: Tag Elsir Alfateh M. , Khaled Alkilane , Wang Pengfei , Shen Yanming
Published: May 2022

Accurate travel time prediction is one of the most promising intelligent transportation system (ITS) services, which can greatly support route planning, ride-sharing, navigation applications, and effective traffic management. Several factors, like spatial, temporal, and external, have big effects on traffic patterns, and therefore, it is important to develop a mechanism that can jointly capture correlations of these components. However, spatial sparsity issues make travel time prediction very challenging, especially when dealing with the origin-destination (OD) method, since the trajectory data may not be available. In this paper, we introduce a unified deep learning-based framework named joint spatial-temporal correlation (JSTC) mechanism to improve the accuracy of OD travel time prediction. First, we design a spatiotemporal correlation block that combines two modules: self-convolutional attention integrated with a temporal convolutional network (TCN) to capture the spatial correlations along with the temporal dependencies. Then, we enhance our model performance through adopting a multi-head attention module to learn the attentional weights of the spatial, temporal, and external features based on their contributions to the output and speed up the training process. Extensive experiments on three large-scale real-world traffic datasets (NYC, Chengdu, and Xi’an) show the efficiency of our model and its superiority compared to other methods.
Deep Neural Network Model Construction for Digital Human Resource Management with Human-Job Matching
Authors: Ni Qing
Published: May 2022

This article uses deep neural network technology and combines digital HRM knowledge to research human-job matching systematically. Through intelligent digital means such as 5G communication, cloud computing, big data, neural network, and user portrait, this article proposes the design of the corresponding digital transformation strategy of HRM. This article further puts forward the guaranteed measures in enhancing HRM thinking and establishing HRM culture to ensure the smooth implementation of the digital transformation strategy of the HRM. This system uses charts for data visualization and flask framework for background construction, and the data is stored through CSV files, My SQL, and configuration files. The system is based on a deep learning algorithm for job applicant matching, intelligent recommendation of jobs for job seekers, and more real help for job applicants to apply for jobs. The job intelligent recommendation algorithm partly adopts bidirectional long and short-term memory neural network (Bi-LSTM) and the word-level human post-matching neural network APJFNN built by the attention mechanism. By embedding the text representation of job demand information into the representation vector of public space, a joint embedded convolutional neural network (JE-CNN) for post matching analysis is designed and implemented. The quantitative analysis method analyzes the degree of matching with the job.
Amino Acid-Doped Polyaniline Nanotubes as Efficient Adsorbent for Wastewater Treatment
Authors: Zhao Zhao , Yang Yimin , Xu Longfei , Qiu Zihan , Wang Ziheng , Luo Yongfeng , Du Kun
Published: May 2022

A natural amino acid-doped polyaniline nanostructure was prepared by a simple in situ chemical polymerization method in an aqueous medium. The structure and morphology of composite material were characterized by FESEM, TEM, FT-IR, and XRD. The results showed that the product possesses a large aspect ratio and a hollow tubular morphology. As-synthesized products were further applied to remove dyes and heavy metal ions from the aqueous solution, which exhibited good removal capacity toward Congo red (955.6 mg·g−1) and Cr(VI) (60.0 mg·g−1). The adsorption data for the former were found to be well described by the pseudo-first-order kinetic and Langmuir adsorption isotherm model. Thermodynamic studies show that the adsorption of Congo red by GluP is a spontaneous and endothermic process. Moreover, cyclic experiment results show that the polyaniline composites exhibited good recyclability. Therefore, these amino acid-doped polyaniline nanotubes can be expected to be an ideal candidate for the removal of organic dye and heavy metal ions from wastewater.
The Diagnostic Value of Scanning in the Injury of Triceps Crus of Volleyball Players
Authors: Zhao Jinfeng , Liu Jianxin
Published: May 2022

The study goal is to solve the problem of the diagnosis of triceps crus injury of volleyball players, meet the needs of volleyball players and team doctors for the correct diagnosis of triceps crus injury scanning, make up for the deficiency that triceps crus injury scanning diagnosis is easy to make mistakes, and improve the efficiency and ability of triceps crus injury diagnosis scanning. Because the experiment involves the technical action of volleyball jump serve, DELSYSR Trignomobile wireless portable surface electromyography tester (16 leads) made in the United States is selected to test the surface electromyography of the main muscle groups of college male volleyball players in the process of jump serve. The German made simi-3D motion image system is used to conduct three-dimensional synchronous test of athletes’ jump serve action. The data analysis software adopts EMG work analysis, EMG analysis software, and simi-3D motion image analysis system for postprocessing data. The original signal is filtered (400 Hz for low pass and 20 Hz for high pass) and rectified. Finally, IEMG, EMG contribution rate, and RMS were calculated. This ensures the accuracy of the experiment.
Study on Pavement Performance of Cement Stabilized Recycled Brick Aggregate Base with Basalt Fiber
Authors: Li Zhenxia , Chen Yuanzhao , Meng Qinlong , Wang Chaohui , Guan Jian , Zhang Lei , Wang Xinqi , Hu Xiaguang , Zhang Yajie , Chen Haijun
Published: May 2022

The solution to environmental problems caused by the generation of construction brick waste is its use as a substitute for natural gravel aggregate in highway base material. The preparation of basalt fiber cement stabilized recycled brick aggregate base material is by adding basalt fiber to cement stabilized recycled waste brick mixture. With the help of nonlateral compressive strength test, indirect tensile (splitting) strength test, and flexural tensile strength test, the influence of basalt fiber with different dosages on the compressive strength, crack resistance, and durability of cement stabilized recycled waste brick mixture was analyzed. The effects of basalt fiber on water loss rate, dry shrinkage strain, and frost resistance of cement stabilized recycled waste brick mixture were analyzed by dry shrinkage test and freeze-thaw test. The bonding morphology of fiber and cement slurry was studied by scanning electron microscopy. The results show that when the waste brick aggregate content is 30% and basalt fiber content is 1‰, the 28-day compressive strength of cement stabilized waste brick mixture is 19% higher than that of the specimen without fiber; indirect tensile strength increased by 36.6%; flexural strength increased by 37.0%; water loss rate decreased by 15.5%; the coherent shrinkage strain decreased by 30.3%; and BDR value (compressive strength loss percentage) increased by 12.3%. Basalt fiber and cement slurry have good bonding force and friction force, which act as tensile reinforcement in the mixture. Fiber bundle and fiber filament compose a fiber network to enwrap the mixture, so that the fiber network and mixture are embedded with each other, thereby improving the mechanical properties and durability of cement stabilized recycled waste brick mixture.
Design of Control System of Once-Through Steam Generator Based on Proximal Policy Optimization Algorithm
Authors: Li Cheng , Yu Ren , Yu Wenmin , Wang Tianshu
Published: May 2022

Because of the characteristics of the small water volume of OTSG, it is hard to control the outlet steam pressure when the load is changed or disturbed. This study is devoted to the control of the once-through steam generator (OTSG). A double-layer controller based on the PPO algorithm is proposed to control the outlet steam pressure of OTSG. The bottom layer is the PID controller; it directly regulates the OTSG feed water valve and then controls the steam pressure. The top layer of the controller is the agent based on the PPO algorithm, which is responsible for optimizing the parameters of the PID in real time to obtain better control performance. The agent chooses PID parameters as actions to the environment, and then, the reward value is obtained through the reward function of the environment which enables online learning of the agent. Compared with the PID controller, the simulation experiment result shows that the method not only has a good control performance but also has a good anti-interference ability.
Extension Limit of a Straight-Swirling Mixed Jet Bit and Its Influential Factors in Radial Jet Drilling
Authors: Du Peng , Xia Weikang , Yu Chaoxiong
Published: May 2022

Radial jet drilling (RJD) is applied to low-permeability and unconventional natural gas. A self-propelled bit chiefly affects the borehole length and drilling efficiency. Herein, for a straight-swirling mixed jet (SSMJ) bit, a prediction model of the drilling extension limit

L

EL

was established by analysing the forces and pressure loss of RJD system.

L

EL

of a specific project was calculated and the pressure loss and forces distribution were obtained. Additionally, the influence laws of the main factors on

L

EL

were studied using the established model. The results indicated that the high-pressure hose contributes the main system pressure loss, and the recoil force of backward nozzles is the sole driving force of RJD. The recoil force of forward nozzle and friction between the hose and borehole constitute the main resistances. Increasing the pump pressure

p

b

, backward nozzle diameter

d

b

, and jet diffusion angle

θ

x

and reducing forward nozzle diameter

d

f

, impeller central hole diameter

d

m

, and backward nozzle inclination angle

θ

b

are conducive to improving

L

EL

. However, larger

p

b

and

d

b

increase the hydraulic consumption, besides larger

θ

x

or smaller

d

f

, and

d

m

will reduce the rock-breaking capability. From a sensitivity analysis,

p

b

and

d

m

have the maximum and minimum influence on

L

EL

, respectively. Finally, prediction value

L

EL

of an oil well in Eastern Sichuan can be up to 63.7 m. The results provide a guidance for the hydraulic parameters and key component selection, additionally bit structure optimization of RJD.
Application of Addition and Multiplication Noise Model Parameter Estimation in INSAR Image Processing
Authors: Cui Ge
Published: May 2022

INSAR images are inevitably contaminated by noise during the process of generation, transmission, compression, and reception. Noise not only affects the quality of the INSAR image, but also affects subsequent operations such as the design of corresponding filters, INSAR image segmentation, compression, restoration, and feature recognition. The INSAR image noise model is mainly divided into additive noise and multiplicative noise. Compared with additive noise, multiplicative noise is more complicated due to INSAR image correlation and non-Gaussian. Based on least squares algorithm system of additive and multiplicative mixed noise model, this paper proposes a method of using PCA to remove multiplicative gamma distribution noise. The pure noise coefficient is obtained by subtracting the original coefficient from the diagonal wavelet coefficient of the noisy image, and the mode of the local variance is calculated as the estimation value of the noise standard deviation. Experiments show that the proposed method can obtain more accurate estimation of noise; in particular in the case of less noise and more detailed image information, its effect is more obvious.
A Rare Case of Raoultella planticola and Enterococcus casseliflavus Coinfection
Authors: Prasad Varsha , Barouni Baina , Khiatah Bashar , Saeed Musab
Published: May 2022

Raoultella planticola, a Gram-negative bacterium, is a nonmotile rod usually found in soil and aquatic environments. It can be found in association with gastrointestinal malignancy. Enterococcus casseliflavus is a rare vancomycin-resistant Enterococcus that is responsible for some bacteremia. Our case describes a unique presentation of colonization with both R. planticola and E. casseliflavus isolated from the biliary stent isolates of a patient with known pancreatic malignancy and concomitant E. casseliflavus bacteremia. This is the first case ever reported of infection with both species.
A Study of DNN-Based Media Literacy and Distance Education Management System in the Context of Participatory Culture
Authors: Xu Rui , Wang Chen , Hsu Yen
Published: May 2022

Through an in-depth study and analysis of the integration of media literacy with distance education management using the DNN algorithm in the context of participatory culture, and the design of a distance education management system for application in actual teaching, the word embedding model is used to embed the ratings and tags, respectively; then, the self-encoder is used to extract textual features for item tags, while DNN is used to extract features for user tagging behaviors; finally, the fully connected neural network is used to predict ratings for the fused user and item features. The experimental results show that the optimized recommendation model effectively reduces the user rating prediction error while alleviating the cold start problem. A blockchain-based learning platform is designed. The purpose is to solve the contradiction between centralized storage and social trust, and to transfer the management of educational certification resources from centralized control management to distributed control management. This platform can record in stages a variety of verification information and course certificate information collected by students in the process of learning courses, create course certificates containing digital summaries of learning information, and store them on the chain to ensure the integrity and traceability of data in the learning process. This paper implements a blockchain-based online education system, which ensures that system data will not be maliciously queried and dynamically changed by management.
Anti-Inflammatory Phytoconstituents of Origanum Majorana
Authors: Zhou Li , Wang Senye , Qu Jiaojiao , Zhou Huihui , Fatma Al-Zahra K. K. Attia , Kang Wenyi , Xi Xuefeng , Liu Zhenhua
Published: May 2022

Origanum majorana belongs to the Lamiaceae family as a famous spice plant in Egypt, which is used to treat arthritis, allergies, fever, flu, hypertension, respiratory infections, migraine, and asthma. In our studies, it was found that the ethanol extract of O. marjoram could significantly reduce NO release at 200 (

P
<
0.001

), 100 (

P
<
0.001

) and 50 (

P
<
0.01

) μg/mL compared with the model group. Therefore, the chemical constituents were further studied to obtain the bioactive compounds. As a result, ten compounds were isolated and identified from the 70% ethanol extract of O. marjoram, including six flavonoids (3–8), two terpene derivatives (9-10), one lignan (2), and one phenolic glycoside (1). Among them, compounds 1–3, 5, and 9-10 were isolated from this genus for the first time. Compounds 1, 9, and 10 could significantly decrease the content of NO at the concentration of 100 μm (

P
<
0.001

) in RAW264.7 cells induced by LPS. Furthermore, compounds 9 and 10 were more effective than compound 1 to lower the content at 50 μm (

P
<
0.001

).