bluuebunny/crossref_metadata_2025 huggingface dataset:
Computational investigation of the plasmonic properties of TiN, ZrN, and HfN nanoparticles: the role of particle size, medium, and surface oxidation
Authors: Esfahani Monfared Yashar , Dasog Mita
Published: February 2021

Group 4 transition metal nitride (TMN) nanoparticles (NPs) display strong plasmonic responses in the visible and near-infrared regimes, exhibit high melting points and significant chemical stability, and thus are potential earth-abundant alternatives to Au and Ag based plasmonic applications. However, a detailed understanding of the relationship between TMN NP physical properties and plasmonic response is required to maximize their utility. In this study, the localized surface plasmon resonance (LSPR) frequency, bandwidth, and extinction of titanium nitride (TiN), zirconium nitride (ZrN), and hafnium nitride (HfN) NPs were examined as a function of the particle size, surface oxidation, and refractive index of the surrounding medium using finite element method (FEM). A linear redshift in the LSPR frequency and a linear increase in the associated full width at half maximum (FWHM) was observed with increasing the particle size, oxidation layer thickness, and medium refractive index. We show that the effect of surface oxidation on plasmonic properties of TMN NPs is strongly size-dependent with a significant LSPR redshift, intensity reduction, and broadening in small NPs compared with larger NPs. Furthermore, the performance and efficiency of HfN, ZrN, and TiN, as well as Au NPs for narrowband (photothermal therapy, PTT) and broadband (solar energy conversion) applications, was investigated in detail. The results indicate that narrowband and broadband photothermal performance of NPs strongly depend on the particle size, surface properties, and in case of narrowband absorption, excitation wavelength.
Material application methodologies for winter road maintenance: a renewed perspective
Authors: Du Sen , Akin Michelle , Bergner Dave , Xu Gang , Shi Xianming
Published: February 2021

Winter roadway operations, commonly known as snow and ice control operations, are one of the most critical functions of state, provincial, and local transportation agencies in cold regions. These operations aim to provide safety and mobility through the timely and effective application of materials and mechanical removal. The most common materials used are salt (sodium chloride, solid or liquid brine), magnesium chloride-based, calcium chloride-based deicers, agro-based additives and blends, and abrasives. In practice, the specific choice and application method and rate of these materials are dependent on pavement temperature, precipitation type, level of service goals, budget, and environmental sustainability considerations. Best practices of material application are designed to apply the right type and amount of materials in the right place at the right time. This review presents a literature review and agency interviews that were conducted to gather information about the use of materials, including types of materials, application strategies, application rates, and application equipment.
From 95 to 59 millimetres: a new active acoustic tag size guideline for salmon
Authors: Liss Stephanie A. , Znotinas Katherine R. , Blackburn Shannon E. , Fischer Eric S. , Hughes James S. , Harnish Ryan A. , Li Huidong , Deng Zhiqun Daniel
Published: February 2021

Two laboratory studies evaluated small Chinook salmon (Oncorhynchus tshawytscha) (36–99 mm fork length (FL), 0.7%–26.7% tag burden) survival, tag retention, and growth (n = 539) and critical swimming speed (Ucrit; n = 241). Fish were implanted with a new active acoustic tag and compared with untagged controls at 12 and 17 °C. Across studies, no temperature differences were detected. All control fish survived. All tagged fish ≥58 mm FL survived and retained their tags. Regression models predicted ≥98.6% survival and retention for tagged fish ≥58.6 mm FL or ≥1.9 g (4.2% tag burden). No growth differences among treatments were identified. Spline regression analysis indicated Ucrit was similar for control and tagged fish that measured ≥57.3 mm FL. We recommend tagging salmon ≥59 mm FL or ≥1.9 g (≤4.2% tag burden), although the guideline should be confirmed in a field setting. Study results represent an important step towards using the new active tag in acoustic telemetry field studies that estimate short-term (30-day) survival of small salmonids.
Realized and potential efficiency for post-stratified estimation in a national forest inventory
Authors: Westfall James A. , Lister Andrew J. , Coulston John W. , McRoberts Ronald E.
Published: February 2021

Post-stratification is often used to increase the precision of estimates arising from large-area forest inventories with plots established at permanent locations. Remotely sensed data and associated spatial products are often used for developing the post-stratification, which offers a mechanism to increase precision for less cost than increasing the sample size. While important variance reductions have been shown from post-stratification, it remains unknown where observed gains lie along the continuum of possible gains. This information is needed to determine whether efforts to further improve post-stratification outcomes are warranted. In this study, two types of optimal post-stratification were compared with typical production-based post-stratifications to estimate the magnitude of remaining gains possible. Although the optimal post-stratifications were derived using methods inappropriate for operational usage, the results indicated that substantial further increases in precision for estimates of both forest area and total tree biomass could be obtained with better post-stratifications. The potential gains differed by the attribute being estimated, the population being studied, and the number of strata. Practitioners seeking to optimize post-stratification face challenges, such as evaluation of numerous auxiliary data sources, temporal misalignment between plot observations and remotely sensed data acquisition, and spatial misalignment between plot locations and remotely sensed data due to positional errors in both data types.
Nucleon and dinucleon decays to leptonic final states in a left-right symmetric model with large extra dimensions
Authors: Girmohanta Sudhakantha
Published: February 2021

We consider baryon-number-violating nucleon and dinucleon decays to leptonic final states in the context of a left-right symmetric (LRS) model with large extra dimensions. Specifically, we study (a) nucleon to trilepton decays with $$\varDelta B=-1$$

Δ
B
=
-
1

and $$\varDelta L=-3$$

Δ
L
=
-
3

, and (b) dinucleon to dilepton decays with $$\varDelta B=-2$$

Δ
B
=
-
2

and $$\varDelta L=-2$$

Δ
L
=
-
2

. In the LRS model, $$B-L$$

B
-
L

is gauged and is spontaneously broken by a Higgs vacuum expectation value $$v_R$$

v
R

, which characterizes the scale at which processes violating $$B-L$$

B
-
L

occur. We show that together with the lower bound on $$v_R$$

v
R

from experimental limits on n-$${\bar{n}}$$

n

¯

oscillations, constraints from searches for other nucleon decay modes imply sufficient suppression of these nucleon to trilepton and dinucleon to dilepton decay modes in this model to agree with experimental bounds.
HiggsSignals-2: probing new physics with precision Higgs measurements in the LHC 13 TeV era
Authors: Bechtle Philip , Heinemeyer Sven , Klingl Tobias , Stefaniak Tim , Weiglein Georg , Wittbrodt Jonas
Published: February 2021

The program confronts the predictions of models with arbitrary Higgs sectors with the available Higgs signal rate and mass measurements, resulting in a likelihood estimate. A new version of the program, , is presented that contains various improvements in its functionality and applicability. In particular, the new features comprise improvements in the theoretical input framework and the handling of possible complexities of beyond-the-SM Higgs sectors, as well as the incorporation of experimental results in the form of simplified template cross section (STXS) measurements. The new functionalities are explained, and a thorough discussion of the possible statistical interpretations of the results is provided. The performance of is illustrated for some example analyses. In this context the importance of public information on certain experimental details like efficiencies and uncertainty correlations is pointed out. is continuously updated to the latest experimental results and can be obtained at https://gitlab.com/higgsbounds/higgssignals.
MODIFIED AMORPHOUS SiO2 FROM Zr-CONTAINING SILICA RESIDUE: A PROMISING WAY OF RECYCLING USEFUL MATERIALS AS WELL AS REMOVING Cr(VI) FROM WATER
Authors: LIANG YU , CHEN WANTING , ZHANG HAN , WANG JIMO , DING HAO , YU XIPENG
Published: February 2021

The amorphous SiO2, which is purified from Zr-containing silica residue, was modified by CTAB before the adsorption of Cr(VI). The impact of different variables, such as solution pH value, adsorption time, adsorption temperature, and adsorbent dosage were investigated on the Cr(VI) removal from solution. The results show that the optimal pH value for Cr(VI) adsorption is 3. And 60 min is needed for the adsorption with 10 g/L of modified amorphous SiO2 at [Formula: see text]C. The acquired adsorption isotherm and the adsorption process can be interpreted by Langmuir model and pseudo-second-order kinetic model, respectively. This paper provides an effective option for waste water treatment as well as a way of recycling useful materials from the discarded Zr-containing silica residue.
Modified Chilled Coil Model Development and Application to Turbine Inlet Air Cooling
Authors: Anand Gopalakrishnan , Makar Ellen
Published: February 2021

A Turbine Inlet Air Conditioning (TIAC) system can chill the inlet air of the turbine to maintain maximum turbine performance at all ambient temperatures. However, turbine characteristics, performance guarantees and bell-mouth icing considerations require accurate prediction of the chilling coil performance over a wide range of operating conditions. A modified wet-surface model (MWSM) is developed to more accurately predict the chilling coil performance. The higher accuracy of the model is demonstrated by applying the model to simulate performance data of two different coils. The data covered a wide range of operating conditions with ambient temperature vary from [Formula: see text]C to [Formula: see text]C dry bulb and [Formula: see text]C to [Formula: see text]C wet bulb. The turbine flow rate varies from 100% to 43% with chilled air temperature in the range of 3.3–[Formula: see text]C and chilling load variation of 100% to 5%. The chilled water flow rate varies from 100% to 32% with supply glycol-water temperature in the range of [Formula: see text]2.2–[Formula: see text]C. The MWSM uses 11 empirical parameters evaluated from the coil performance data and is able to correlate the data with an adjusted coefficient of determination ([Formula: see text]) of over 99%. The higher accuracy of the modified model enables the development of a more robust controls strategy required to maintain the inlet air temperature at the set point with varying ambient temperatures and chilling load conditions. The model can also be applied to other chilling and dehumidification applications especially those experiencing wide variations in operating conditions and load or those requiring close control of the chilling and dehumidification process.
Facet-oriented Modelling
Authors: Lara Juan De , Guerra Esther , Kienzle Jörg
Published: February 2021

Models are the central assets in model-driven engineering (MDE), as they are actively used in all phases of software development. Models are built using metamodel-based languages, and so objects in models are typed by a metamodel class. This typing is static, established at creation time, and cannot be changed later. Therefore, objects in MDE are
closed
and fixed with respect to the class they conform to, the fields they have, and the well-formedness constraints they must comply with. This hampers many MDE activities, like the reuse of model-related artefacts such as transformations, the opportunistic or dynamic combination of metamodels, or the dynamic reconfiguration of models.

To alleviate this rigidity, we propose making model objects
open
so that they can acquire or drop so-called
facets
. These contribute with a type, fields and constraints to the objects holding them. Facets are defined by regular metamodels, hence being a lightweight extension of standard metamodelling. Facet metamodels may declare usage
interfaces
, as well as
laws
that govern the assignment of facets to objects (or classes).

This article describes our proposal, reporting on a theory, analysis techniques, and an implementation. The benefits of the approach are validated on the basis of five case studies dealing with annotation models, transformation reuse, multi-view modelling, multi-level modelling, and language product lines.
A Survey of Nature-Inspired Computing
Authors: Song Bosheng , Li Kenli , Orellana-Martín David , Pérez-Jiménez Mario J. , PéRez-Hurtado Ignacio
Published: February 2021

Nature-inspired computing
is a type of human-designed computing motivated by nature, which is based on the employ of paradigms, mechanisms, and principles underlying natural systems. In this article, a versatile and vigorous bio-inspired branch of natural computing, named
membrane computing
is discussed. This computing paradigm is aroused by the internal membrane function and the structure of biological cells. We first introduce some basic concepts and formalisms of membrane computing, and then some basic types or variants of
P systems
(also named
membrane systems
) are presented. The state-of-the-art computability theory and a pioneering computational complexity theory are presented with P system frameworks and numerous solutions to hard computational problems (especially
NP
-complete problems) via P systems with membrane division are reported. Finally, a number of applications and open problems of P systems are briefly described.
A Network Analysis of Twitter Interactions by Members of the U.S. Congress
Authors: Chamberlain Joshua M. , Spezzano Francesca , Kettler Jaclyn J. , Dit Bogdan
Published: February 2021

Usage of Twitter by politicians has become more prevalent in recent years, with a goal of influencing the electorate and public perception. We collect, explore, and analyze over 12 years of public Twitter interactions of U.S. senators and representatives. Using community detection algorithms on these interaction networks, and without considering the content of the tweets, we are able to infer the political affiliation of each member of Congress with up to 98.8% accuracy in the House and 94.1% accuracy in the Senate. In addition, we define two metrics that can determine the political ideology of members of Congress achieving a very high Spearman’s rank correlation of 0.86 with the existing DW-NOMINATE score from the field of political science. Finally, we expand our structural analysis to intra-party factions and found evidence that some factions act on Twitter more cohesively than others, suggesting an increasing risk of an echo chamber effect when promoting their political agenda.
Optical Force-Induced Chemistry at Solution Surfaces
Authors: Masuhara Hiroshi , Yuyama Ken-ichi
Published: February 2021

When an intense 1,064-nm continuous-wave laser is tightly focused at solution surfaces, it exerts an optical force on molecules, polymers, and nanoparticles (NPs). Initially, molecules and NPs are gathered into a single assembly inside the focus, and the laser is scattered and propagated through the assembly. The expanded laser further traps them at the edge of the assembly, producing a single assembly much larger than the focus along the surface. Amino acids and inorganic ionic compounds undergo crystallization and crystal growth, polystyrene NPs form periodic arrays and disklike structures with concentric circles or hexagonal packing, and Au NPs demonstrate assembling and swarming, in which the NPs fluctuate like a group of bees. These phenomena that depend on laser polarization are called optically evolved assembling at solution surfaces, and their dynamics and mechanisms are elucidated in this review. As a promising application in materials science, the optical trapping assembly of lead halide perovskites, supramolecules, and aggregation-induced emission enhancement–active molecules is demonstrated and future directions for fundamental study are discussed.
Room Temperature Synthesis of Colossal Magneto-Resistance of La2/3Ca1/3MnO3: Ag0.10 Composite
Authors: Boora Navjyoti , Ahmad Rafiq , Rani Poonam , Maheshwari Pankaj Kumar , Khosla Ajit , Bansal Sonia , Awana V. P. S. , Hafiz A.K.
Published: February 2021

Rare-earth manganite-based perovskite has great potential as a promising material for spintronics and ferroelectromagnets. Herein, we have synthesized La2/3Ca1/3MnO3:Silverx (LCMO-Agx; where x = 0.00 and 0.10) composite using a standard solid-state reaction route. Their structural and physical properties have been investigated. Pristine LCMO and LCMO-Ag composite are crystallized in an orthorhombic structure, which is in a single-phase and has a space group of Pbnm. Pristine LCMO and LCMO-Ag composite’s structural analysis showed better grain connectivity in ferromagnetic domains of LCMO-Ag composite compared to pristine LCMO. Ag doping enhances the paramagnetic-ferromagnetic transition Tc (Curie temperature) to 277 K, which is 8 K higher than that of pristine LCMO (Tc = 269 K). Additionally, the magneto-resistance (MR) of LCMO-Ag composite was improved by ∼10% with Ag doping even at room temperature (RT), which is due to improved connectivity and grain size with Ag doping. Thus, the enhanced value of MR at RT may efficiently open up the possible use of LCMO-Ag composite as ferroelectromagnets and spintronics applications. Additionally, LCMO thin films can be useful in artificial planar junctions, vertical tunnel junctions, and sensing applications.
Comparison of Formation Mechanism between Porous Anodic Sn Oxide and Anodic TiO2 Nanotubes
Authors: Li Puying , Zhou Qinyi , Dan Yuxin , Lu Yishan , Zhang Shaoyu , Xu Haoqing , Li Xia , Song Ye , Zhu Xufei
Published: February 2021

Porous anodic Sn oxide (PASO) and other porous anodic oxides have aroused worldwide scientific interest. However, the relationship between the complex porous structure and the current-time curve cannot be interpreted by the traditional dissolution theory. In particular, with the change of anodizing conditions of Sn, the current-time curve sometimes shows three stages, sometimes five stages. In order to study the relationship between current-time curve and the growth model of complex PASO structure during Sn anodization, this study compares the anodizing processes of Sn and Ti. Under normal circumstances, the current-time curve of Ti in anodizing process is three stages, which can be interpreted reasonably by electronic current and oxygen bubble model. By adjusting the anodizing processes of both metals, their current-time curves would be changed into five stages, which means that the formation mechanism of the two metal oxide porous structures may be inherently connected. Here, the current-time curves of three stages and five stages are carefully compared. The internal relationship between the structure of anodic TiO2 nanotubes and the complex porous structure of PASO is found, revealing that the complex porous structure of PASO is caused by excessive gas evolution which is the result of electronic current.
Impact of changes in tissue optical properties on near-infrared diffuse correlation spectroscopy measures of skeletal muscle blood flow
Authors: Bartlett Miles F. , Jordan Scott M. , Hueber Dennis M. , Nelson Michael D.
Published: February 2021

We investigated how changes in tissue optical properties affect near-infrared diffuse correlation spectroscopy (NIR-DCS)-derived indices of skeletal muscle blood flow (BFI) during physiological provocation. Although accounting for changes in tissue optical properties has little impact on BFI on a group level, individual BFI calculations are indeed impacted by changes in tissue optical properties. NIR-DCS calculations of BFI should therefore account for real-time, physiologically induced changes in tissue optical properties whenever possible.
Transcriptional Profile of Helicobacter pylori Virulence Genes in Patients with Gastritis and Gastric Cancer
Authors: Hedayati Manouchehr Ahmadi , Salavati Saeed
Published: February 2021

Introduction. Numerous molecular epidemiology studies have been performed about the frequency of Helicobacter pylori virulence genes in patients with H. pylori infection so far. This study was conducted to detect transcriptional profile by cDNA of H. pylori virulence genes in gastric biopsy samples of gastritis and gastric carcinoma patients. Materials and Methods. In a case-control study, based on the prevalence of gastritis and gastric cancer in Sanandaj city during 2018 and 2019, 23 and 11 gastric antral biopsy samples with H. pylori infection were collected from gastritis and gastric carcinoma patients by the consecutive and available sampling method. Pathological characters, including tumor grades and tumor areas for gastric carcinoma biopsy samples prepared from gastric cancer areas, were determined by the pathologist. Total RNA of gastric antral biopsy samples was extracted, and their cDNA was synthesized by TaKaRa kit. H. pylori virulence genes’ cDNA using specific primers and PCR was detected. This study’s results were analyzed by SPSS version 25 and statics chi-square tests for determination of relationship and correlation between cDNAs of H. pylori transcriptional profile and clinical outcomes of H. pylori infection, including gastritis, gastric carcinoma, tumor grades, and tumor area. Results. The positive statistical correlations were observed between transcripts of cagA, cagA-EPIYAC, cagE, and cagY genes and H. pylori infection clinical outcomes (

P
<
0.05

). Conclusion. Detection of the H. pylori virulence genes’ cDNA in gastric biopsy samples can help provide the prognosis of clinical outcomes.
Fecal Microbiota Transplantation Is a Promising Method to Restore Gut Microbiota Dysbiosis and Relieve Neurological Deficits after Traumatic Brain Injury
Authors: Du Donglin , Tang Wei , Zhou Chao , Sun Xiaochuan , Wei Zhengqiang , Zhong Jianjun , Huang Zhijian
Published: February 2021

Background. Traumatic brain injury (TBI) can induce persistent fluctuation in the gut microbiota makeup and abundance. The present study is aimed at determining whether fecal microbiota transplantation (FMT) can rescue microbiota changes and ameliorate neurological deficits after TBI in rats. Methods. A controlled cortical impact (CCI) model was used to simulate TBI in male Sprague‐Dawley rats, and FMT was performed for 7 consecutive days. 16S ribosomal RNA (rRNA) sequencing of fecal samples was performed to analyze the effects of FMT on gut microbiota. Modified neurological severity score and Morris water maze were used to evaluate neurobehavioral functions. Metabolomics was used to screen differential metabolites from the rat serum and ipsilateral brains. The oxidative stress indices were measured in the brain. Results. TBI induced significance changes in the gut microbiome, including the alpha‐ and beta‐bacterial diversity, as well as the microbiome composition at 8 days after TBI. On the other hand, FMT could rescue these changes and relieve neurological deficits after TBI. Metabolomics results showed that the level of trimethylamine (TMA) in feces and the level of trimethylamine N‐oxide (TMAO) in the ipsilateral brain and serum was increased after TBI, while FMT decreased TMA levels in the feces, and TMAO levels in the ipsilateral brain and serum. Antioxidant enzyme methionine sulfoxide reductase A (MsrA) in the ipsilateral hippocampus was decreased after TBI but increased after FMT. In addition, FMT elevated SOD and CAT activities and GSH/GSSG ratio and diminished ROS, GSSG, and MDA levels in the ipsilateral hippocampus after TBI. Conclusions. FMT can restore gut microbiota dysbiosis and relieve neurological deficits possibly through the TMA‐TMAO‐MsrA signaling pathway after TBI.
Study on Collision Detection and Force Feedback Algorithm in Virtual Surgery
Authors: Zhang Yu , Luo Dan , Li Jia , Li Jisheng
Published: February 2021

The development of virtual reality technology is expected to solve traditional surgical training. The lack of methods has brought revolutionary advances in technology. The virtual surgery system based on collision detection and force feedback can enable the operator to have stronger interaction, which is an exploration of the feature of touch in virtual reality technology. Reality is an important indicator of the virtual surgical system. This article improves the realism of the system from the visual and tactile senses and uses the surrounding ball collision detection and force feedback algorithms to build a realistic surgical platform. In the virtual surgery training system, the introduction of force feedback greatly improves the sense of presence during virtual surgery interaction. The operator can feel the softness and hardness of different tissues and organs through the force feedback device. Virtual reality is an interdisciplinary comprehensive technology that has been widely used in military, film, medical, and gaming fields. Virtual reality can simulate the objective world and display it visually, making people feel immersive. Virtual surgery provides surgeons with a recyclable surgical practice platform and can help doctors perform preoperative rehearsals and predict the results of surgery. The design of collision detection and force feedback algorithms is a prerequisite to ensure the immersion and transparency of the virtual surgical training system. This article mainly introduces the collision detection and force feedback algorithm research in virtual surgery, with the intention of providing some ideas and directions for the development of virtual surgery. This paper proposes two collision detection algorithms, space decomposition method and hierarchical bounding box method, and three force feedback algorithms including spring mass point algorithm, Runge–Kutta method, and Euler method to construct virtual surgery collision detection and force feedback. Experiment with the Overall System Architecture. This paper proves through experimental results that the average collision detection time after the application of the improved collision detection and force feedback algorithm in the virtual surgery system is more than 80.7% less than the traditional method, which greatly improves the detection speed.
Serum Glycated Albumin Levels Are Affected by Alcohol in Men of the Jinuo Ethnic Group in China
Authors: Zhu Chaoyu , Hou Xuhong , Li Ming , Sun Qingyi , Lu Huijuan , Bao Yuqian , Wei Li , Jia Weiping , Jiang Fusong
Published: February 2021

Aim. To investigate the effects of alcohol on serum glycated albumin (GA) levels in Chinese men. Methods. A total of 2314 male subjects from the Jinuo ethnic group in China were enrolled. Of these, 986 subjects drank alcohol frequently and 404 subjects did not. Lifestyle information was gathered by using a questionnaire, and measurements of blood pressure, body mass index, blood glucose level, liver function, and kidney function were collected. GA was measured by using an enzymatic method. Frequent drinking was defined as a history of drinking ethanol > 80 g/d within the past two weeks. Nondrinking was defined as no alcohol consumption in the past three months. Subjects with an alcohol intake between 0 and 80 g/d in the past two weeks were included in the drinking-occasionally group. Analysis of variance (ANOVA), correlation analysis, and linear regression were used to evaluate the effects of drinking on serum GA levels. Decision tree regression (DTR) algorithm was used to evaluate the effect of features (variables) on GA levels. Results. We found that male subjects who drank frequently had significantly lower serum GA levels than subjects who did not drink (13.0 ± 1.7 vs. 14.1 ± 3.7,

p
<
0.05

). Spearman’s correlation analysis calculated a coefficient of −0.152 between drinking and GA (

p
<
0.005

). Linear regression established that drinking was an independent predictor for GA levels with a standardized regression coefficient of −0.144 (

p
<
0.05

). Decision tree regression showed that the effect of drinking on GA levels (0.0283) is five times higher than that of smoking (0.0057). Conclusions. Frequent alcohol consumption could result in decreased GA levels in men of the Jinuo ethnic group in China.
Double-Diffusive of a Nanofluid in a Rectangle-Shape Mounted on a Cavity Saturated by Heterogeneous Porous Media
Authors: Aly Abdelraheem M. , Mahmoud Ehab Mohamed , Ahmad Hijaz , Yao Shao-Wen
Published: February 2021

This study presents numerical simulations on double-diffusive flow of a nanofluid in two cavities connected with four vertical gates. Novel shape of an outer square shape mounted on a square cavity by four gates was used. Heterogeneous porous media and

Al

2

O

3

-water nanofluid are filled in an inner cavity. Outer rectangle shape is filled with a nanofluid only, and its left walls carry high temperature

T

h

and high concentration

C

h

. The right walls of a rectangle shape carry low temperature

T

c

and low concentration

C

c

and the other walls are adiabatic. An incompressible smoothed particle hydrodynamics (ISPH) method is applied for solving the governing equations of velocities, temperature, and concentration. Results are introduced for the effects of a buoyancy ratio

−
2
≤
N
≤
2

, Darcy parameter

10

−

3

≤

Da

≤

10

−

5

, solid volume fraction

0
≤
ϕ
≤
0.05

, and porous levels. Main results are indicated in which the buoyancy ratio parameter adjusts the directions of double-diffusive convection flow in an outer shape and inner cavity. Adding more concentration of nanoparticles reduces the flow speed and maximum of the velocity field. Due to the presence of a porous medium layer in an inner cavity, the Darcy parameter has slight changes inside the rectangle shape.
Intelligent Neutrosophic Diagnostic System for Cardiotocography Data
Authors: Amin Belal , Salama A. A. , El-Henawy I. M. , Mahfouz Khaled , Gafar Mona G.
Published: February 2021

Cardiotocography data uncertainty is a critical task for the classification in biomedical field. Constructing good and efficient classifier via machine learning algorithms is necessary to help doctors in diagnosing the state of fetus heart rate. The proposed neutrosophic diagnostic system is an Interval Neutrosophic Rough Neural Network framework based on the backpropagation algorithm. It benefits from the advantages of neutrosophic set theory not only to improve the performance of rough neural networks but also to achieve a better performance than the other algorithms. The experimental results visualize the data using the boxplot for better understanding of attribute distribution. The performance measurement of the confusion matrix for the proposed framework is 95.1, 94.95, 95.2, and 95.1 concerning accuracy rate, precision, recall, and F1‐score, respectively. WEKA application is used to analyse cardiotocography data performance measurement of different algorithms, e.g., neural network, decision table, the nearest neighbor, and rough neural network. The comparison with other algorithms shows that the proposed framework is both feasible and efficient classifier. Additionally, the receiver operation characteristic curve displays the proposed framework classifications of the pathologic, normal, and suspicious states by 0.93, 0.90, and 0.85 areas that are considered high and acceptable under the curve, respectively. Improving the performance measurements of the proposed framework by removing ineffective attributes via feature selection would be suitable advancement in the future. Moreover, the proposed framework can also be used in various real‐life problems such as classification of coronavirus, social media, and satellite image.
Assessment of Steatosis and Fibrosis in Liver Transplant Recipients Using Controlled Attenuation Parameter and Liver Stiffness Measurements
Authors: Mikolasevic Ivana , Hauser Goran , Mijic Maja , Domislovic Viktor , Radic-Kristo Delfa , Krznaric Zeljko , Razov-Radas Melanija , Pavic Tajana , Matasin Marija , Filipec Kanizaj Tajana
Published: February 2021

Aim. The primary objective of this study was to evaluate the prevalence of increased controlled attenuation parameter (CAP) and liver stiffness measurements (LSM) as surrogate markers of liver steatosis and fibrosis in liver transplant recipient (LTR). Secondary objectives were to determine the predictors of increased CAP and LSM in population of LTR. Methods. In this prospective, cross-sectional study, we have evaluated 175 LTRs’ mean age as 61 (53–65) with a functioning graft for more than one year who came for regular outpatient examinations to the Department of Gastroenterology, University Hospital (UH) Merkur, Zagreb, Croatia. Results. Of 175 analyzed LTRs, 34.28% had obesity, 64.00% had hypertension, 38.28% had diabetes, and 58.85% had hyperlipidemia. The prevalence of liver steatosis was 68.57%, while the prevalence of severe liver steatosis was 46.85%. On multivariate analysis, independent factors associated with liver steatosis were male gender, total cholesterol as positive predictor, and HDL as negative predictor, and independent factors positively associated with severe liver steatosis were higher body mass index (BMI) and higher triglyceride levels. The prevalence of moderate liver fibrosis was 54.85%, while the prevalence of advanced liver fibrosis was 24%. On multivariate analysis, independent factors positively associated with moderate fibrosis were gamma-glutamyl transferase (GGT) and CAP, while the independent factor positively associated with advanced fibrosis was GGT. Conclusion. Our study showed high prevalence of increased CAP and LSM measurements as surrogate markers of liver steatosis and fibrosis. Metabolic syndrome components were highly present and were associated with CAP and LSM values as well as in the pretransplant setting. Due to high prevalence of metabolic comorbidities and nonalcoholic fatty liver disease in LTRs and the lack of the abnormal liver test in a significant number of these patients, TE with CAP may be a reasonable initial assessment for LTRs with one or more components of the metabolic syndrome.
Identifying Stage II Colorectal Cancer Recurrence Associated Genes by Microarray Meta-Analysis and Building Predictive Models with Machine Learning Algorithms
Authors: Lu Wei , Pan Xiang , Dai Siqi , Fu Dongliang , Hwang Maxwell , Zhu Yingshuang , Zhang Lina , Wei Jingsun , Kong Xiangxing , Li Jun , Xiao Qian , Ding Kefeng
Published: February 2021

Background. Stage II colorectal cancer patients had heterogeneous prognosis, and patients with recurrent events had poor survival. In this study, we aimed to identify stage II colorectal cancer recurrence associated genes by microarray meta-analysis and build predictive models to stratify patients’ recurrence-free survival. Methods. We searched the GEO database to retrieve eligible microarray datasets. The microarray meta-analysis was used to identify universal recurrence associated genes. Total samples were randomly divided into the training set and the test set. Two survival models (lasso Cox model and random survival forest model) were trained in the training set, and AUC values of the time-dependent receiver operating characteristic (ROC) curves were calculated. Survival analysis was performed to determine whether there was significant difference between the predicted high and low risk groups in the test set. Results. Six datasets containing 651 stage II colorectal cancer patients were included in this study. The microarray meta-analysis identified 479 recurrence associated genes. KEGG and GO enrichment analysis showed that G protein-coupled glutamate receptor binding and Hedgehog signaling were significantly enriched. AUC values of the lasso Cox model and the random survival forest model were 0.815 and 0.993 at 60 months, respectively. In addition, the random survival forest model demonstrated that the effects of gene expression on the recurrence-free survival probability were nonlinear. According to the risk scores computed by the random survival forest model, the high risk group had significantly higher recurrence risk than the low risk group (HR = 1.824, 95% CI: 1.079–3.084,

p

 = 0.025). Conclusions. We identified 479 stage II colorectal cancer recurrence associated genes by microarray meta-analysis. The random survival forest model which was based on the recurrence associated gene signature could strongly predict the recurrence risk of stage II colorectal cancer patients.
Application of Bionanomaterials in Tumor Immune Microenvironment Therapy
Authors: Wang Jiawei , Bao Yan , Yao Yandan
Published: February 2021

Targeted therapy for the cancer immune system has become a clinical reality with remarkable success. Immune checkpoint blockade therapy and chimeric antigen receptor T-cell (CAR-T) immunotherapy are clinically effective in a variety of cancers. However, the clinical utility of immunotherapy in cancer is limited by severe off-target toxicity, long processing time, limited efficacy, and extremely high cost. Bionanomaterials combined with these therapies address these issues by enhancing immune regulation, integrating the synergistic effects of different molecules, and, most importantly, targeting and manipulating immune cells within the tumor. In this review, we will summarize the most current researches on bionanomaterials for targeted regulation of tumor-associated macrophages, myeloid-derived suppressor cells, dendritic cells, T lymphocyte cells, and cancer-associated fibroblasts and summarize the prospects and challenges of cell-targeted therapy and clinical translational potential in a tumor immune microenvironment in cancer treatment.
A Novel MILP Model for the Production, Lot Sizing, and Scheduling of Automotive Plastic Components on Parallel Flexible Injection Machines with Setup Common Operators
Authors: Andres Beatriz , Guzman Eduardo , Poler Raul
Published: February 2021

In this article, a mixed integer linear program (MILP) model is proposed for the production, lot sizing, and scheduling of automotive plastic components to minimize the setup, inventory, stockout, and backorder costs, by taking into account injection molds as the main index to schedule on parallel flexible injection machines. The proposed MILP considers the minimum and maximum inventory capacities and penalizes stockout. A relevant characteristic of the modeled problem is the dependence between mold setups to produce plastic components. The lot sizing and scheduling problem solution results in the assignment of molds to machines during a specific time period and in the calculation of the number of components to be produced, which is often called lot size, following a sequence‐dependent setup time. Depending on the machine on which the mold is setup, the number of units to be produced will be distinct because machines differ from one another. The stock coverage, defined in demand days, is also included in the MILP to avoid backorders, which is highly penalized in the automotive supply chain. Added to this, the proposed model is extended by considering setup common operators to respond to and fulfill the constraints that appear in automotive plastic enterprises. In this regard, the MILP presented solves a lot‐sizing and scheduling problem, emerged in a second‐tier supplier of a real automotive supply chain. Finally, this article validates the MILP by performing experiments with different sized instances, including small, medium, and large. The large‐sized dataset is characterized by replicating the amount of data used in the real enterprise, which is the object of this study. The goodness of the model is evaluated with the computational time and the deviation of the obtained results as regards to the optimal solution.
Size Detection Method of Embedded Ball Based on Aviation Bearing Image
Authors: Xue Ping , Wang Yihui , Wang Hongmin
Published: February 2021

In the aerospace industry, bearing is widely used in various rotating machinery. The performance of bearing affects the operation of the whole machinery and even aviation equipment. The wrongly assembled ball due to size is an important reason for unqualified bearing. To solve this problem, an accurate ball detection method based on the bearing image is proposed. Firstly, according to the imaging characteristics of bearing and light propagation characteristics, an image collection system based on the coaxial light source is designed. Then, aiming at the problem that the embedded ball is occluded by the bearing ring and the cage, only partial ball in the narrow gap can be used to predict the full ball and the high-precision requirement of ball detection, a ball segmentation model based on DeepLab v3+ network is used to segment the local ball, and CBAM is added in the Xception network of the original network. According to the characteristics of the segmentation result, a circle detection algorithm based on circle fitting evaluation designed for incomplete short arc is proposed. Finally, according to the detection results, judge whether the bearing is qualified or not and evaluate the feasibility of this method. Experimental results show that the ball detection accuracy is about 27 microns, and the wrongly assembled ball with a size difference of only 198 microns can be distinguished. The false detection rate of unqualified bearing is 1%. As the last line of defense of bearing quality inspection, this method can achieve zero false detection rate of unqualified bearing in the industry.
Clinical and Imaging Analysis of Cerebral Infarction Caused by Spontaneous Cerebral Artery Dissection Based on Augmented Reality Technology
Authors: Wang Yinghai , Duan Kedong , Zhang Aihua , Lv Yaping , Cao Dahai
Published: February 2021

In recent years, with the progress of population ageing, the incidence of a stroke caused by spontaneous dissection of the cerebral artery also increases with time. In order to address the health damage caused by a stroke caused by spontaneous dissection of the cerebral artery and to study its effect on human health, this article analyzes the incidence, type, electrocardiogram, and cardiovascular biomarker changes of cerebral infarction through statistical analysis and then discusses cerebral infarction. The pathogenesis and prevention measures of the disease are expected to provide better means for the treatment of cerebral infarction. Based on the case investigation of patients with cerebral infarction caused by spontaneous cerebral artery dissection, a case template was constructed, and a damage assessment matrix was created using a comprehensive quantitative and qualitative analysis method. Experimental results prove that cerebral infarction caused by spontaneous cerebral artery dissection is a great threat to human health, and the fatality rate of patients is extremely high. Enhanced imaging technology is of great help to clinical and image analysis, with a correlation coefficient of 0.87, compared with the other damage rate of cerebral infarction caused by spontaneous cerebral artery dissection which is about 15% higher than that of cerebral infarction caused by different methods. Studies have found that there are great differences in the age of people with cerebral infarction caused by spontaneous cerebral artery dissection, and the patients are generally over 45 years old. This shows that cerebral infarction caused by spontaneous cerebral artery dissection will cause great damage and affect people's health, which requires people’s attention.
Different Doses of β‐Cryptoxanthin May Secure the Retina from Photooxidative Injury Resulted from Common LED Sources
Authors: Orhan Cemal , Tuzcu Mehmet , Gencoglu Hasan , Sahin Emre , Sahin Nurhan , Ozercan Ibrahim Hanifi , Namjoshi Tejas , Srivastava Vandita , Morde Abhijeet , Rai Deshanie , Padigaru Muralidhara , Sahin Kazim
Published: February 2021

Retinal damage associated with loss of photoreceptors is a hallmark of eye diseases such as age‐related macular degeneration (AMD) and diabetic retinopathy. Potent nutritional antioxidants were previously shown to abate the degenerative process in AMD. β‐Cryptoxanthin (BCX) is an essential dietary carotenoid with antioxidant, anti‐inflammatory, and provitamin A activity. It is a potential candidate for developing intervention strategies to delay the development/progression of AMD. In the current study, the effect of a novel, highly purified BCX oral formulation on the rat retinal damage model was evaluated. Rats were fed with BCX for four weeks at the doses of 2 and 4 mg/kg body weight in the form of highly bioavailable oil suspension, followed by retinal damage by exposing to the bright light‐emitting diode (LED) light (750 lux) for 48 hrs. Animals were sacrificed after 48 hours, and eyes and blood samples were collected and analyzed. BCX supplementations (2 and 4 mg/kg) showed improvements in the visual condition as demonstrated by histopathology of the retina and measured parameters such as total retinal thickness and outer nuclear layer thickness. BCX supplementation helped reduce the burden of oxidative stress as seen by decreased serum and retinal tissue levels of malondialdehyde (MDA) and restored the antioxidant enzyme activities in BCX groups. Further, BCX supplementation modulated inflammatory markers (IL‐1β, IL‐6, and NF‐κB), apoptotic proteins (Bax, Bcl‐2, caspase 3), growth proteins and factors (GAP43, VEGF), glial and neuronal proteins (GFAP, NCAM), and heme oxygenase‐1 (HO‐1), along with the mitochondrial stress markers (ATF4, ATF6, Grp78, Grp94) in the rat retinal tissue. This study indicates that oral supplementation of BCX exerts a protective effect on light‐induced retinal damage in the rats via reducing oxidative stress and inflammation, also protected against mitochondrial DNA damage and cellular death.
When All Else Fails: A Rare Case of Postoperative Toxic Shock Syndrome Arising from Surgical Site Infection after Decompressive Neurectomy Successfully Treated with Angiotensin-2
Authors: Chandra Raghav , Gold Samuel , Kohler Casey , Valladares Jason , Hennessy Sara A. , Bhat Sneha G.
Published: February 2021

Toxic shock syndrome is a serious complication of Streptococcus pyogenes or Staphylococcus aureus infections associated with very high morbidity and mortality. Postoperative toxic shock syndrome is an extremely rare phenomenon which manifests as fevers, diffuse rash, septic shock, and death. We present the first reported case of toxic shock syndrome associated with a surgical site infection from a decompressive neurectomy for refractory migraines in a 41-year-old female as well as the first use of angiotensin-2 vasopressor therapy to treat persistent septic shock from toxic shock syndrome refractory to conventional therapies.