bluuebunny/crossref_metadata_2025 huggingface dataset:
Seasonal regulation of river discharge by the cascade reservoirs in the Lancang River and its effect on downstream freshwater and estuarine saltwater intrusion
Authors: Zhu Jianrong , Qiu Wei , Tang Chuanmin , Cheng Xinyue
Published: November 2021

This study assesses the seasonal regulation of river discharge by hydropower dam-induced cascade reservoirs in the Lancang River and its effect on downstream freshwater and estuarine saltwater intrusion. There are eight main reservoirs in the Lancang River, with a total regulation capacity of 25.67 billion m3, which regulates river discharge by conserving water in the flood season and releasing water in the dry season. River discharge during the dry season from 1960 to 2009 accounted for 21% of the annual discharge before the cascade reservoirs were constructed and increased to 33% from 2010 to 2015 after the cascade reservoirs were constructed at the Jinghong hydrological station, which is the lowermost station in the Lancang River. During the 2016 extreme drought in the lower Mekong River basin, the river discharge increased by 550, 367, 1283, 969, and 524 m3/s in January, February, March, April, and May, respectively, regulated by the cascade reservoirs at the Jinghong hydrological station. Considering runoff, tides, wind, and continental shelf currents, a high-resolution three-dimensional numerical model was used to simulate the effect of regulation of river discharge by the cascade reservoirs in the Lancang River on the saltwater intrusion in the Mekong River Delta (MRD). The simulation results show that the seasonal regulation of river discharge by the cascade reservoirs in the Lancang River weakens estuarine saltwater intrusion during the dry season, especially in the sand bar areas, which is much more significant in the extreme dry season of 2016. The seasonal regulation of river discharge by the reservoirs in the Lancang River makes the seasonal distribution of downstream river discharge more uniform, favoring downstream freshwater utilization and alleviating flood disasters and saltwater intrusion in the MRD.
Ruthenium(II)–arene complexes with chelating quinoline ligands as anti-amyloid agents
Authors: Meiss Cade J. , Bothwell Paige J. , Webb Michael I.
Published: November 2021

Recent recognition of the soluble form of the amyloid-beta (Aβ) peptide as a neurotoxic agent in Alzheimer’s disease (AD) has spurred the development of agents to target this species. Because Aβ is known to chelate metal ions in solution, metal-based therapeutics are uniquely suited to exploit this affinity, where coordination to Aβ has been shown to impact the neurotoxicity of the peptide. Ruthenium(II)–arene complexes are unique candidates for evaluation, as one face of the molecule is blocked by the hydrophobic arene ring, while coordination to the Aβ peptide can occur on the other side of the molecule. We have prepared and evaluated two Ru(II)–arene complexes with chelating quinoline-based ligands, Ru1 and Ru2, for their respective anti-amyloid abilities. Although both complexes decreased the aggregation of soluble Aβ, Ru1 displayed promise in disrupting formed aggregates of the peptide. These findings represent an exciting new avenue for therapeutic development in AD, where both sides of the aggregation equilibrium are affected.
Thermal transitions in metastable Cu – 68.5 at. % Co alloy
Authors: Jegede Oluwatoyin E. , Haque Nafisul , Mullis Andrew M. , Cochrane Robert F.
Published: November 2021

The arc melted and drop tube processed Cu – 68.5 at. % Co alloy was subjected to differential thermal analysis (DTA). The liquidus temperature determined from the DTA curves of the arc melt sample (1664 K) was found to be close to the phase diagram estimate of 1662 K. In contrast, as a result of liquid phase separation in the drop-tube samples, the values obtained in the powders were much lower, mainly because the compositions of the demixed phases varied from those of the parent melt. The liquidus temperature of the 850+ μm powder was 1632 K, whereas that of the <38 μm sieve powder was 1616 K. This variance was due to the asymmetric nature of the metastable phase diagram of the system.
Comprehensive quasi-Einstein spacetime with application to general relativity
Authors: Gupta Punam , Singh Sanjay Kumar
Published: November 2021

The aim of this paper is to extend the notion of all known quasi-Einstein (QE) manifolds like generalized QE, mixed generalized QE manifold, pseudo generalized QE manifold and many more and name it comprehensive QE manifold [Formula: see text]. We investigate some geometric and physical properties of the comprehensive QE manifolds [Formula: see text] under certain conditions. We study the conformal and conharmonic mappings between [Formula: see text] manifolds. Then we examine the [Formula: see text] with harmonic Weyl tensor. We define the manifold of comprehensive quasi-constant curvature and prove that conformally flat [Formula: see text] is manifold of comprehensive quasi-constant curvature and vice versa. We study the general two viscous fluid spacetime [Formula: see text] and find out some important consequences about [Formula: see text]. We study [Formula: see text] with vanishing space matter tensor. Finally, we prove the existence of such manifolds by constructing nontrivial example.
Interpretable Aspect-Aware Capsule Network for Peer Review Based Citation Count Prediction
Authors: Li Siqing , Li Yaliang , Zhao Wayne Xin , Ding Bolin , Wen Ji-Rong
Published: November 2021

Citation count prediction is an important task for estimating the future impact of research papers. Most of the existing works utilize the information extracted from the paper itself. In this article, we focus on how to utilize another kind of useful data signal (i.e., peer review text) to improve both the performance and interpretability of the prediction models.

Specially, we propose a novel aspect-aware capsule network for citation count prediction based on review text. It contains two major capsule layers, namely the feature capsule layer and the aspect capsule layer, with two different routing approaches, respectively. Feature capsules encode the local semantics from review sentences as the input of aspect capsule layer, whereas aspect capsules aim to capture high-level semantic features that will be served as final representations for prediction. Besides the predictive capacity, we also enhance the model interpretability with two strategies. First, we use the topic distribution of the review text to guide the learning of aspect capsules so that each aspect capsule can represent a specific aspect in the review. Then, we use the learned aspect capsules to generate readable text for explaining the predicted citation count. Extensive experiments on two real-world datasets have demonstrated the effectiveness of the proposed model in both performance and interpretability.
ITO/Poly-3-Methylaniline/Au Electrode for Electrochemical Water Splitting and Dye Removal
Authors: Abdelazeez Ahmed Adel A. , El-Fatah Gehad Abd , Shaban Mohamed , Ahmed Ashour M. , Rabia Mohamed
Published: November 2021

Application of aniline derivative semiconductor nanopolymer and its Au composite for H2 generation and dye removal were investigated. Electrochemical polymerization of poly-3-methylaniline (P3MA) on ITO glass was carried out for acid medium. Au nanoparticles with crystal sizes of 15 and 30 nm were sputter coated on the surface. Chemical structure of the polymer and its composite was characterized using FTIR, XRD, 1HNMR, SEM, and UV-Vis. All function groups were confirmed using FTIR analyses. XRD confirmed the formation of nanopolymer with a crystal size of ∼15 nm. SEM confirmed the formation of smooth lamellar surface feature with a <20 nm nanoporous structure. Porosity and particle sizes increases with Au coating, confirmed using the modeling Image J program. Optical analysis also demonstrated that the strength of P3MA absorption peaks increases with rising Au coating time, in which the bandgap values changed from 1.64 to 1.63 eV for 15 and 30 nm Au, respectively. The photoelectrode ITO/PMT/30 nm Au was applied for H2 generation and dye removal. The current density (J
ph) values were −0.3 and −1.6 mA.cm−2 in the absence and presence of the Congo red dye, respectively. The incident photon-to-current conversion efficiency (IPCE%) for the electrode was 2.3 at 390 nm. The activation energy (E

a
) was 31.49 KJ mol−1. The enthalpy (∆H

*
) and entropy (∆S

*
) values were 114.49 and 160.46 JK−1 mol−1, respectively. A simple mechanism for the H2 generation and dye removal is mentioned.
Fecal microbiome and bile acid metabolome in adult short bowel syndrome
Authors: Boutte Harold J. , Chen Jacqueline , Wylie Todd N. , Wylie Kristine M. , Xie Yan , Geisman Mackenzie , Prabu Anirudh , Gazit Vered , Tarr Phillip I. , Levin Marc S. , Warner Brad W. , Davidson Nicholas O. , Rubin Deborah C.
Published: November 2021

Loss of intestinal surface area causes short bowel syndrome, intestinal failure, and parenteral nutrition dependence. We analyzed the gut microbiota and bile acid metabolome of a large cohort of short bowel syndrome adult patients with different postsurgical anatomies. We report a novel analysis of the microbiome of patients with ileostomy and jejunostomy. Enrichment of specific microbial and bile acid species may be associated with the ability to wean from parenteral nutrition.
Accurate Identification of Agricultural Inputs Based on Sensor Monitoring Platform and SSDA‐HELM‐SOFTMAX Model
Authors: Zou Juan , Jiang Hanjing , Wang Qingxiu , Chen Ningxia , Wu Ting , Yang Ling
Published: November 2021

The unreliability of traceability information on agricultural inputs has become one of the main factors hindering the development of traceability systems. At present, the major detection techniques of agricultural inputs were residue chemical detection at the postproduction stage. In this paper, a new detection method based on sensors and artificial intelligence algorithm was proposed in the detection of the commonly agricultural inputs in Agastache rugosa cultivation. An agricultural input monitoring platform including software system and hardware circuit was designed and built. A model called stacked sparse denoising autoencoder‐hierarchical extreme learning machine‐softmax (SSDA‐HELM‐SOFTMAX) was put forward to achieve accurate and real‐time prediction of agricultural input varieties. The experiments showed that the combination of sensors and discriminant model could accurately classify different agricultural inputs. The accuracy of SSDA‐HELM‐SOFTMAX reached 97.08%, which was 4.08%, 1.78%, and 1.58% higher than a traditional BP neural network, DBN‐SOFTMAX, and SAE‐SOFTMAX models, respectively. Therefore, the method proposed in this paper was proved to be effective, accurate, and feasible and will provide a new online detection way of agricultural inputs.
Controlling the Emission Properties of Quantum Rods via Multiscale 3D Ordered Organization
Authors: Bizien Thomas , Postic Marie , Even-Hernandez Pascale , Panizza Pascal , Mériadec Cristelle , Meneau Florian , Mazari-Arrighi Elsa , Dupuis Christophe , Gosse Charlie , Cotlet Mircea , Gang Oleg , Marchi Valérie , Artzner Franck
Published: November 2021

A specific organization of optically active nanoscale objects can greatly affect the optical response of a system. Here, we report the controlled modification of the fluorescent emission by the assembly of water-soluble quantum rods (QRs). Our study combines optical, electron microcopy, and X-ray scattering characterizations to reveal a correlation between the self-assembly behavior of QRs into ordered 3D-arrays and the optical properties (luminescence) of formed assemblies, where the observed optical response is highly dependent on the QR aspect ratio. Specifically, shorter, 18 nm long QRs (QR18), exhibiting a well-defined smectic packing, demonstrate an enhancement of the emission intensity accompanied by a red shift and a lifetime reduction. In contrast, 40 nm long QRs (QR40), forming a columnar phase, does not show these optical properties.
Availability Optimization of Multicomponent Products with Economic Dependence under Two-Dimensional Warranty
Authors: Dong Enzhi , Cheng Zhonghua , Wang Rongcai , Zhang Xiaona
Published: November 2021

For multicomponent products, the maintenance of every component separately will increase the downtime and reduce the availability of products during the warranty period. To solve this problem, the economic dependence between the components is considered in this paper. Firstly, a single-component two-dimensional (2D) preventive maintenance (PM) availability model is established, and the simulated annealing algorithm is adopted to calculate the optimal 2D PM interval to achieve the maximal availability of any single component. Then, to ensure that the warranty cost of each component does not exceed the budget, the PM benchmark interval is introduced, and the PM work is optimized following the method of grouping maintenance. Based on this, the 2D preventive grouping maintenance availability model of multicomponent products is established. Finally, an example is given to verify the proposed method, and the results indicate that the proposed method increases the availability of multicomponent products during the 2D warranty period.
Continuous Differential Microemulsion Polymerization to Prepare Nanosized Polymer Latices in Microreactors
Authors: Qiu Min , Xiang Liang , Shang Minjing , Su Yuanhai
Published: November 2021

Microreactors are a promising platform for continuous synthesis of polymer latices when combined with emulsion polymerization. However, this application has long been haunted by fouling and clogging problems. In this work, we proposed the strategy of conducting differential microemulsion polymerization in microreactors within a biphasic slug flow and achieved rapid and stable preparation of nanosized PMMA latices (polymeric content as high as 15.7% with average particle size smaller than 20 nm). We started by exploring the temperature thresholds with thermal and redox initiation, the effect of initiator concentration, and the kinetic characteristics of microemulsion polymerization at different temperatures. Then, as for the differential microemulsion polymerization, extensive investigation was made into the effects of the volumetric flow ratio, the prepolymerization time, the initiator concentration, and the solid content of the initial microemulsion. Finally, we compared the differential microemulsion polymerization with the soap-free emulsion polymerization in the slug flow. The striking advantages in the polymerization rate, the average particle diameter, and the size distribution reflected higher density of particle nuclei, larger specific surface area of particles, and the pivotal effect of the persistent particle nucleation in the microemulsion polymerization.
The Locating Chromatic Number of Book Graph
Authors: Inayah Nur , Aribowo Wisnu , Windra Yahya Maiyudi Mariska
Published: November 2021

Let

G
=

V

G

,
E

G

be a connected graph and

c
:
V

G

⟶

1,2
,
…
,
k

be a proper

k

-coloring of

G

. Let

Π

be a partition of vertices of

G

induced by the coloring

c

. We define the color code

c

Π

v

of a vertex

v
∈
V

G

as an ordered

k

-tuple that contains the distance between each partition to the vertex

v

. If distinct vertices have distinct color code, then

c

is called a locating

k

-coloring of

G

. The locating chromatic number of

G

is the smallest

k

such that

G

has a locating

k

-coloring. In this paper, we determine the locating chromatic number of book graph.
A Blockchain‐Based Federated Learning Method for Smart Healthcare
Authors: Chang Yuxia , Fang Chen , Sun Wenzhuo
Published: November 2021

The development of artificial intelligence and worldwide epidemic events has promoted the implementation of smart healthcare while bringing issues of data privacy, malicious attack, and service quality. The Medical Internet of Things (MIoT), along with the technologies of federated learning and blockchain, has become a feasible solution for these issues. In this paper, we present a blockchain‐based federated learning method for smart healthcare in which the edge nodes maintain the blockchain to resist a single point of failure and MIoT devices implement the federated learning to make full of the distributed clinical data. In particular, we design an adaptive differential privacy algorithm to protect data privacy and gradient verification‐based consensus protocol to detect poisoning attacks. We compare our method with two similar methods on a real‐world diabetes dataset. Promising experimental results show that our method can achieve high model accuracy in acceptable running time while also showing good performance in reducing the privacy budget consumption and resisting poisoning attacks.
An Improved Tunnel‐Track Model in Saturated Poroelastic Soils to a Moving Point Load
Authors: Fu Zunan , Xu Yuanlei , Yuan Zonghao , Shi Li , Wang Guoshuai , Song Wenbo , Yu Yanming
Published: November 2021

To predict the mechanical response of a circular cavity/tunnel buried in saturated poroelastic soils to a moving point load, a semianalytical model is provided in this work. The soils are governed by Biot’s theory that describes the wave propagations for saturated poroelastic materials. The displacement and stress vectors for the solid skeleton and pore‐water fluid are represented by scalar and vectorial potentials. The governing equations for the tunnel and surrounding soils are solved in the frequency domain with the aid of separation of variables and Fourier transformations. To check the feasibility of the present analytical model, the solution is compared with other available results calculated for the ring load case. The good agreement shows the correctness of the present model. Numerical results suggest that the mechanical response from a moving point load in a tunnel for two‐phase poroelastic materials is quite different from that in single‐phase elastic materials. The critical velocity of the tunnel‐soil system is around the shear wave speed of soils while the second one introduced into the track‐tunnel‐soil system with very high value is around the critical velocity of the track structure itself.
Neural Network Segmentation Algorithm-Based Magnetic Resonance Imaging to Explore the Relationship between Cerebrospinal Fluid Flow with Communicating Hydrocephalus after Decompressive Craniectomy for Craniocerebral Injury
Authors: Wang Yan , Zhang Yanmin , Zhang Chunyue
Published: November 2021

This study aimed to explore the application value of magnetic resonance imaging optimized by neural network segmentation algorithm in analyzing the relationship between cerebrospinal fluid changes after decompressive craniectomy and the occurrence of communicating hydrocephalus. 100 patients with craniocerebral injury undergoing decompressive craniectomy in hospital were selected as research subjects. The collected MRI images were processed using the OTSU algorithm, the cerebrospinal fluid flow rate was calculated based on the observation results, and the MRI based on the neural network segmentation algorithm was used to analyze the relationship between the occurrence of communicating hydrocephalus with the cerebrospinal fluid flow after decompressive craniectomy for craniocerebral injury. Additionally, the dynamics of the flow of cerebrospinal fluid in the midbrain aqueduct was analyzed. After decompressive craniectomy for craniocerebral injury, of the 24 cases of cerebrospinal fluid accumulation, 23 cases had hydrocephalus; of the 55 cases of cerebrospinal fluid flow disorder, hydrocephalus occurred in 47 cases; and of the 21 cases of normal cerebrospinal fluid, no patients had hydrocephalus. For patients with communicating hydrocephalus, the cerebrospinal fluid flow at the aqueduct was obviously accelerated and the flow was increased. From this, the differential diagnosis of cerebrospinal fluid and communicating hydrocephalus can be further confirmed. The results showed that the third ventricle of the study group was significantly reduced, and the flow of cerebrospinal fluid was similar to that of normal people. It suggested that decompressive craniectomy can relieve communicating hydrocephalus. In patients with communicating hydrocephalus, the cerebrospinal fluid flow at the aqueduct was significantly accelerated, the flow amount was increased, and the blocked flow of cerebrospinal fluid can also lead to hydrocephalus, which further clarified the relationship between the occurrence of communicating hydrocephalus with the flow of cerebrospinal fluid. In short, the neural network segmentation algorithm-based magnetic resonance imaging demonstrated a good value in the analysis of craniocerebral injury, from which the doctor observed that the cerebrospinal fluid flow at the aqueduct was significantly accelerated. Its detection of brain complications after decompressive craniectomy was also effective.
Discussion on the Design and Performance of the Whole Packaging Box of Environmentally Friendly Packaging Materials
Authors: Xie Mengwei
Published: November 2021

More and more designers and companies in the packaging industry begin to pay attention to research on environmentally friendly packaging design. From studying the additional functions of packaging to starting to study the environmentally friendly materials of packaging, as well as the “zero‐pollution” packaging advocated today, the traditional form and mode of packaging has changed. This article aims to study the design of the overall packaging box of environmentally friendly packaging materials and discuss its performance. In this paper, the platform construction method and the modulus definition classification method are used to calculate the positive axis stiffness of the single‐layer board. The effect of coating process on the wear resistance of paper‐based materials was studied, the wear resistance of box board base paper and coated box board under different temperatures and different humidity conditions was compared, and the optimal design variable value range was set. The experimental results show that after the first level of optimization, the overall mass of the structure is reduced from the initial 39.42 kg to 31.18 kg and the optimization efficiency is 20.90%; the maximum relative deformation of the flap structure has increased from 0.143 mm to 0.198 mm, despite having the maximum tension. The opening displacement has increased, but it still meets the sealing deformation requirements. The design and performance discussion of the overall packaging box of environmentally friendly packaging materials have been completed relatively well.
Teachers’ Perception of Their Work Environment: Evidence from the Primary and Secondary Schools of Bangladesh
Authors: Masoom Muhammad Rehan
Published: November 2021

The work environment includes conducive aspects such as (1) organizational encouragement, (2) supervisory encouragement, and (3) workgroup support, as well as toxic conditions like (4) teaching impediments and (5) workload pressure; the objective of the research is which of the factors and what are the elements of those factors teachers perceive as constituting the conducive and toxic environment. The research also outlines the effects of years of experience and the level of teaching on the specified factors. The study used a quantitative-based cross-sectional survey to analyze teachers’ perceptions of their work environment. A questionnaire comprised some background information, and 34 close-ended questions were used to elicit the responses. About 368 (230 males and 138 females) teachers participated in the survey. Structural equation models were constructed, where the five mentioned factors were part of two second-order formative constructs. Independent sample t-test was estimated to outline gender-wise and teaching level-wise (primary and secondary) variation, whereas Pearson correlation coefficients were calculated to check whether the experience was correlated with any of the perceived factors of the work environment. It is found that workgroup encouragement, particularly having good relations with the principal, is the most important factor in the conducive environment of the school. The physical facilities were the least, whereas promoting positive behavior by avoiding conflict and ensuring fairness was the most important aspect of organizational encouragement. Teaching impediments were mostly shaped by how often teachers require dealing with disruptive and violent pupils. Teachers perceived too many after-school meetings, unreasonable deadlines, and office staffs’ inspections enhance their workload pressure. The more a teacher became experienced, the more he or she positively perceived the conducive environment of the school. The findings can serve as a guide for educational policymakers and school administrators to identify which factors in the school environment need urgent attention and modification.
Human Detection via Image Denoising for 5G‐Enabled Intelligent Applications
Authors: Li Hui , Zhou Hang , Liang Xiaoguo , Cai Fen , Xu Lingwei , Kong Wei , Guo Ying
Published: November 2021

5G technology strongly supports the development of various intelligent applications, such as intelligent video surveillance and autonomous driving. And the human detection technology in intelligent video surveillance has also ushered in new challenges. A number of video images will be compressed for efficient transmission; the resulting incomplete feature representation of images will drop the human detection performance. Therefore, in this work, we propose a new human detection method based on compressed denoising. We exploit the quality factor in the compressed image and incorporate the pixel_shuffle inverse transform based on FFDNet to effectively improve the performance of image compression denoising, then HRNet and HRFPN are used to extract and fuse high‐resolution features of denoised images, respectively, to obtain high‐quality feature representation, and finally, a cascaded object detector is used for classification and bounding box regression to further improve object detection performance. At last, the experimental results on PASCAL VOC show that the proposed method effectively removes the compression noise and further detects human objects with multiple scales and different postures. Compared with the state‐of‐the‐art methods, our method achieved better detection performance and is, therefore, more suited for human detection tasks.
Growth and Yield of Different Varieties of True Shallot Seed on Highland in West Sumatra, Indonesia
Authors: Atman  , Suliansyah Irfan , Anwar Aswaldi , Yasin Syafrimen
Published: November 2021

Cultivation of true shallot seeds has the potential to be developed in Indonesia because apart from being able to reduce the cost of providing seeds, it also has higher productivity than shallot from tubers. This study aims to determine the appearance of true shallot seed varieties that have high yield potential in the highlands of West Sumatra. The study used a randomized complete block design (RCBD) with 4 treatments of true shallot seed varieties, namely, Trisula, Bima, Lokananta, and Sanren, with 6 replications. The results showed that except for the age of harvest and the number of tubers per hill, the treatment of various varieties of true shallot seeds showed a significant effect on all observed variables. Lokananta variety has better growth component, yield component, and yields compared to other varieties (Trisula, Bima, and Sanren). Cultivation of true shallot seeds in the highlands gives lower yields than in the adapted area (lowland), except for the Trisula variety. Lokananta variety is recommended for use in the highlands of West Sumatra.
A Safety Evaluation Model of Intersections under Mixed Traffic Conditions Using Traffic Conflicts and Cloud Model
Authors: Vuong Xuan Can , Mou Rui-Fang , Vu Trong Thuat , Tran Van Hung , Nguyen Chi Trung
Published: November 2021

Safety evaluation of traffic conflict is a very important and challenging issue in evaluating intersection safety under incomplete traffic accident data conditions and is also one of the main safety surrogate measures of analyzing accident data recently. It helps to analyze and solve intersection problems comprehensively and deeply. From there, it helps to improve traffic safety as well as reduce the risk of traffic accidents at intersections. Various evaluation methods based on traffic conflict have been proposed to make conflict safety levels at intersections more consistent and objective. However, a major concern is that many existing measurements are still subjective and are not easy to obtain uniformly. This study aimed to develop a model for safety evaluation at intersections in a comprehensive way that may be expected to directly link to the severity of the accident from different evaluation indicators. First, the three factors, including time to collision (TTC), conflicting speed (CS), and deceleration rate (DR) to avoid a crash, are introduced into safety evaluation of conflicts as the indicators. And then, as regards the fuzziness and randomness of the evaluation indicators, the qualitative concept has to be converted into a quantitative one utilizing cloud model, which implements the natural transformation between the qualitative concept of the safety level of traffic conflict and the membership degree of the evaluation indicators corresponding to the different safety levels. Finally, an indicator weight model is built based on the information entropy and the AHP method to determine the safety level. We illustrate the practical implementation of the proposed method using actual data of a typical signalized intersection from Hanoi City of Vietnam. The results indicate that traffic conflict analyzed by the proposed method was appropriate with actual state of the intersection, and the proposed method is simple, effective, and feasible, so it has a certain application value.
Optimization for the Redundancy Allocation Problem of Reliability Using an Improved Particle Swarm Optimization Algorithm
Authors: Marouani H.
Published: November 2021

This paper presents an enhanced and improved particle swarm optimization (PSO) approach to overcome reliability-redundancy allocation problems in series, series-parallel, and complex systems. The problems mentioned above can be solved by increasing the overall system reliability and minimizing the system cost, weight, and volume. To achieve this with these nonlinear constraints, an approach is developed based on PSO. In particular, the inertia and acceleration coefficients of the classical particle swarm algorithm are improved by considering a normal distribution for the coefficients. The new expressions can enhance the global search ability in the initial stage, restrain premature convergence, and enable the algorithm to focus on the local fine search in the later stage, and this can enhance the perfection of the optimization process. Illustrative examples are provided as proof of the efficiency and effectiveness of the proposed approach. Results show that the overall system reliability is far better when compared with that of some approaches developed in previous studies for all three tested cases.
Lower Semicontinuity in

L

1

of a Class of Functionals Defined on
B
V
with Carathéodory Integrands
Authors: Wunderli T.
Published: November 2021

We prove lower semicontinuity in

L

1

Ω

for a class of functionals

G
:
B
V

Ω

⟶
ℝ

of the form

G

u

=

∫

Ω

g

x

,

∇

u

d
x
+

∫

Ω

ψ

x

d

D

s

u

where

g
:
Ω
×

ℝ

N

⟶
ℝ

,

Ω
⊂

ℝ

N

is open and bounded,

g

·
,
p

∈

L

1

Ω

for each

p
,

satisfies the linear growth condition

lim

p

⟶

∞

g

x
,
p

/

p

=
ψ

x

∈
C

Ω

∩

L

∞

Ω

,

and is convex in

p

depending only on

p

for a.e.

x
.

Here, we recall for

u
∈
B
V

Ω

; the gradient measure

D
u
=
∇
u
 
d
x
+
d

D

s

u

x

is decomposed into mutually singular measures

∇
u
 
d
x

and

d

D

s

u

x

. As an example, we use this to prove that

∫

Ω

ψ

x

α

2

x

+

∇
u

2

 
d
x
+

∫

Ω

ψ

x

d

D

s

u

is lower semicontinuous in

L

1

Ω

for any bounded continuous

ψ

and any

α
∈

L

1

Ω

.

Under minor addtional assumptions on

g

, we then have the existence of minimizers of functionals to variational problems of the form

G

u

+

u
−

u

0

L

1

for the given

u

0

∈

L

1

Ω

,

due to the compactness of

B
V

Ω

in

L

1

Ω

.
Generalized Ulam–Hyers–Rassias Stability Results of Solution for Nonlinear Fractional Differential Problem with Boundary Conditions
Authors: Naimi A. , Tellab B. , Altayeb Y. , Moumen A.
Published: November 2021

The problem of existence and generalized Ulam–Hyers–Rassias stability results for fractional differential equation with boundary conditions on unbounded interval is considered. Based on Schauder’s fixed point theorem, the existence and generalized Ulam–Hyers–Rassias stability results are proved, and then some examples are given to illustrate our main results.
A Generalizable Sample Resolution Augmentation Method for Mechanical Fault Diagnosis Based on ESPCN
Authors: Chu Zhenyun , Ji Shanshan , Wang Jinrui , Wang Xiaoyu , Zhang Zongzhen , Zhao Xuefeng , Han Baokun
Published: November 2021

Data augmentation has become a hot topic in the field of mechanical intelligent fault diagnosis. It can expand the limited training dataset by generating simulated samples, but there is still no effective method augmenting the resolution of low resolution sample. In this paper, a simple algorithm, namely, efficient subpixel convolutional neural network (ESPCN), is proposed to solve this deficiency. The ESPCN model performs the arrange operation on the raw low resolution data through the subpixel layer and outputs the result of four‐channel multifeature maps. Then, the sample resolution is increased to four times compared with the raw low resolution sample. Finally, the generated high resolution dataset is employed to train the stacked autoencoders (SAE) for fault classification, and the raw high resolution dataset is used for testing. Two fault diagnosis cases with different sample dimensions and rotating speeds are set up to simulate the low resolution situation, and the experimental results verify the feasibility of the proposed algorithm.
Deep Learning Approach for Stages of Severity Classification in Diabetic Retinopathy Using Color Fundus Retinal Images
Authors: Goel Silky , Gupta Siddharth , Panwar Avnish , Kumar Sunil , Verma Madhushi , Bourouis Sami , Ullah Mohammad Aman
Published: November 2021

Diabetes is a very fast-growing disease in India, with currently more than 72 million patients. Prolonged diabetes (about almost 20 years) can cause serious loss to the tiny blood vessels and neurons in the patient eyes, called diabetic retinopathy (DR). This first causes occlusion and then rapid vision loss. The symptoms of the disease are not very conspicuous in its early stage. The disease is featured by the formation of bloated structures in the retinal area called microaneurysms. Because of negligence, the condition of the eye worsens into the generation of more severe blots and damage to retinal vessels causing complete loss of vision. Early screening and monitoring of DR can reduce the risk of vision loss in patients with high possibilities. But the diabetic retinopathy detection and its classification by a human, is a challenging and error-prone task, because of the complexity of the image captured by color fundus photography. Machine learning algorithms armed with some feature extraction techniques have been employed earlier to detect and classify the levels of DR. However, these techniques provide below-par accuracy. Now, with the advent of deep learning (DL) techniques in computer vision, it has become possible to achieve very high levels of accuracy. DL models are an abstraction of the human brain coupled with the eyes. To create a model from scratch and train it is a cumbersome task requiring a huge amount of images. This deficiency of the DL techniques can be patched up by employing another technique to a task called transfer learning. In this, a DL model is trained on image metadata, and to learn features it used hundreds of classes from the DR fundus images. This enables professionals to create models capable of classifying unseen images into a proper grade or level with acceptable accuracy. This paper proposed a DL model coupled with different classifiers to classify the fundus image into its correct class of severity. We have trained the model on IDRD images and it has proven to show very high accuracy.
Improving Self-Resilience in Students with Special Needs through the Counseling Teachers’ Roles: A Case Study on Grounded Theory
Authors: Azwar Beni , Wanto Deri , Hidayat Rahmad
Published: November 2021

Previous studies show that self-resilience was significantly improved in students with special needs by supporting the social environment and the learning system. Additionally, support for the role of counseling teachers in inclusive schools fosters self-resilience. In this regard, this study aimed to understand the role of counseling teachers foster self-resilience among students with special needs in inclusive schools. The grounded theory approach was applied to produce theories related to these issues. The participants included eleven counseling teachers and the special needs students drawn from three schools in West Sumatra and Bengkulu, Indonesia. The data collected were analyzed based on three stages of grounded analysis, including open coding, axial coding, and selective coding. The findings indicated that self-resilience among students with special needs grows when the counseling teachers use three roles, namely, modifying behavior, giving instructions repeatedly and providing options according to students’ interest.
Clinical Outcomes and Prognostic Factors for Patients with Malignant Peripheral Nerve Sheath Tumour
Authors: Imura Yoshinori , Outani Hidetatsu , Takenaka Satoshi , Yasuda Naohiro , Nakai Sho , Nakai Takaaki , Wakamatsu Toru , Tamiya Hironari , Hamada Kenichiro , Kakunaga Shigeki
Published: November 2021

Introduction. Few studies have described the characteristics and prognostic factors of patients with malignant peripheral nerve sheath tumour (MPNST). In this study, we retrospectively investigated the clinicopathological features, clinical outcomes, and prognostic factors of these patients. Patients and Methods. We recruited patients with MPNST who were treated at our institutions from 1991 to 2020. We collected and statistically analysed information on patient-, tumour-, and treatment-related factors. The median follow-up period was 61 months (range, 1–335.8 months). Results. A total of 60 patients (31 males, 29 females) with a median age of 55 years (range, 8–84 years) at initial diagnosis were included. The median tumour size was 7 cm (range, 1.6–30 cm) in the greatest dimension. The 5-year overall survival (OS) rate of all patients was 69.5%. Univariate analysis revealed that large-sized tumour, metastasis at diagnosis, and no surgery of the primary tumour were significantly associated with patients with worse OS. Multivariate analysis identified surgery of the primary tumour as an independent prognostic factor for improved OS. Among patients with localised disease at diagnosis who underwent surgery of the primary tumour at our institutions, the 5-year OS, local recurrence-free survival (LRFS), and metastasis-free survival (MFS) rates were 81.1%, 78.2%, and 70.3%, respectively. Univariate analysis revealed that positive surgical margin was significantly correlated with unfavourable OS and LRFS, and high grade was a poor prognostic indicator for MFS. Conclusion. Complete surgical resection with negative surgical margins is necessary for a successful MPNST treatment. Multidisciplinary management of MPNST with aggressive features is important for optimising patient outcomes.
A Comparative Study of Hematological Parameters of Endurance Runners at Guna Athletics Sport Club (3100 Meters above Sea Level) and Ethiopian Youth Sport Academy (2400 Meters above Sea Level), Ethiopia
Authors: Tilahun Muche Zelalem , Haile Wondimu Diresibachew , Bayissa Midekssa Milkessa , Chekol Abebe Endeshaw , Mengie Ayele Teklie , Abebe Zewdie Ediget
Published: November 2021

Introduction. Endurance running performance is dependent upon hematological, physiological, anthropometrical, diet, genetic, and training characteristics. Increased oxygen transport and efficiency of tissue in extracting oxygen are the major determinants to competitions that require endurance. Thus, altitude training is often employed to increase blood oxygen-carrying capacity to improve sea-level endurance performance. This study aimed to compare hematological parameters of endurance runners’ training at different clubs with different altitudes (Guna Athletics Sport Club at Guna (3100 meter above sea level) and Ethiopian Youth Sport Academy at Addis Ababa (2400 meter above sea level)). Methods. A comparative cross-sectional study was conducted at GASC and EYSA. Data were collected from a total of 102 eligible study subjects (26 runners and 25 controls at Guna and 26 runners and 25 controls at Addis Ababa) from May to October 2019. About 3 ml of the venous blood was drawn from the antecubital vein by aseptic procedure and analyzed using a hematology analyzer (DIRUI BCC-3000B, China). One-way ANOVA and independent-sample t-tests were used to compare means. Result. Male runners in Guna had significantly higher hemoglobin (Hgb), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and white blood cell (WBC) count than male runners in Addis Ababa. Besides, female runners in Guna had significantly higher MCH and MCHC than female runners in Addis Ababa. However, there were no significant differences between Guna and Addis Ababa runners in red blood cell (RBC) count, Hct, MCV, and platelet count in both sexes, while Hgb and WBC count in females. Conclusion. Decisively, Guna Athletics Sport Club endurance runners had significantly higher hematological parameters than Ethiopian Youth Sport Academy endurance runners. This provides invaluable information for coaches and sport physicians to monitor the hematological profile and the health status of an athlete living and training at different altitudes.
Effects of Bilingualism on Reading Fluency: An Analysis of Pausing Patterns of Iranian Learners of English as a Third Language
Authors: Banitalebi Zahra , Jabbari Ali Akbar , Tilwani Shouket Ahmad , Razmi Mohammad Hasan
Published: November 2021

Fluency is one of the most important components of oral proficiency, which can be affected by a number of variables including frequency, duration, and place of pause phenomena. The present study aimed at investigating the effect of bilingualism on learning a foreign language from the angle of fluency and pausing patterns by comparing the pausing patterns of monolingual (Persian speakers) and bilingual (Iranian Turkish speakers; L1: Turkish and L2: Persian) EFL learners. To this end, a sample of 40 male and female advanced EFL learners were selected from Yazd University and several English-language institutes. An English reading passage test was used to measure students’ fluency in terms of their pausing patterns in prepared mode of speech. As learners started to read the passage, their speeches were recorded. The collected data were analyzed by Praat software. The statistical analyses revealed a significant difference between monolingual and bilingual learners in the frequency, duration, and placement of the pauses they had produced while they were reading the English passage. The results showed that bilingual learners outperformed monolingual participants, suggesting the superiority of bilinguals in their pausing patterns. The implications are discussed.
Deep Sequencing of the Rat MCAO Cortexes Reveals Crucial circRNAs Involved in Early Stroke Events and Their Regulatory Networks
Authors: Wang Chengtan , Yang Yuying , Xu Mengsi , Mao Fuxiu , Yang Peng , Yuan Shan , Gao Rui , Gan Shangquan
Published: November 2021

Circular RNAs (circRNAs) are highly enriched in the central nervous system and significantly involved in a range of brain-related physiological and pathological processes. Ischemic stroke is a complex disorder caused by multiple factors; however, whether brain-derived circRNAs participate in the complex regulatory networks involved in stroke pathogenesis remains unknown. Here, we successfully constructed a cerebral ischemia-injury model of middle cerebral artery occlusion (MCAO) in male Sprague-Dawley rats. Preliminary qualitative and quantitative analyses of poststroke cortical circRNAs were performed through deep sequencing, and RT-PCR and qRT-PCR were used for validation. Of the 24,858 circRNAs expressed in the rat cerebral cortex, 294 circRNAs were differentially expressed in the ipsilateral cerebral cortex between the MCAO and sham rat groups. Cluster, GO, and KEGG analyses showed enrichments of these circRNAs and their host genes in numerous biological processes and pathways closely related to stroke. We selected 106 of the 294 circRNAs and constructed a circRNA-miRNA-mRNA interaction network comprising 577 sponge miRNAs and 696 target mRNAs. In total, 15 key potential circRNAs were predicted to be involved in the posttranscriptional regulation of a series of downstream target genes, which are widely implicated in poststroke processes, such as oxidative stress, apoptosis, inflammatory response, and nerve regeneration, through the competing endogenous RNA mechanism. Thus, circRNAs appear to be involved in multilevel actions that regulate the vast network of multiple mechanisms and events that occur after a stroke. These results provide novel insights into the complex pathophysiological mechanisms of stroke.
C3aR Signaling Inhibits NK-cell Infiltration into the Tumor Microenvironment in Mouse Models
Authors: Nandagopal Saravanan , Li Caiyun G. , Xu Yu , Sodji Quaovi H. , Graves Edward E. , Giaccia Amato J.
Published: November 2021

Many solid tumors have low levels of cytotoxic CD56dim natural killer (NK) cells, suggesting that CD56dim NK-cell exclusion from the tumor microenvironment (TME) contributes to the decreased response rate of immunotherapy. Complement component 3a (C3a) is known for its tumor-promoting and immunosuppressive roles in solid tumors. Previous reports have implicated the involvement of the C3a receptor (C3aR) in immune cell trafficking into the TME. C3aR is predominantly expressed on the surface of activated cytotoxic NK cells, but a specific role for C3aR in NK-cell biology has not been investigated. Because solid tumors generate elevated C3a and have decreased NK-cell infiltration, we hypothesized that C3aR might play a role in cytotoxic NK-cell recruitment into the TME. Our results indicate that blocking C3aR signaling in NK cells increased NK-cell infiltration into the TME in mouse models and led to tumor regression. Because the critical lymphocyte trafficking integrin LFA-1 orchestrates the migration of activated NK cells, we wanted to gain insight into the interaction between C3aR signaling and LFA-1. Our results demonstrated that direct interaction between C3aR and LFA-1, which led to a high-affinity LFA-1 conformation, decreased NK-cell infiltration into the TME. We propose that approaches to enhance cytotoxic NK-cell infiltration into the TME, through either disrupting C3a and C3aR interaction or inhibiting the formation of high-affinity LFA-1, represent a new strategy to improve the efficiency of immunotherapy for cancer treatment.