bluuebunny/crossref_metadata_2025 huggingface dataset:
Automated English Speech Recognition Using Dimensionality Reduction with Deep Learning Approach
Authors: Yu Jing , Ye Nianhua , Du Xueqin , Han Lu
Published: March 2022

Speech recognition technology is a multidisciplinary field, comprising signal processing, pattern recognition, acoustics, artificial intelligence, etc. Presently, speech recognition plays a vital role in human-computer interface in information technology. Due to the advancements of deep learning (DL) models, speech recognition system has received significant attention among researchers in several areas of speech recognition like mobile communication, voice recognition, and personal digital assistance. This paper presents an automated English speech recognition using dimensionality reduction and deep learning (AESR-DRDL) approach. The proposed AESR-DRDL technique involves a series of operations, namely, feature extraction, preprocessing, dimensionality reduction, and speech recognition. During feature extraction process, a hybridization of high-dimension rich feature vectors is derived from the speech as well as glottal-waveform signals by the use of MFCC, PLPC, and MVDR techniques. Besides, the high dimensionality of features can be reduced by the design of quasioppositional poor and rich optimization algorithm (QOPROA). Moreover, the Bidirectional Long Short-Term Memory (BiLSTM) technique is employed for speech recognition, and the optimal hyperparameter tuning of the Bidirectional Long Short-Term Memory technique can be chosen using Adagrad optimizer. For the dimensionality reduction technique, the quasioppositional poor and rich optimization algorithm (QOPROA) is applied. The performance validation of the AESR-DRDL technique is carried out against benchmark datasets, and the results reported the better performance of the AESR-DRDL technique compared to recent approaches. The AESR-DRDL technique has shown to be superior in terms of recovery time, with an average of 0.50 days. The AESR-DRDL method's overall performance has been validated using benchmark datasets, and the results show that it outperforms more current technique. Because of this, the AESR-DRDL approach can be used to recognize English speech.
Perception and Recognition of Upper Limb Movement Trajectory of Aerobics Based on Multi-Intelligent Sensors
Authors: Li Qingyao
Published: March 2022

Aerobics is an indispensable part of school teaching. Aerobics can exercise the human body’s flexibility, muscle extension, and cardiopulmonary function. However, there are many details in the aerobics movements that need attention, so this article mainly studies the perception and recognition of the upper limb movement trajectory of aerobics. This article is mainly based on multi-intelligent sensors to perform motion capture and recognition of upper limb movements in aerobics. Therefore, in order to design a multismart sensor-based aerobics upper limb movement perception recognition system, this paper proposes to combine the VM-i three-axis magnetic sensor and MEMS smart sensor to capture the upper limb movement trajectory. Then, the aerobics upper limb movement trajectory and posture mathematical description method to obtain the model of the action perception recognition system are written. In order to verify the system, this paper also designed the actual effect of attitude calculation and A-RRM algorithm verification experiment. Finally, it is optimized with the data obtained from the experiment, and the accuracy and efficiency comparison experiment with the traditional motion perception recognition system is carried out. Experimental results show that the motion recognition accuracy of the aerobics upper limb movement trajectory recognition system based on multi-smart sensors is improved by 13%-23% compared with the traditional motion recognition system. The recognition efficiency of the action perception recognition system based on multismart sensors is 9%-15% higher than that of the traditional action recognition system.
Demyelinating Neurological Adverse Events following the Use of Anti-TNF-α Agents: A Double-Edged Sword
Authors: Gharib Miral H. , AlKahlout Mohamed Awni , Garcia Canibano Beatriz , Theophiel Deleu Dirk , Malallah AlEssa Hani , AlEmadi Samar
Published: March 2022

Background. Tumor necrosis factor antagonists (anti-TNF-α) are an established therapeutic option for several autoimmune and inflammatory bowel diseases. Despite their clinical effectiveness, neurological adverse events have been reported, and literature data suggest a potential role of anti-TNF-α in the induction of demyelination. Case Presentation. In this series, we present three cases of demyelination after the use of anti-TNF-α agents. The first case involved a 21-year-old man with HLA-B27 negative peripheral spondylarthritis who had been taking adalimumab for 2 years. He developed headache, urinary incontinence, and bilateral lower extremity numbness that progressed to the middle of the trunk for 2 days. Magnetic resonance imaging (MRI) showed multiple hyperintense enhancement lesions in the left paramedian anterior pons consistent with multiple sclerosis (MS). The second case included a 17-year-old woman who was on 2 years of adalimumab treatment for juvenile idiopathic arthritis and chronic anterior uveitis and developed new-onset dizziness and tremors. The clinical examination showed signs of cerebellar dysfunction. MRI findings were consistent with multiple sclerosis. The third case was a 34-year-old male who was on 5 years of infliximab treatment for ankylosing spondylitis when he developed left hand numbness and weakness. Cerebrospinal fluid (CSF) analysis and MRI findings were consistent with demyelination. Discontinuation of tumor necrosis factor antagonists (anti-TNF-α) resulted in resolution of the symptoms with no recurrence in the first case, but there was evidence of recurrence in the other 2 cases, where one was managed with rituximab and the second one improved with pulse steroid therapy. Conclusion. Despite the small number of patients, our series adds to the growing body of evidence supporting a causal link between anti-TNF-α agents and demyelination. Thus, we can conclude that on suspicion of any neurological side effects, early discontinuation of the TNF-α blockers and requesting urgent MRI scan to confirm the diagnosis is of utmost importance.
The Creative Route of University Ideological and Political Teaching on the Essential of Embedded Sensor Network
Authors: Gao Shuang , Li Shibao , Zhang Qiangying
Published: March 2022

Contemporary society has opened the door to the Internet era due to the advancement of knowledge and skills. The utilization of Internet technology has brought unprecedented challenges to the teaching of academic and politics systems in college. This research is on the basis of the effect of embedded sensor networks on the innovation of intellectual and mechanical teaching paths in university. This article is aimed at analyzing the application of embedded sensor technology in image processing and video processing to provide a basis for the development of teaching paths in college. The article searches related literature to investigate the current status and progress. This article mainly selects 200 students from a certain university to participate in the experimental investigation under the mode of new web teaching. This article combines the embedded system, audio network node function, sensing network system, etc., to improve the teaching tools and methods on the basis of the previous one. Finally, this article conducts the evaluation and statistical analysis of students before and after the embedded sensor network application teaching path from the phrases of course content, education mode, education function, etc. The experimental results show that the content of education is more scientific and coordinated, and the students’ evaluations have changed from 4.4-6.3 to 6.8-8.1. After the utility of embedded sensing net, the influence played a role to a large altitude. Exploring the multiple paths not only is conducive to more effective and targeted ideological education of students but also makes difference in guiding practical work at the theoretical level.
Effect of Different Polymerized Xylooligosaccharides on the Metabolic Pathway in Bifidobacterium adolescentis
Authors: Yao Di , Wu Mengna , Wang Xiaoyu , Xu Lei , Zheng Xiqun
Published: March 2022

Metabolic pathway analysis of Bifidobacterium adolescent (B. adolescentis) grown on either xylobiose and xylotriose (X2/X3) or xylopentaose (X5) and identifying key regulatory-related genes and metabolites from RNA-seq and UHPLC system was performed. Compared with X5, X2/X3 highly promoted the growth of B. adolescentis. Also, the transcriptome analysis showed that a total of 268 differentially expressed genes (DEGs) of B. adolescentis cultured with X2/X3 and X5 were screened, including 163 upregulated and 105 downregulated genes (X2/X3 vs. X5), which mainly were ABC transporters. Furthermore, the qRT-PCR results of 16 DGEs validated the accuracy of the RNA-seq data. Meanwhile, metabolomics analysis showed that 192 differential metabolites noted on MS2 included 127 upregulated and 65 downregulated metabolites; mainly, metabolites were amino acids and organic acids. The abundance difference of specific genes and metabolites highlighted regulatory mechanisms involved in utilizing different polymerized xylooligosaccharides by B. adolescentis.
Grade IV Sacral Sore Treated with an Ointment Rich in PUFAs, Ceramides, and Antimicrobial Peptides
Authors: Cassini Marta , Saretzky Irina
Published: March 2022

This report presents the case of a 57-year-old male patient with a history of hypertension, obesity, dyslipidemia, and coronary disease that after a prolonged postcoronary surgery hospitalization developed a sacral butterfly-shaped sore, with asymmetric involvement of the base of both buttocks, grade III on the left and grade IV on the right sides. The lesion was very painful and had a negative impact on the patient’s sleep and mood. Following the initial surgical debridement and treatment with collagenase ointment, the wound showed delayed healing, an increase in necrotic tissue, and purulent discharge, requiring a second surgical debridement that revealed a deeper involvement of the wound. After a month with poor therapeutic response, it was decided to change the treatment to the application of gauzes embedded in an ointment rich in polyunsaturated fatty acids (PUFAs), ceramides, and antimicrobial peptides, Curefini® ointment. After 30 days of treatment, a 50% reduction of the initial wound diameter was obtained with a positive impact on the patient’s quality of life, together with a reduction of incidental and spontaneous local pain resulting in better night rest and a return of appetite and strength. During the treatment course, the patient did not suffer any local or systemic infection in connection with the wound. After one month, the patient could discontinue the use of opioid analgesics. A 95% closure of the lesion was achieved in 45 days. This case highlights the therapeutic efficacy of the treatment of cavitated wounds with a product based on natural ingredients that helps reduce pain and promotes granulation and reepithelialization.
Structure and Menthone Encapsulation of Corn Starch Modified by Octenyl Succinic Anhydride and Enzymatic Treatment
Authors: Ji Xuan , Du Jing , Gu Jiaying , Yang Jie , Cheng Li , Li Zhaofeng , Li Caiming , Hong Yan
Published: March 2022

In order to improve the ability of starch to absorb menthone, corn starch was modified by enzymatic treatment (amyloglucosidase and α-amylase) combined with octenyl succinic anhydride (OSA) esterification. The oil absorption rate of starch modified by enzymatic treatment followed by OSA (P-OSA) reached 101.33%, whereas that of samples with reverse action sequences (OSA-P) was only 59.67%. The degree of substitution of OSA-P was also generally lower than that of P-OSA. At high OSA addition, OSA-P had a smaller specific surface area with fewer pores because octenyl succinic (OS) groups impeded the enzymatic treatment. Compared with OSA-P, the lamellar structure of P-OSA is sparser and less ordered. Owing to its pores, P-OSA was beneficial for the reaction to occur inside the granules, which was observed by Raman spectroscopy and laser confocal microscopy. At high OSA addition, the loading of P-OSA to menthone could reach 64.34 mg/g.
Numerical Method to Modify the Fractional-Order Diffusion Equation
Authors: Chen Yunkun
Published: March 2022

Time or space or time-space fractional-order diffusion equations (FODEs) are widely used to describe anomalous diffusion processes in many physical and biological systems. In recent years, many authors have proposed different numerical methods to solve the modified fractional-order diffusion equations, and some achievements have been obtained. However, to our knowledge of the literature, up to date, all the proposed numerical methods to modify FODE have achieved at most a second-order time accuracy. In this study, we focus mainly on the numerical methods based on numerical integration in order to modify the fractional-order diffusion equation:

1
+

1
/

12

δ
x
2

p
j
k

−

1
+

1
/

12

δ
x
2

p
j

k
−
1

=

μ

α

∑

l
=
0

k

λ
α

l

δ
x
2

p
j

k
−
l

+
 

μ

β

∑

l
=
0

k

λ
β

l

δ
x
2

p
j

k
−
l

+

τ
/
2

1
+

1
/

12

δ
x
2

f
j

k
−
1

+

f
j
k

,

k
=
1,2
,
…
,
K
;
j
=
1,2
,
…
,
j
−
1
,

p
j
0

=

ω

j

,
j
=
0,1
,
…
,
J

,

p
0
k

=
φ

t

k

,

p
j
k

=
ψ

t

k

,
k
=
0,1
,
…
,
K
,

f
j
l

=
f

x

j

,

t

l

,

ω

j

=
ω

x

j

. Accordingly, numerical methods can be built to modify FODE with second-order time accuracy and fourth-order spatial accuracy in

∂
p

x
,
t

/

∂
t

=

∂

1
−
α

/

∂

t

1
−
α

+
B

∂

1
−
β

/

∂

t

1
−
β

∂

2

p

x
,
t

/

∂

x

2

+
f

x
,
t

,
0
<
t
≤
1,0
<
x
<
1
,
p

x
,
0

=
0,0
≤
x
≤
1

.

p

0
,
t

=

t

2

,
p

1
,
t

=
e

t

2

,
0
≤
t
≤
1

. Our suggested method can improve the time precision with a certain value.
A Robust Approach for Speaker Identification Using Dialect Information
Authors: Shah Shahid Munir , Moinuddin Muhammad , Khan Rizwan Ahmed
Published: March 2022

The present research is an effort to enhance the performance of voice processing systems, in our case the speaker identification system (SIS) by addressing the variability caused by the dialectical variations of a language. We present an effective solution to reduce dialect-related variability from voice processing systems. The proposed method minimizes the system’s complexity by reducing search space during the testing process of speaker identification. The speaker is searched from the set of speakers of the identified dialect instead of all the speakers present in system training. The study is conducted on the Pashto language, and the voice data samples are collected from native Pashto speakers of specific regions of Pakistan and Afghanistan where Pashto is spoken with different dialectal variations. The task of speaker identification is achieved with the help of a novel hierarchical framework that works in two steps. In the first step, the speaker’s dialect is identified. For automated dialect identification, the spectral and prosodic features have been used in conjunction with Gaussian mixture model (GMM). In the second step, the speaker is identified using a multilayer perceptron (MLP)-based speaker identification system, which gets aggregated input from the first step, i.e., dialect identification along with prosodic and spectral features. The robustness of the proposed SIS is compared with traditional state-of-the-art methods in the literature. The results show that the proposed framework is better in terms of average speaker recognition accuracy (84.5% identification accuracy) and consumes 39% less time for the identification of speaker.
Approximate Solutions, Thermal Properties, and Superstatistics Solutions to Schrödinger Equation
Authors: Okon Ituen , Onate Clement , Omugbe Ekwevugbe , Okorie Uduakobong , Antia Akaninyene , Onyeaju Michael , Wen-Li Chen , Araujo Judith
Published: March 2022

In this work, we apply the parametric Nikiforov-Uvarov method to obtain eigensolutions and total normalized wave function of Schrödinger equation expressed in terms of Jacobi polynomial using Coulomb plus Screened Exponential Hyperbolic Potential (CPSEHP), where we obtained the probability density plots for the proposed potential for various orbital angular quantum number, as well as some special cases (Hellmann and Yukawa potential). The proposed potential is best suitable for smaller values of the screening parameter

α

. The resulting energy eigenvalue is presented in a close form and extended to study thermal properties and superstatistics expressed in terms of partition function

Z

and other thermodynamic properties such as vibrational mean energy

U

, vibrational specific heat capacity

C

, vibrational entropy

S

, and vibrational free energy

F

. Using the resulting energy equation and with the help of Matlab software, the numerical bound state solutions were obtained for various values of the screening parameter (

α

) as well as different expectation values via Hellmann-Feynman Theorem (HFT). The trend of the partition function and other thermodynamic properties obtained for both thermal properties and superstatistics were in excellent agreement with the existing literatures. Due to the analytical mathematical complexities, the superstatistics and thermal properties were evaluated using Mathematica 10.0 version software. The proposed potential model reduces to Hellmann potential, Yukawa potential, Screened Hyperbolic potential, and Coulomb potential as special cases.
Power Grid Low Carbon Collaborative Planning Method Using Improved Cat Swarm Optimization Algorithm in Edge Cloud Computing Environment
Authors: Li Xiang , Guo Chong , Li Chengjun , Xu Tianyuan , Wu Songyu
Published: March 2022

The current power grid planning mostly realizes the calculation and analysis based on the factors of operation reliability or operation economy, but low-carbon green operation has become the main melody of power system development. Aiming to support the green and reliable operation of the power grid, this paper proposes a power grid low-carbon collaborative planning method based on improved cat swarm optimization algorithm. First, the carbon emission characteristics of the whole cycle of power grid construction are analyzed on the edge side, and a power grid planning model including environmental, economic, and reliability is constructed; on the cloud side, the cat swarm optimization algorithm is improved based on quantum mechanics and chaotic algorithm to achieve efficient solution to the power grid low-carbon planning model, which can support the stable and sustainable operation. Finally, the simulation experiment is realized based on IEEE 39 bus system. In this experiment, the construction cost and carbon emission of the proposed collaborative planning method are 23 million yuan and 2.28 t/MWh, respectively, which can reduce carbon emission while optimizing the construction cost and maintaining the low-carbon and stable operation.
Decision Tree-Based Body Constitution Diagnosis System for Traditional Chinese Medicine
Authors: Yang Cheng-Chan , Yen Shi-Jim , Chiu Xian-Dong , Wu Kuo-Chu , Ye Shih-Cheng , Su San-Hua , Huang Hsiao-Yi
Published: March 2022

This study aimed to establish a method for fast and accurate determination of body constitution types from the body constitution questionnaire (BCQ) by employing a decision tree model. The model was trained for 4 classes, namely, Yin-Xu, Yang-Xu, Phlegm and Blood Stasis, and Normal, and it achieved 67% accuracy for the testing dataset. The model also reduced the required number of BCQ questions from 44 to 3–6, depending on the responses. Lastly, we developed the Traditional Chinese Medicine (TCM) body constitution online diagnosis system using our model to collect data digitally and use it more practically and efficiently. This system can assist doctors to improve the diagnosis and treatment in TCM practice.
Nutrient Detection Sensors in Seawater Based on ISI Web of Science Database
Authors: Cao Lina , Xiang Hongyong , Xu Jingwen , Gao Yufu , Lin Chenlu , Li Kun , Li Zhiwei , Guo Nana , David P. , He Chunguang , Yang Haijun
Published: March 2022

Marine ecosystem is increasingly deteriorating. In order to assess anthropogenic influence and instigate appropriate remedial actions, it is still of great significance to develop the technology of sensors applied for nutrient detection (e.g., nitrate, phosphate, and silicate) in seawater. This brief review shows an important direction for the development of nutrient detection sensors in seawater and also the limitations and challenges based on data from the ISI Web of Science database. Being different from previous review papers, in this short critical review paper (1) we unified the unit of limit of detection (LOD) for making the comparison within different researches possible; (2) only the literatures focusing on the technological development of sensors in seawater were used; and (3) not only the detection methods but also the detected analytes and publication years were discussed to supply more valuable information for the development of nutrient sensors applied in seawater. In total, 109 literatures were collected with regard to technological development. The quantity of literatures has increased most during 2011-2020. For analytes, literatures related to nitrate, phosphate, ammonium, and phosphate will continue to increase with more accurate data. For detection methods, spectrophotometry, colorimetry, fluorimetry, and electrochemistry are the most widely used sensors. LODs show thousands of orders. In general, there are lower LOD to nitrite and ammonium and fluorimetry method. Now, for analytes,

nitrate
 

1.0983

>
silicate
 

0.5495

>
phosphate
 

0.4823

>
ammonium
 

0.1324

>
nitrite
 

0.0568

. For detection methods,

microfluidics
 

1.7617

>
electrochemistry
 

1.2607

>
colorimetry
 

0.4462

>
spectrophotometry
 

0.2941

>
fluorimetry
 

0.0558

. This result indicated that the development level of detection methods is closer for nitrate, nitrite, phosphate, and silicate. For ammonium, spectrophotometry has significantly lower LOD than electrochemistry (

p
<
0.05

), and fluorimetry also has significantly lower LOD than electrochemistry (

p
<
0.05

). Our results imply that sensors with accurate LOD should be developed in the future. In addition, more detection methods should be considered by future sensors.
Association between the Platelet-Derived Growth Factor/Platelet-Derived Growth Factor Receptor System and Risk of Rheumatoid Arthritis: A Systematic Review and Meta-Analysis
Authors: Li Feiyan , Wu Shaoping , Xie Hualing , Wang Wanling , Wang Jing , Jia Chanyi , Xie Chao , Zhang Xia
Published: March 2022

This research examines the association between the platelet-derived growth factor/platelet-derived growth factor receptor (PDGF/PDGFR) system and rheumatoid arthritis (RA) susceptibility through a comprehensive search of the PubMed database to study the expression of the PDGF/PDGFR system in RA. Review Manager software version 5.3 was used for statistical analysis. Six eligible studies published in the English language were included, including 108 rheumatoid arthritis cases and 85 controls with the corresponding 126 and 97 tests, respectively, relating the expression of the PDGF/PDGFR system to the risk of RA. The overall results indicated a significant association between the PDGF/PDGFR system expression and RA (

OR
=
5.25

, 95% CI: 3.00-9.18,

p
<
00001

), RA patients in Asian countries (

OR
=
4.13

, 95%

CI
=
2.04

-8.39,

p
<
0.0001

) and in Western countries (

OR
=
9.18

, 95%

CI
=
2.04

-8.39,

p
=
0.03

), and only PDGF expression in RA patients (

OR
=
5.28

, 95%

CI
=
2.73

-10.21,

p
<
0.00001

). Thus, only the PDGFR expression was insignificantly associated with RA susceptibility (

OR
=
9.25

, 95%

CI
=
0.63

-136.30,

p
=
0.11

). Hence, the PDGF/PDGFR system most likely contributes to susceptibility to RA.
Evaluation of Running Intensity and Fatigue Degree Based on Human Physiological Information
Authors: Li Wang
Published: March 2022

Muscle fatigue represents a complex phenomenon including various causes, mechanisms, and forms of manifestation. It develops as a result of a chain of metabolic, structural, and energetic changes in muscles due to insufficient oxygen and nutritive substances supply through blood circulation, as well as a result of intensive physical exercise. In this study, a new method for frequency band energy of wavelet packet decomposition is proposed which combines normalized energy into wavelet packet decomposition and uses the frequency band energy quotient as physiological parameters for detecting muscles fatigue before and after human exercise. The operator’s subjective fatigue test and surface electromyography (EMG) objective test were combined to design the experiment, and a computer program was used to control the operation interface and record the operation results. Three major operating fatigue variables, namely, the most comfortable initial position of the operator, the difference in operating direction, and the difference in operating distance, were evaluated. The surface EMG consumption of the operator was measured synchronously with the surface EMG meter. After variable control and error analysis, test results are analyzed, and the range of the operator’s most comfortable initial position is summarized. The differences of operator fatigue degree in eight operating directions and operating fatigue degree in different operating distance variables are obtained. In the whole test process, the operator’s subjective test results and objective test results remain consistent, which has proved the rationality of the experimental design and experimental results.
Computer Network Intrusion Anomaly Detection with Recurrent Neural Network
Authors: Fu Zeyuan
Published: March 2022

Network intrusion anomaly detection technique has been widely employed in computer network environments as a highly effective security prevention method. As network technology and network applications have advanced at a rapid pace, so too has network data traffic, resulting in an increase in virus and attack kinds. In the face of large-scale traffic and characteristic information, traditional intrusion detection will have problems such as low detection accuracy, high false negatives, and reliance on dimensionality reduction algorithms. Therefore, it is particularly important to establish a fast and efficient network intrusion anomaly detection method to deal with the current complex network environment. This work designs a computer network intrusion detection model with a recurrent neural network in order to explore a new intrusion detection method. The main purpose of this article include the following: (1) design a network security emergency response system architecture with the recurrent neural network model. This system consists of a management center module, a knowledge database module, a data acquisition module, a risk detection tool module, a risk analysis and processing module, a data protection module, and a remote connection auxiliary module. The modules cooperate with each other to complete system functions. (2) Aiming at the risk analysis and processing module, a network intrusion detection model combining bidirectional long short-term memory (BiLSTM) and deep neural network (DNN) is designed. In view of the lack of consideration of the before-and-after relevance of intrusion data features and the multifeature problem in existing models, the use of BiLSTM to extract the relevance between features and the use of DNN to extract deeper features are proposed. Aiming at the problem that the model lacks consideration of the importance of features, it is proposed to embed an attention mechanism into the network to increase consideration for the importance of features. (3) Massive experiments have verified the reliability and effectiveness of the method proposed in this work.
Rare Presentation of Angiolipoma Affecting an Intact Achilles Tendon
Authors: Mammoto Takeo , Takahashi Nobuyuki , Takayashiki Norio
Published: March 2022

Musculoskeletal lipomatous lesions are common in soft tissues. However, these are rarely associated with tendon sheaths or tendon compartments. Moreover, angiolipoma of the Achilles tendon is yet to be described. Here, we report an angiolipoma of an intact Achilles tendon, which has not been described previously. A 54-year-old woman presented with a two-year history of a palpable mass in the posterior aspect of the left ankle. The mass caused an intermittent localized pain while walking and a catching phenomenon induced by the plantar dorsiflexion movement of the ankle joint. Magnetic resonance imaging revealed a well-circumscribed, oval lesion on the lateral aspect of the Achilles tendon. The location and shape of the lesion had changed over time, suggesting that the lesion was moving in and out around the Achilles tendon. At the surgery, the tumor was confirmed under the crural fascia. Histopathological examination revealed that the tumor comprised mature adipocytes covered peripherally with a fibrovascular capsule. Based on these features, the tumor was diagnosed as an angiolipoma. Angiolipomas are typically treated surgically by simple excision, and lipomatous lesions of the tendon sheath are not different. From this case report, angiolipomas are rare but should be considered in the differential diagnosis and treatment of Achilles tendon tumors.
Root and Root Canal Anatomy of Primary Mandibular Central Incisor, Lateral Incisor, and Canine in Indian Children: A Cone Beam Computed Tomography Study
Authors: Katge Farhin , Dixit Uma B.
Published: March 2022

Background. A thorough knowledge of root and root canal morphology in primary dentition is essential for success of endodontic therapy. This information also finds importance in anthropological research in reconstructing human population history. Lack of studies of root and root canal morphology in mandibular anterior teeth prompted us to the present study. Methods. A total of 109 extracted primary mandibular incisors and canines were collected, out of which 90 teeth were selected for this study and divided into 3 groups: CI, mandibular central incisor; LI, mandibular lateral incisor; C, mandibular canine. All the sample teeth were scanned using cone beam computed tomography (CBCT). Number of roots, number of root canals, length of root, mesiodistal (MD), and buccolingual (BL) width of canal, shape of canal, and presence of accessory canals were assessed. Collected data were statistically compared using one-way ANOVA and chi-square tests. Results. All teeth studied displayed single root with single root canal conforming to type I Vertucci’s classification. Root length of CI was significantly shorter than both LI and C, with no significant difference between LI and C. Straight root canals were more common in CI and LI, whereas curved canals were more common in C. S-shaped canals were seen in a few CI and C. BL canal width was more than MD width in all teeth, C showing significantly larger dimensions than both CI and LI. Conclusion. This study presents root and root canal characteristics of primary mandibular central incisor, lateral incisor, and canine in children from Indian ethnicity.
Optimization of Indirect Fracturing Process Parameters Based on Mechanical Properties of Fractured and Low-Permeability Coal
Authors: Yuan Wenfeng , Zheng Xigui , Shahani Niaz Muhammad
Published: March 2022

The coal-bed methane (CBM) resources in soft and low-permeability coals are assumed to be as much as 15 × 1012 m3 in China. Indirect fracturing technology can be an effective method to successfully extract methane within soft coals. The key to the success of this technique is to optimize the parameters, such as water injection flow rate and fracture initiation location, so that the hydraulic fracturing parameters enable the fractures to pass through the interface between coal and rock and propagate sufficiently into the coal. This paper focuses on solving the above problems by focusing on discontinuities and plastic characteristics of soft coals. Voronoi polyhedron was used to simulate the discontinuities of coal, and the constitutive relations of ductile fracture-seepage and elastoplastic damage-seepage are, respectively, given to the discontinuities and coal matrix. A numerical model was established based on the above theory to simulate the effect of stress difference Δσ, coal-rock interface friction coefficient fc,r, water injection flow rate i

w

, and distance between the well and the interface Dop on indirect fracturing fractures. The results show that the HFs area in the coal is positively correlated with Δσ, fc,r, and i

w

, and it first increases and then decreases with the decrease of Dop. The above results were applied in the Zhaozhuang mine of Qinshui Basin by optimizing Dop = 1 m and iw = 8 m3/min, so that CBM production has been greatly increased. The results can provide theoretical support for the efficient development of CBM in fractured and low-permeability coal seam areas.
Diagnostic Performance of Atherosclerotic Carotid Plaque Neovascularization with Contrast-Enhanced Ultrasound: A Meta-Analysis
Authors: Dong Shanshan , Hou Jianzhong , Zhang Caiyun , Lu Guilin , Qin Wenjuan , Huang Lei , Zhou Guangqin
Published: March 2022

Objectives. To evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) for atherosclerotic carotid plaque neovascularization. Methods. The electronic databases like PubMed, Embase, OVID, and Web of Science were used to search for the relevant studies, which are involved in the evaluation of the diagnostic parameters of QUS for atherosclerotic carotid plaque neovascularization. Review Manager 5.4 and Stata 14.0 were used to estimate the pooled diagnostic value of CEUS. Forest plots, sensitivity analysis, and Deeks’ funnel plots were performed on the included studies. Results. Ten studies eventually met the final inclusion criteria. For diagnostic performance, CUES showed that the pooled values of sensitivity, specificity, positive likelihood odds ratios, negative likelihood odds ratios, and diagnostic odds ratios were 0.83 (95% CI 0.78-0.86), 0.77 (95% CI 0.68-0.84), 3.61 (95% CI 2.59-5.03), 0.23 (95% CI 0.18-0.28), and 16.02 (95% CI 10.02-25.60), respectively. The estimate of the area under curve (AUC) was 0.85 (95% CI 0.82-0.88). Conclusion. Our research supported that CEUS had high sensitivity and specificity in the diagnosis of atherosclerotic carotid plaque neovascularization. More high-quality prospective multicenter studies focusing on the accuracy of CEUS for carotid atherosclerotic plaque should be performed to verify our conclusions.
Clustering by Hybrid K-Means-Based Rider Sunflower Optimization Algorithm for Medical Data
Authors: Jaya Mabel Rani A. , Pravin A.
Published: March 2022

Currently, medical data clustering is a very active and effective part of the research area to take proper decisions at the medical field from medical data sets. But medical data clustering is a very challenging issue due to limitless receiving data, vast size, and high frequencies. To achieve this and improve the performance with fast and effective clustering, this paper proposes a hybrid optimization technique, namely, the K-means-based rider sunflower optimization (RSFO) algorithm for medical data. In this research, initially, the data preprocessing phase has been carried out to clean the current input medical data, and then in the second phase, important features are chosen with the help of the Tversky index with holoentropy. Finally, medical data clustering has been carried out by using hybrid K-means-based rider sunflower optimization (RSFO) algorithm. RSFO is designed to produce optimum clustering centroid, which is the combination of two optimization techniques, such as rider optimization algorithm (ROA) and sunflower optimization (SFO). This hybrid algorithm can get the advantages of both K-means and RSFO technique and avoid premature convergence of K-means algorithm and high computation cost of optimization technique. K-Means clustering algorithm is used to cluster the medical data by using an optimum centroid. The efficiency of the proposed K-means-based rider sunflower optimization algorithm is examined with a heart disease data set and analyzed based on three different performance metrics.
Cellulosic Ethanol Production Using a Dual Functional Novel Yeast
Authors: Liu Z. Lewis , Dien Bruce S.
Published: March 2022

Reducing the cost of cellulosic ethanol production, especially for cellulose hydrolytic enzymes, is vital to growing a sustainable and efficient cellulosic ethanol industry and bio-based economy. Using an ethanologenic yeast able to produce hydrolytic enzymes, such as Clavispora NRRL Y-50464, is one solution. NRRL Y-50464 is fast-growing and robust, and tolerates inhibitory compounds 2-furaldehyde (furfural) and 5-hydroxymethyl-2-furaldehyde (HMF) associated with lignocellulose-to-fuel conversion. It produces three forms of β-glucosidase isozymes, BGL1, BGL2, and BGL3, and ferment cellobiose as the sole carbon source. These β-glucosidases exhibited desirable enzyme kinetic parameters and high levels of enzyme-specific activity toward cellobiose and many oligosaccharide substrates. They tolerate the product inhibition of glucose and ethanol, and are stable to temperature and pH conditions. These characteristics are desirable for more efficient cellulosic ethanol production by simultaneous saccharification and fermentation. NRRL Y-50464 provided the highest cellulosic ethanol titers and conversion rates at lower cellulase loadings, using either pure cellulose or agricultural residues, as so far reported in the literature. This review summarizes NRRL Y-50464 performance on cellulosic ethanol production from refined cellulose, rice straw, and corn stover processed in various ways, in the presence or absence of furfural and HMF. This dual functional yeast has potential to serve as a prototype for the development of next-generation biocatalysts. Perspectives on continued strain development and process engineering improvements for more efficient cellulosic ethanol production from lignocellulosic materials are also discussed.
A Deployment Strategy of Nodes in WSN Based on “X” Partition
Authors: Liu Jinxue , Sun Gengxin
Published: March 2022

In order to reduce the energy consumption and the cost of wireless sensor networks (WSNs) deployed in linear areas and prolong the life of the network, a deployment strategy of nodes in WSNs based on “X” partition was proposed in this paper. The monitored area was partitioned based on “X” shape, and the sensor nodes were deployed, so as to make the whole area be covered and the number of nodes deployed be reduced. At the same time, the monitoring units are divided and compressed to balance and save energy of the network and prolong life of the network. Through experiment verification, compared with traditional partition deployment strategy, the deployment cost of network can be reduced effectively by the proposed strategy. In terms of the life of the network, the proposed strategy is longer than the diamond partition strategy more than 50%.
Research on HMM-Based Efficient Stock Price Prediction
Authors: Su Zhi , Yi Bo
Published: March 2022

Stock market is one of the most important parts of the investment market. Compared with other industries, the stock market not only has a higher rate of return on investment but also has a higher risk, and stock price prediction has always been a close concern of investors. Therefore, the research on stock price prediction methods and how to reduce the error of stock price prediction has become a hot topic for many scholars at home and abroad. In recent years, the development of computer technology such as machine learning and econometric method makes the stock price prediction more reliable. Due to the hidden Markov nature of stock price, this paper proposes a stock price prediction method based on hidden Markov model (HMM). To be specific, since the data of stock price have continuity in time series, it is necessary to extend the discrete HMM to the continuous HMM, and then put forward the up and down trend prediction model based on the continuous HMM. The first-order continuous HMM is extended to the second-order continuous HMM, and the stock price is predicted by combining the prediction method of fluctuation range. As a result, the proposed second-order continuous HMM-based stock price prediction model is simulated on Hang Seng Index (HSI), one of the earliest stock market indexes in Hong Kong. The evaluation results on six months HSI show that the predicted value of the proposed model is very close to the actual value and outperforms three benchmarks in terms of RMSE, MAE, and R2.
Mapping Pupil’s Learning Progression Using Hand Manipulatives and Touch Screen Applications: Implications to Post-COVID-19 New Normal
Authors: Gonzales Gamaliel
Published: March 2022

The study investigates the shifts in pupils’ learning progression levels while they learn fractions using hand manipulatives and touch screen applications. A total of 10 children paired with preservice teachers participated in a 12-week learning design. This was performed during the disruptions of the academic year due to the COVID-19 pandemic. The study uses the convergent mixed methods design to document qualitative and quantitative data. The method enables the researcher to compare, relate, and merge results. The author develops a microscoring tool to help the preservice teachers analyze observed learning progressions. The theoretical underpinning was based on a constructivist environment while learning mathematics. Results documented evidence of shifts and recursions in children’s learning progressions along with the Pirie–Kieren model while interacting with hand manipulatives and touch screen applications. The quantitative and thematic analyses revealed three different shifts in pupils’ learning. The study suggests that an open-ended number of tasks at varying levels of difficulty led the pupils to refine their understanding of the concept image resulting in progression shifts in learning. With the interconnectedness of the findings, it is proposed that design features in mathematics apps paired with manipulative kits be investigated on a large population. Implications for delivery modes and policy directions in post-COVID-19 new normal are presented.
Prediagnostic Levels of Copper and Zinc and Breast Cancer Risk in the ORDET Cohort
Authors: Pala Valeria , Agnoli Claudia , Cavalleri Adalberto , Rinaldi Sabina , Orlandi Rosaria , Segrado Francesco , Venturelli Elisabetta , Vinceti Marco , Krogh Vittorio , Sieri Sabina
Published: March 2022

Background:

Case–control studies show that copper (Cu) is high and zinc (Zn) low in blood and urine of women with breast cancer compared with controls.

Methods:

To assess whether prediagnostic Cu and Zn are associated with breast cancer risk, OR of breast cancer according to Cu, Zn, and Cu/Zn ratio in plasma and urine was estimated in a nested case–control study within the ORDET cohort, using conditional logistic regression adjusted for multiple variables: First 496 breast cancer cases and matched controls, diagnosed ≥2 years after recruitment (to eliminate reverse causation) were analyzed. Then all eligible cases/controls were analyzed with stratification into years from recruitment to diagnosis.

Results:

For women diagnosed ≥2 years, compared with lowest tertiles, breast cancer risk was higher in the highest tertile of plasma Cu/Zn ratio (OR, 1.75; 95% CI, 1.21–2.54) and the highest tertile of both plasma and urine Cu/Zn ratio (OR, 2.37; 95% CI, 1.32–4.25). Risk did not vary with ER/PR/HER2 status. For women diagnosed <2 years, high Cu/Zn ratio was strongly associated with breast cancer risk.

Conclusions:

Our prospective findings suggest that increased Cu/Zn ratio in plasma and urine may be both an early marker of, and a risk factor for, breast cancer development. Further studies are justified to confirm or otherwise our results and to investigate mechanisms.

Impact:

Our finding that prediagnostic Cu/Zn ratio is a strong risk factor for breast cancer development deserves further investigation and, if confirmed, might open the way to interventions to reduce breast cancer risk in women with disrupted Cu/Zn homeostasis.
Catchment Area: An Opportunity for Collective Impact, Strategic Collaboration, and Complementary Focus
Authors: Vadaparampil Susan T. , Tiro Jasmin A.
Published: March 2022

Since NCI's 2016 guidance to define a catchment area and describe aims for community outreach and engagement to address community needs and priorities, cancer center leaders and researchers have begun to see how this focused attention brings impact. DelNero, Buller, and colleagues highlight coverage of the United States based on catchment areas of 63 NCI-Designated Cancer Centers. The data visualization naturally lends itself to consideration of future opportunities for strategic collaboration and complementary focus among the 63 designated cancer centers included in their analysis.

See related article by DelNero et al., p. 965
Phase I Study of Taminadenant (PBF509/NIR178), an Adenosine 2A Receptor Antagonist, with or without Spartalizumab (PDR001), in Patients with Advanced Non–Small Cell Lung Cancer
Authors: Chiappori Alberto A. , Creelan Ben , Tanvetyanon Tawee , Gray Jhanelle E. , Haura Eric B. , Thapa Ram , Barlow Margaret L. , Chen Zhihua , Chen Dung Tsa , Beg Amer A. , Boyle Theresa A. , Castro Julio , Morgan Liza , Morris Erick , Aregay Mehreteab , Hurtado Felipe K. , Manenti Luigi , Antonia Scott
Published: March 2022

Purpose:

The adenosine 2A receptor (A2AR) mediates the immunosuppressive effects of adenosine in the tumor microenvironment and is highly expressed in non–small cell lung cancer (NSCLC). Taminadenant (PBF509/NIR178) is an A2AR antagonist able to reactivate the antitumor immune response.

Patients and Methods:

In this phase I/Ib, dose-escalation/expansion study, patients with advanced/metastatic NSCLC and ≥1 prior therapy received taminadenant (80–640 mg, orally, twice a day) with or without spartalizumab (anti–programmed cell death-1, 400 mg, i.v., every 4 weeks). Primary endpoints were safety, tolerability, and feasibility of the combination.

Results:

During dose escalation, 25 patients each received taminadenant alone or with spartalizumab; 19 (76.0%) and 9 (36.0%) had received prior immunotherapy, respectively. Dose-limiting toxicities (all Grade 3) with taminadenant alone were alanine/aspartate aminotransferase increase and nausea [n = 1 (4.0%) each; 640 mg], and in the combination group were pneumonitis [n = 2 (8.0%); 160 and 240 mg] and fatigue and alanine/aspartate aminotransferase increase [n = 1 (4.0%) each; 320 mg]; pneumonitis cases responded to steroids rapidly and successfully. Complete and partial responses were observed in one patient each in the single-agent and combination groups; both were immunotherapy naïve. In the single-agent and combination groups, 7 and 14 patients experienced stable disease; 7 and 6 patients were immunotherapy pretreated, respectively.

Conclusions:

Taminadenant, with and without spartalizumab, was well tolerated in patients with advanced NSCLC. The maximum tolerated dose of taminadenant alone was 480 mg twice a day, and 240 mg twice a day plus spartalizumab. Efficacy was neither a primary or secondary endpoint; however, some clinical benefit was noted regardless of prior immunotherapy or programmed cell death ligand-1 status.