bluuebunny/crossref_metadata_2025 huggingface dataset:
Automated Dual-Channel Speech Enhancement Using Adaptive Coherence Function with Optimised Discrete Wavelet Transform
Authors: Tank Vanita Raj , Mahajan Shrinivas Padmakar
Published: May 2022

Voice quality enhancement is a significant method for any speech communication model. Speech Enhancement (SE) and noise reduction approaches can significantly improve the perceptual voice quality of a hands-free communication system and increase the recognition rates of automatic speech recognition systems. Speech communications in real-world cases require high-performance enhancement techniques for addressing the distortions, which can corrupt the intelligibility and quality of the speech signal. Recent portable devices generally incorporate several microphones that can be easily used for improving signal quality. This paper plans to present a novel dual-channel SE model using the coherence function and heuristic concepts. The adaptive coherence function relates to the dual-microphone SE approach suitable for smartphones with primary and reference microphones. With this improved signal, the enhancement is performed by optimising denoising using Discrete Wavelet Transform (DWT) by Adaptive wind speed-based Deer Hunting Optimization Algorithm (AWS-DHOA). The considered objective function depends on the quality measure called Perceptual Evaluation of Speech Quality (PESQ) score. From the results, the RMSE of the proposed model using AWS-DHOA is 39.8%, 45.5%, 53.8% and 45.5% minimised than GWO-CFD, WOA-CFD, CSA-CFD, and RDA-CFD, respectively, on considering the babble noise. Finally, the comparative analysis confirmed that the proposed method improves speech quality and intelligibility by comparing diverse algorithms when different noise types corrupt the speech.
Emerging Dynamics in Malaysia-Japan Relations under the Second Mahathir Administration
Authors: LAI YEW MENG , MOORTHY RAVICHANDRAN
Published: May 2022

Japan and Malaysia established relations in 1957, the year Malaysia obtained independence from the British. Malaysia has largely benefited through many Japanese assistance programs, and in return, the country has remained one of Japan’s closest friends in Southeast Asia. During his first premiership, Mahathir introduced the Look East Policy (LEP) as a major foreign policy re-direction, moving away from the Western approach adopted by his predecessors. Nevertheless, bilateral relations plateaued during the reign of the two successive prime ministers Abdullah Badawi and Najib Razak primarily as a result of the changing regional geopolitical landscape. Malaysia moved closer towards an emerging China. However, the May 2018 general election paved the way for Mahathir to resume control of the country for the second time after a lapse of 15 years. Within less than a year, Japan started to bounce back in Malaysia’s political and strategic sensors. Japan is set to play a greater role in the Malaysian economic landscape, especially with its assistance of low-interest samurai bonds to aid the debt-stricken new Malaysian government. For Japan, this rekindling of old friendship could not have been more timely and may translate into greater support to Japan’s initiatives for regional peace and for a free and open Indo-Pacific region. This paper examines the evolving trends in bilateral relations between Japan and Malaysia in the second Mahathir administration. More specifically, it explicates the external and domestic sources which have affected and recalibrated Malaysia’s Japan policy in the context of a shifting regional strategic milieu as well as an evolving post-election domestic political landscape. This paper contends that the emerging dynamics and trajectories in Malaysia’s relations with Japan under the nascent “Mahathirism 2.0” period have been primarily shaped by the country’s ruling elite’s perceptions of her external conditions in the context of East Asia’s changing power dynamics, tempered by their domestic political considerations and leadership traits/idiosyncrasies. It further argues that despite the newly-minted Pakatan Harapan (PH) government’s visible foreign policy adjustments indicating a possible shift of emphasis from China towards Japan, such recalibrations are yet to alter the fundamentals of Malaysia’s Northeast Asia policy generally and its Japan policy specifically, an area in which the effects of structural conditions (proximity, power asymmetry, rivalries and uncertainties) continue to be informed by the Malaysian ruling elite’s domestic political considerations as they strive as much to optimize the country’s external interests as to consolidate their domestic legitimation.
Dynamic Motion Matching: Design and Implementation of a Context-Aware Animation System for Games
Authors: Häfliger Adan , Kurabayashi Shuichi
Published: May 2022

Despite modern game systems adopting motion matching to retrieve an appropriate short motion clip from a database in real-time, existing methods struggle to support complex gaming scenes due to their inability to adapt live the motion retrieval based on the context. This paper presents the design and implementation of a context-aware character animation system, synthesizing realistic animations suitable for complex game scenes from a large-scale motion database. This system, called dynamic motion matching (DyMM), enables geometry and objects aware motion synthesis by introducing a two-phase context computation: an offline subspace decomposition of motion clips for creating a set of retrieval sub-spaces tailored to specific contexts and a subspace ensemble matching to compare relevant sub-features to determine the most appropriate motion clip. We also show the system architecture and implementation details applicable to a production-grade game engine. We verified the effectiveness of our method with industry-level motion data captured by professional game artists for multiple configurations and character controllers. The results of this study show that, by finding motion clips that comply well with the scene context, one can leverage large motion capture datasets to create practical systems that generate believable and controllable animations for games.
New models to aid the discovery of critical raw material deposits for the Green Stone Age
Authors: Bidgood Anna , Hitzman Murray
Published: May 2022

Critical raw materials (CRMs) will be crucial for delivery of the technologies society requires to meet its decarbonization goals and successfully address the current climate crisis. Although there are a number of well-established ore deposit models, few have been developed for CRMs. History demonstrates that ore deposit models are commonly developed to explain new discoveries. However, it is also possible to develop new ore deposit models based solely on basic geochemical and geological principles. We review the development of several ore deposit models, suggest some deposits for which models have not yet been developed and utilize the specific example of hydrothermal nickel deposits in the Central African Copperbelt to illustrate how new ore deposit models for CRM deposits may be formulated. The current impetus to discover new resources of what have been up to the present elemental curiosities should spur significant research, including work to determine the geochemical behaviour of CRMs across a range of physio-chemical conditions. There is no reason to believe that economically significant concentrations of any of the newly critical elements do not exist in nature. Imagination should make the future of CRM discovery in the Green Stone age bright.
Spontaneous Regression of Plasmablastic Lymphoma in an Immunocompetent Patient: Case Report and Review of the Literature
Authors: Lee Kee Tat , Misron Nurul Akmar , Abdul Aziz Norasmidar , Wong Chin Hau , Liew Hong Keng
Published: May 2022

Plasmablastic lymphoma (PBL) is a rare and highly aggressive type of lymphoma, which is commonly associated with human immunodeficiency virus (HIV) infection. Spontaneous regression of aggressive lymphomas is rare as they typically require administration of chemotherapy and radiotherapy for treatment. Here, we describe a case of a spontaneous regression of PBL after nasal biopsy and computed tomography (CT) guided biopsy of paravertebral mass in an immunocompetent patient. We postulate that the patient’s immune system may be activated as a result of the stress and physical trauma brought on by nasal and paravertebral mass biopsy. Our case highlights the rare phenomenon of spontaneous regression of lymphoma which needs to be further studied on to establish its underlying pathophysiology.
Protective Effects of Oxyberberine in 5-Fluorouracil-Induced Intestinal Mucositis in the Mice Model
Authors: Huang Ronglei , Ai Gaoxiang , Zhong Linjiang , Mai Liting , Chen Jian-Nan , Liu Yuhong , Li Yucui , Huang Xiaoqi , Su Ziren , Zhan Janis Ya-Xian
Published: May 2022

Berberine (BBR), a major active constituent of Rhizoma coptidis, was reported to exert beneficial effects on intestinal mucositis (IM) induced by 5-fluorouracil (5-FU). However, the bioavailability of BBR is extremely low, and its metabolites were perceived to contribute to its prominent pharmacological activities. Oxyberberine (OBB) is a gut metabolite of BBR, which has been reported to have a superior anti-inflammatory effect in experimental colitis. However, its anti-inflammatory effects against 5-FU-induced IM mice have not yet been investigated. Hence, the purpose of this study was to reveal the protective effects of OBB on IM induced by 5-FU and investigate its potential underlying mechanism. The IM mice model was induced by receiving 5-FU (60 mg/kg, i.p.) for five days. Meanwhile, BBR (50 mg/kg) and OBB (12.5, 25, and 50 mg/kg) were given prior to 30 min intraperitoneal injection of 5-FU for seven days. Results indicated that OBB ameliorated body weight loss, anorexia, diarrhea, and histopathological damage in 5-FU-induced IM mice. After OBB administration, the amounts of MDA, SOD, and GSH altered by IM were remarkably restored. OBB was also observed to dramatically decrease the levels of TNF-α, IL-8, IL-6, COX-2, and iNOS and promote the release of IL-10. Besides, OBB distinctly upregulated the mRNA expressions of PCNA, ZO-1, occludin, and mucin-1, which could improve intestinal homeostasis in IM mice. OBB also blocked the activation of the upstream TLR4/MyD88 signaling pathway, and then it inhibited the phosphorylation of the NF-κB and MAPK pathways. Importantly, compared with BBR, OBB displayed a superior therapeutic effect to BBR in alleviating 5-FU-induced IM mice. These results indicated that OBB has considerable potential to become a novel candidate drug against IM.
Efficient Auxiliary Information–Based Control Charting Schemes for the Process Dispersion with Application of Glass Manufacturing Industry
Authors: Aslam Muhammad , Anwar Syed Masroor , Khan Majid , Abiodun Nafiu Lukman , Rasheed Zahid
Published: May 2022

The hybrid exponentially weighted moving average (HEWMA) control chart is an enhanced version of the EWMA control chart that monitors the process parameters effectively. Similarly, the auxiliary information-based (AIB) EWMA control charts are very efficient for monitoring process parameters. The purpose of this paper is to propose two new control charts for the improved monitoring of process dispersion referred to as

HEWMA

AIB

1

and

HEWMA

AIB

2

control charts. A simulation study is carried out to assess the performance of the proposed

HEWMA

AIB

1

and

HEWMA

AIB

2

control charts. Average run length, extra quadratic loss, relative average run length, and performance comparison index are used to compare the performance of the proposed control charts against the existing counterparts. The comparisons reveal the superiority of the proposed control charts against other competing control charts, particularly for small to moderate shifts in the process dispersion. Finally, a real-life data set from the glass industry is used to demonstrate the practical implementation of the proposed control charts.
[Retracted] Therapeutical Significance of Serpina3n Subsequent Cerebral Ischemia via Cytotoxic Granzyme B Inactivation
Authors: Aslam Mehwish Saba , Aslam Mobeena Saba , Aslam Komal Saba , Iqbal Asia , Yuan Liudi
Published: May 2022

Ischemic stroke is a devastating CNS insult with few clinical cures. Poor understanding of underlying mechanistic network is the primary limitation to develop novel curative therapies. Extracellular accumulation of granzyme B subsequent ischemia promotes neurodegeneration. Inhibition of granzyme B can be one of the potent strategies to mitigate neuronal damage. In present study, we investigated the effect of murine Serpina3n and human (homolog) SERPINA3 against cerebral ischemia through granzyme B inactivation. Recombinant Serpina3n/SERPINA3 were expressed by transfected 293 T cells, and eluted proteins were examined for postischemic influence both in vitro and in vivo. During in vitro test, Serpina3n was found effective enough to inhibit granzyme B, while SERPINA3 was ineffectual to counter cytotoxic protease. Treatment of hypoxic culture with recombinant Serpina3n/SERPINA3 significantly increased cell viability in dosage‐dependent manner, recorded maximum at the highest concentration (4 mM). Infarct volume analysis confirmed that 50 mg/kg dosage of exogenous Serpina3n was adequate to reduce disease severity, while SERPINA3 lacked behind in analeptic effect. Immunohistochemical test, western blot analysis, and protease activity assay’s results illustrated successful diffusion of applied protein to the ischemic lesion and reactivity with the target protease. Taken together, our findings demonstrate therapeutic potential of Serpina3n by interfering granzyme B‐mediated neuronal death subsequent cerebral ischemia.
An Enhanced Fermatean Fuzzy Composition Relation Based on a Maximum‐Average Approach and Its Application in Diagnostic Analysis
Authors: Ejegwa P. A. , Muhiuddin G. , Algehyne E. A. , Agbetayo J. M. , Al-Kadi D.
Published: May 2022

The idea of composition relations on Fermatean fuzzy sets based on the maximum‐extreme values approach has been investigated and applied in decision making problems. However, from the perspective of the measure of central tendency, this approach is not reliable because of the information loss occasioned by the use of extreme values. Based on this limitation, we introduce an enhanced Fermatean fuzzy composition relation with a better performance rating based on the maximum‐average approach. An easy‐to‐follow algorithm based on this approach is presented with numerical computations. An application of Fermatean fuzzy composition relations is discussed in diagnostic analysis where diseases and patients are mirrored as Fermatean fuzzy pairs characterized with some related symptoms. To ascertain the veracity of the novel Fermatean fuzzy composition relation, a comparative analysis is presented to showcase the edge of this novel Fermatean fuzzy composition relation over the existing Fermatean fuzzy composition relation.
Efficacy of Dexmedetomidine Anesthesia plus Dorsal Penile Nerve Block in Pediatric Circumcision
Authors: Ji Ling , Yao Fan , Wang Yanwu , Li Caishun , Lin Yulong
Published: May 2022

Objective. To assess the efficacy of dexmedetomidine anesthesia plus dorsal penile nerve block in pediatric circumcision. Methods. In this retrospective study, 80 children receiving circumcision in our hospital from February 2020 to February 2021 were recruited and assigned via different anesthesia methods at a ratio of 1 : 1 to receive dorsal penile nerve block plus dexmedetomidine anesthesia (combined anesthesia group) or only sevoflurane for total inhalational anesthesia (total anesthesia group). Traditional Chinese medicine (TCM) care was introduced to both groups of patients. Outcome measures included vital signs, operative indices, anesthesia effect, adverse reactions, parent satisfaction, and nursing satisfaction. Results. There were no significant differences in the heart rate, oxygen saturation, and mean arterial pressure between the two groups of children before anesthesia, after anesthesia, and during the awakening period (

P
>
0.05

). Patients receiving combined anesthesia showed a shorter time lapse before the disappearance of eyelash reflex, longer time lapse before postoperative analgesic use, faster awakening, and shorter operation time and hospital stay versus those receiving total inhalational anesthesia alone (

P
>
0.05

). The combined anesthesia resulted in a lower Induction Compliance Checklist (ICC) score, McGill score, and Richmond Agitation-Sedation Scale (RASS) score and a higher Ramsay score versus total anesthesia (

P
>
0.05

). Patients receiving combined anesthesia showed a significantly lower incidence of adverse events (5.00% (2/40)) versus total inhalational anesthesia (62.50% (25/40)) (X2 = 29.574,

P
>
0.05

). The combined anesthesia group had a higher parent satisfaction (92.50% (37/40)) versus the total anesthesia group (75.00% (30/40)) (X2 = 4.501,

P
>
0.05

). A total of 80 questionnaires were distributed, with a 100% return rate and a 100% validity rate, and all 80 questionnaires scored 90 points or above. The families of children in both groups were satisfied with the quality of TCM care. Conclusion. The efficacy of dorsal penile nerve block plus dexmedetomidine anesthesia in pediatric circumcision is better than total inhalational anesthesia with sevoflurane.
Damage Modelling of Compressed Earth Blocks Stabilised with Cement
Authors: Goutsaya Janvier , Ntamack Guy Edgar , d’Ouazzane Saâd Charif
Published: May 2022

This work aims at studying the mechanical behaviour of compressed Earth blocks (CEBs) and compressed stabilised Earth blocks (CSEBs) with 4% and 8% in weight cement stabilisation. A numerical simulation method based on the nonlinear behaviour law coupling isotropic elasticity damage is proposed to predict the mechanical behaviour of brittle and quasibrittle materials at simple compressive loading conditions. This model relies on the free energy of the material to generate the damage‐dependent stress expression in order to bring it closer to the experimental findings. Tests on the geotechnical properties of the three soil samples (MAI, BAM, and GAD) collected in Ngaoundere city, the chief town of the Adamawa region of Cameroon, were carried out. Furthermore, simple compression tests were carried out on samples of dimensions 4 × 4 × 4 cm3 after 28 days of drying. By comparing the experimental and numerical results used, we could notice that the average compressive stresses of CEBs are approximately 4.13 MPa and 4.16 MPa, and the average deformation limits are 0.0068 and 0.0069; concerning the average Young’s moduli, they are about 842.30 MPa and 789.88 MPa, and for 4% cement, we obtained an average compressive strain of about 4.23 MPa and 4.28 MPa, average deformation limit 0.0072 and 0.0075, and Young’s moduli we obtained about 719.16 MPa and 714.06 MPa. At 8% cement dosage, we obtained average compressive stresses of about 5.01 MPa and 5.20 MPa, average deformation limit of 0.0073 and 0.0074, and Young’s moduli give us 866.43 MPa and 872.56 MPa.
Long Short‐Term Memory Recurrent Neural Network for Predicting the Return of Rate Underframe the Fama‐French 5 Factor
Authors: Khoa Bui Thanh , Huynh Tran Trong
Published: May 2022

The multifactor approach helps determine the linear connection between a diversified portfolio’s return and risk; however, the efficacy of the model models is still limited in the experiment. Algorithms in machine learning have recently grown in popularity to compensate for some of the shortcomings of theoretical models. This study applied a machine learning technique to compare the performance of the Fama‐French 5‐factor model (FF5). Two approaches are employed in the Fama‐French model: Long Short Term Memory Recurrent Neural Network (LSTM‐RNN) and Maximum Likelihood Estimation (MLE). From January 1, 2010, through March 3, 2022, the stock market in Ho Chi Minh City was experimentally researched. The rolling window approach is used in combination with the Root Mean Square Error (RMSE), and the results of the FF5 model with the LSTM‐RNN algorithm are more efficient in prediction error than the MLE methodology. This contribution encourages investors and hedge fund managers to use the LSTM‐RNN algorithm to boost forecasting efficiency.
Biomechanical Effect of Valgus Knee Braces on the Treatment of Medial Gonarthrosis: A Systematic Review
Authors: Yan Yuzhou , Liu Geng , Zhang Li , Gong Ruitao , Fu Pengge , Han Bing , Li Hui
Published: May 2022

Background. Valgus braces are prescribed as a common conservative treatment option for patients with medial gonarthrosis to improve their quality of life. Many studies had reviewed the effects of the valgus braces on patients with medial gonarthrosis, while they mainly focused on the knee adduction moment (KAM), with less attention paid to other parameters such as spatiotemporal and morphological parameters. Objectives. The purpose of this study was to review the effects of valgus braces on the spatiotemporal, kinematic/kinetic, morphological, and muscle parameters. Methods. Based on the selected keywords, a survey of literatures was performed in Web of Science, PubMed, Scopus, and Google Scholar using the PRISMA methods, and the search period was established from January 2000 to March 2022. Results. Thirty-four articles were included. According to the conclusion of these articles, the valgus brace can be used to relieve the symptoms of patients with medial gonarthrosis by decreasing the varus angle, decreasing the KAM, and redistributing the knee compartment loads. However, the effects of valgus braces on other biomechanical parameters (e.g., walking speed, cadence, joint angle, and joint space) had not reached a consensus. Conclusions. The valgus knee brace can effectively relieve the symptoms of medial gonarthrosis through multiple mechanisms, while there is still some confusion about the effectiveness of the valgus brace on the other biomechanical parameters.
Spherical Fuzzy Decision-Making Approach Integrating Delphi and TOPSIS for Package Tour Provider Selection
Authors: Nguyen Phi-Hung
Published: May 2022

The spherical fuzzy sets were recently developed among various fuzzy sets to handle the hesitancy representation issue in multiple criteria decision-making (MCDM) problems, where experts provide information about attributes in the form of spherical fuzzy numbers using linguistic variables. The main purpose of this study is to develop a novel approach integrating Delphi Technique for Order of Preference by Similarity to Ideal Solution based on spherical fuzzy sets (SF-Delphi and SF-TOPSIS). First, the SF-Delphi technique is suggested to derive a valid set of critical criteria based on qualitative information and linguistic preferences. Second, the SF-TOPSIS approach is utilized to rank alternatives based on different spherical fuzzy aggregating operators. Hence, to validate the effectiveness of the proposed methodology, an empirical case study of package tour provider selection is given. Seventeen critical criteria related to four main dimensions (price, service quality, information and technology, and location) were shortlisted and validated from literature and expert opinions. Ten potential package tour providers from Vietnam were ranked in this study. A comparative analysis was conducted to check the proposed methodology’s robustness and validity. The results indicated that the novel SF-Delphi technique may become very helpful for dealing with critical factors, and SF-TOPSIS could be applied to decision problems in uncertain data environments. Furthermore, this research’s findings imply that tour operators should emphasize the most critical attributes to increase the appeal and competitiveness of their package tour products.
Traffic Sign Detection Based on SSD Combined with Receptive Field Module and Path Aggregation Network
Authors: Wu Jianjun , Liao Shaowen
Published: May 2022

The traditional traffic sign detection algorithm can not deal with the application scenarios such as intelligent transportation system or advanced assisted driving environment, and it is difficult to meet the application requirements in detection accuracy and efficiency. Focusing on the above problems, this paper proposes a traffic sign detection algorithm based on Single Shot Multibox Detector (SSD) combined with Receptive Field Module (RFM) and Path Aggregation Network (PAN). The proposed algorithm is abbreviated to SSD-RP. The SSD-RP uses the RFM to improve the receptive field and semantics of the predicted feature maps, thus improving the detection performance of small traffic signs. At the same time, the path aggregation network is introduced to integrate multiscale features, which makes the abstract semantic information and rich detailed information shared among multiscale feature maps, enhances the discrimination ability of feature system, and improves the location and classification accuracy of traffic signs. Following that, the spatial pyramid pooling module is used to pool the shallow features and integrate them into the bottom-up information transmission path of the path aggregation network, thus continuing to supplement the fine-grained features for the feature system and further improve the detection performance. The experimental results on GTSDB and CCTSDB data sets show that SSD-RP has higher mean average precision (mAP) than traditional SSD algorithm and can better detect small traffic signs, which means that SSD-RP has higher detection precision. In addition, the experimental results also show that, compared with the common object detection algorithms such as Faster R-CNN, RetinaNet, and YOLOv3, the SSD-RP achieves a better balance between detection time and detection precision.
A Mobile Terminal-Based College English Teaching Evaluation Method
Authors: Lili Gao
Published: May 2022

At the moment, the existing teaching evaluation system cannot be used for wireless data input and reception, limiting the system's application scope and making it less practical. As a result, a new system for evaluating college English teaching is being developed using a mobile terminal. The English teaching quality model is constructed using the Internet of Things mobile platform, and the network teaching structure is analyzed using the model parameters to monitor and control the teaching progress. A classification and evaluation system will be established in conjunction with the campus network and intelligent sensor networking technology. The development environment and overall design of the mobile terminal are used to create an evaluation system for English teaching in an Internet of Things environment. Create the critical architecture based on the B/S model. In the section on system software design, we mine data from English teaching resources, evaluate students’ progress toward English proficiency, and use convolutional neural networks to evaluate the quality of English teaching. The teaching results are output according to the distribution of convolutional layers, allowing us to analyze the level of English instruction in colleges and universities. Comparative experiments demonstrate that this research system has a higher information query efficiency, a lower convergent error of 4 ms, and a higher evaluation accuracy for oral English, English writing, and English reading.
Build Strategies Based on Substrate Utilization for 3-Axis Hybrid Wire Arc Additive Manufacturing Process
Authors: Sarma Ritam , Kapil Sajan , Joshi Shrikrishna N.
Published: May 2022

The hybrid wire arc additive manufacturing (H-WAAM) process is one of the prominent methods for realizing large near-net-shaped metallic objects. In this process, a CAD model of the component is sliced into a set of 2D contours followed by the generation of toolpaths. An arc welding torch then follows these toolpaths for adding material over a substrate to realize the near-net shape of the object. These near-net-shaped objects are then followed by a machining operation to convert them into a fully functional part. It is always anticipated that the near-net shape of an object is produced quickly and upholds a high geometrical accuracy. Conventionally, the deposition rate is increased to reduce the build time but with a compromisation in the geometrical accuracy and material integrity. Therefore, in this work, the authors have investigated three substrate utilization methods, viz., (i) reusable substrate, (ii) embedded substrate, and (iii) integrated substrate to achieve the same goal. The build strategies for these three substrate utilization methods are illustrated through several examples. Also, a case study was performed for fabricating an impeller-like structure through a 3-axis H-WAAM setup. It has been observed that the embedded substrate method exhibits superior geometrical accuracy and takes less time to build the part as compared to other methods. A maximum of 64.34% of the material and 89.17% of build time is saved by adopting proposed build strategies compared with the traditional subtractive process.
Differentiation of Isolated Small Bowel Crohn’s Disease from Other Small Bowel Ulcerative Diseases: Clinical Features and Double-Balloon Enteroscopy Characteristics
Authors: Niu Meng , Chen Zheng-Hao , Li Meng , Zhang Xing , Chen Chun-Xiao
Published: May 2022

Background. The diagnosis of isolated small bowel Crohn’s disease (ISBCD) has always been challenging. Aims. This study is aimed at comparing the clinical features and double-balloon enteroscopy (DBE) characteristics of ISBCD with those of other small bowel ulcerative diseases (OSBUD). Methods. Patients with coexisting colonic and/or ileal valve lesions (

n
=
45

) or whose final diagnosis was not determined (

n
=
29

) were excluded. One hundred thirty-nine patients with ISBCD and 62 patients with OSBUD found by DBE were retrospectively analyzed. Results. The age of ISBCD onset was lower than that of OSBUD (OR 0.957, 95% CI 0.938-0.977,

p
<
0.001

). Abdominal pain was more common in ISBCD (OR 4.986, 95% CI 2.539-9.792,

p
<
0.001

). Elevated fibrinogen levels (OR 1.431, 95% CI 1.022-2.003,

p
=
0.037

) and lower levels of D-dimer (OR 0.999, 95% CI 0.999-1.000,

p
=
0.017

) were also more supportive of the diagnosis of ISBCD. Nonsteroidal anti-inflammatory drugs (NSAIDs) used for more than two weeks decreased the probability of a diagnosis of ISBCD (OR 0.173, 95% CI 0.043-0.695,

p
=
0.013

). Abdominal computed tomography revealed a higher proportion of skip lesions in ISBCD than in OSBUD (OR 9.728, 95% CI 3.676-25.742,

p
<
0.001

). The ulcers of ISBCD were more distributed in the ileum (111 (79.9%) vs. 29 (46.8%),

p
<
0.001

), and their main morphology differed in different intestinal segments. Longitudinal ulcers (OR 14.293, 95% CI 4.920-41.518,

p
<
0.001

) and large ulcer (OR 0.128, 95% CI 0.044-0.374,

p
<
0.001

) contributed to the differentiation of ISBCD from OSBUD. We constructed a diagnostic model, ISBCD index (

AUROC
=
0.877

, 95% CI: 0.830-0.925), using multifactorial binary logistic regression to help distinguish between these two groups of diseases. Conclusion. Clinical features, laboratory tests, abdominal computed tomography, DBE characteristics, and pathology help to distinguish ISBCD from OSBUD.
Evaluation of the Emotion Model in Electronic Music Based on PSO-BP
Authors: Guo Ting
Published: May 2022

Electronic music can help people alleviate the pressure in life and work. It is a way to express people’s emotional needs. With the increase of the types and quantity of electronic music, the traditional electronic music classification and emotional analysis cannot meet people’s more and more detailed emotional needs. Therefore, this study proposes the emotion analysis of electronic music based on the PSO-BP neural network and data analysis, optimizes the BP neural network through the PSO algorithm, and extracts and analyzes the emotional characteristics of electronic music combined with data analysis. The experimental results show that compared with BP neural network, PSO-BP neural network has a faster convergence speed and better optimal individual fitness value and can provide more stable operating conditions for later training and testing. The electronic music emotion analysis model based on PSO-BP neural network can reduce the error rate of electronic music lyrics text emotion classification and identify and analyze electronic music emotion with high accuracy, which is closer to the actual results and meets the expected requirements.
Point-of-Care Based Electrochemical Immunoassay for Epstein-Barr Virus Detection
Authors: Yu Miao , Liu Ming , Li Yuan
Published: May 2022

This work describes a label-free electrochemical immunosensor for the sensing of Epstein-Barr virus (EBV) with high sensitivity. First, a monolayer of 1,6-hexanedithiol (HDT) was fabricated on the screen-printed electrode surface by the interaction between sulfur atoms and SPE. AuNPs can be modified on the electrode by the Au-S bond formed between the HDT-free group and Au atom in AuNPs. Protein A is then adsorbed onto AuNPs. Several parameters were optimized. The optimum concentration of protein A is 0.6 mg/mL. The optimum immobilization time for protein A is 90 min. The optimum concentration of antibody is 80 μg/mL. The optimum immobilization time for antibody is 90 min. Directional immobilization of EBV antibody is achieved by high affinity binding of protein A to the Fc segment of antibody. When antigen specifically binds to antibody, the formation of immune complexes blocks electron transfer of [Fe(CN)6]4-/3- and is reflected in the detection of cyclic voltammetry/electrochemical impedance spectroscopy. The detection range is 1 pg/mL–l00 ng/mL with a LOD of 0.1 pg/mL. In addition, the proposed sensor exhibited an excellent antiinterference property.
Modeling and Bayesian Analysis of Time between the Breakdown of Electric Feeders
Authors: Ateeq Kahkashan , Altaf Saima , Aslam Muhammad
Published: May 2022

The failure of electric feeders is a common problem in the summer season in Pakistan. In this article, one of the troubling aspects of the electric power system of Pakistan (Multan city) has been studied. The time lapses between the breakdown of electric feeders of the city have been modeled by suggesting an inverse Rayleigh-exponential distribution. The parameters of the distribution are estimated in both the frequentist and Bayesian paradigms. Since the Bayes estimators under informative priors are not attained in the closed form, this paper provides a comparative analysis of the Bayes estimators under Lindley and Tierney–Kadane approximation methods. The simulation study and the real-life data set assessed the validity of the model and the superiority of the Bayes estimators over the maximum likelihood estimators.
Spontaneous Loculated Pneumomediastinum in a COVID-19-Infected Patient
Authors: Jafari Sirous , Jahani Zahra , Alikhani Reihane , SeyedAlinaghi SeyedAhmad , Hasannezhad Malihe , Salahshour Faeze , Asadollahi-Amin Ali
Published: May 2022

While we are still learning about COVID-19 affecting people, older persons and persons with underlying diseases such as high blood pressure, heart disease, and diabetes mellitus (DM) appear to develop serious illness and more complications often than others. In this report, we presented a patient with spontaneous pneumomediastinum after COVID-19. The patient was a 61-year-old man with a history of DM, hypertension, and heart failure, who has been infected with COVID-19. The patient was diagnosed with COVID-19 based on RT-PCR analysis of nasopharyngeal samples, and chest X-ray showed patchy infiltration upper and lower lobes bilaterally. By day 4, imaging was repeated, performed due to exacerbation of pleuritic chest pain, decreased O2 saturation (80%), and coughing that revealed multiple ground-glass opacities bilaterally, and interlobular septal thickening with emphysema in most of the left upper lobe and a small part of right upper lobe which led to severe spontaneous left pneumomediastinum and parenchymal consolidation was also observed. The combination of a chest tube, antibiotics (vancomycin 1 gr/bid and meropenem 1 g/bid), and antiviral (hydroxychloroquine 200 mg/bid and atazanavir 300 mg/daily) was prescribed, and continued treatment with antiviral and appropriate care for pneumomediastinum was successful. Spontaneous pneumomediastinum in the context of COVID-19 should be considered as a prognostic factor in favor of worsening diseases.
Machine Learning- and Feature Selection-Enabled Framework for Accurate Crop Yield Prediction
Authors: Gupta Sandeep , Geetha Angelina , Sankaran K. Sakthidasan , Zamani Abu Sarwar , Ritonga Mahyudin , Raj Roop , Ray Samrat , Mohammed Hussien Sobahi
Published: May 2022

Agriculture is crucial for the existence of humankind. Agriculture provides a significant portion of the income for many people all around the world. Additionally, it provides a large number of work possibilities for the general public. Numerous farmers desire for a return to the old-fashioned techniques of farming, which provides little profit in today’s market. Long-term economic growth and prosperity are dependent on the success of agriculture and associated companies in the United States. Agribusiness crop yields may be increased by carefully selecting the right crops and putting in place supportive infrastructure. Weather, soil fertility, water availability, water quality, crop pricing, and other factors are taken into consideration while making agricultural predictions. Machine learning is critical in crop production prediction because it can anticipate crop output based on factors such as location, meteorological conditions, and season. It is advantageous for policymakers and farmers alike to be able to precisely estimate crop yields throughout the growing season since it allows them to anticipate market prices, plan import and export operations, and limit the social cost of crop losses. The use of this tool assists farmers in making informed decisions about which crops to grow on their land. In this study, a machine learning framework for agricultural yield prediction is presented. Crop information is collected in an experiment’s data set. Then, feature selection is performed using the Relief algorithm. Features are extracted using the linear discriminant analysis algorithm. Machine learning predictors, namely, particle swarm optimization-support vector machine (PSO-SVM), K-nearest neighbor, and random forest, are used for classification.
Network Interconnection Security Buffer Technology for Power Monitoring System
Authors: Wang Jifeng , Wu Jinyu , Tao Wenwei , Zhu Wen , Qiu Weijie
Published: May 2022

In recent years, the risk of malicious attacks on power monitoring systems has increased, and there have been many attacks on power systems in the world. Aiming at the network interconnection security problem of the core control system, the concept of “security buffer” is introduced, and a network security buffer method forpower monitoring system is proposed, which is composed of three parts: paradigm check, behavior analysis, and dynamic conversion and jointly realizes the multilevel security inspection of interconnection requests. Experimental verification results show that the proposed method has a protective effect on malicious attacks of power monitoring system.
A Multineuron-Based Routing Algorithm of Tile-Based 2-D Mesh
Authors: Faujdar Neetu , Akash Punhani  , Agarwal Ankush , Kumar Pradeep , Kumar Ajitesh
Published: May 2022

Tile-based architecture is broadly utilized in the structuring of the system-on-chip by different vendors. Nevertheless, the performance of the system-on-chip (SoC) is incredibly influenced by the performance of the network hidden on a chip named network-on-chip (NoC). Routing of network-on-chip network chips plays a crucial role in the overall performance of the NoC. In this paper, we have proposed a routing algorithm that utilizes the neural network to perform the routing. This routing algorithm updates the route dependent on the port execution of the switch. From the outcome, the execution of the directing has worked successfully and has the option to deal with the enormous burden viably. The result obtained shows that the performance metric for the uniform traffic is slightly better in comparison to XY routing at the higher loads of 80%. In the case of neighbor traffic, bit complement traffic, and tornado traffic, these values are higher on 80% of the load. The reason for better handling of the loads is due to the parallelization due to the pipeline created by the neural network routing decision.
Effect of Acupuncture on Diaphragm Function in Healthy Volunteers: A Pilot Clinical Study
Authors: Formenti Paolo , Galimberti Andrea , Pinciroli Riccardo , Umbrello Michele
Published: May 2022

Introduction. In western medicine, the diaphragm is the main inspiratory muscle. It is involved in the postural control of the trunk and contributes to balance performance. In traditional Chinese medicine (TCM), the diaphragm represents a gateway between the lower and upper parts of the body, and it regulates the descending and ascending functions of the whole organism. The aim of this study was to assess the effect of acupuncture on diaphragm function. Methods. A proof-of-concept, prospective, controlled, pilot trial in healthy volunteers. Respiratory rate, inspired volume, diaphragm excursion, and thickening were measured during tidal and maximal breathing at baseline and after sham or real acupuncture. Acupuncture was performed on Yanglingquan (GB34), Tai Chong (LV3), Danzhong (CV17), Geshu (BL17), and Geguan (BL46). Results. Ten participants were enrolled (6 males, weight 71 ± 12 kg, height 173 ± 9 cm, BMI 21 ± 1.3 kg/m2). During tidal breathing, tidal volume, diaphragm displacement, and end-expiratory diaphragm thickness did not change with sham or real acupuncture as compared to baseline; thickening ratio was 43.5 ± 16.6 vs. 31.3 ± 14.9 (sham) vs. 30.8 ± 15.3% (baseline),

p
=
0.1066

. During breaths at vital capacity, the acupuncture group, as compared to both baseline and sham acupuncture, had a trend toward a larger tidal volume (3840 ± 690 vs. 3110 ± 880 vs. 3230 ± 750 ml,

p
=
0.1247

) and showed a significantly higher thickening ratio (270.6 ± 136.4 vs. 172.4 ± 57.4 vs. 188.6 ± 41.7%,

p
=
0.0414

). Conclusions. Acupuncture significantly influenced diaphragm function in healthy volunteers, improving its inspiratory thickening fraction during breaths at vital capacity, as compared to no or sham acupuncture.
An Exponential Curve Model and Its Application in Forecasting Private Car Ownership of China
Authors: Zuo Kai , Zuo Hang , Zhang Xuege
Published: May 2022

To solve problems of modeling and prediction of nonstationary sequences caused by deterministic factors in the real world, a new type of exponential curve model with first‐order polynomial term is proposed in this paper based on the classical exponential curve model and the modified exponential curve model. According to the characteristics of the new model, the piecewise summation method is adopted to determine the analytical expressions of parameters. Moreover, the model is applied to the ownership of private cars in China. Comparing the calculated results with the classical exponential curve model and the modified exponential curve model, it can be seen that the new exponential curve model has higher accuracy in the analysis of the ownership of private cars in China.
Comparison of Laser Iridotomy and Lensectomy Outcomes for Acute Primary Angle Closure
Authors: Iijima Kei , Kamiya Kazutaka , Iida Yoshihiko , Shoji Nobuyuki
Published: May 2022

Purpose. To compare the clinical outcomes of the different treatments for acute primary angle closure (APAC). Methods. We retrospectively reviewed the clinical charts of 87 eyes of 87 patients undergoing treatment for APAC. We investigated the best spectacle-corrected visual acuity (BSCVA), intraocular pressure (IOP), corneal endothelial cell density (ECD), and secondary interventions after each treatment. Results. The pretreated IOP was 56.4 ± 9.0 mmHg. As the first treatment for APAC, all eyes underwent topical 2% pilocarpine and systemic mannitol administration. Subsequent laser iridotomy (LI) and lensectomy were necessary in 29 eyes (33%) and 35 eyes (40%), respectively. Bullous keratopathy developed in 1 eye (1%), and following glaucoma surgery was required in 7 eyes (8%). The BSCVA at the final follow-up was 0.16 ± 0.53 and 0.01 ± 0.20 logMAR (Mann–Whitney U test,

p
=
0.149

), the IOP was 12.8 ± 2.6, and 12.6 ± 2.9 mmHg (

p
=
0.860

), and the ECD was 2295.9 ± 658.2 and 2244.1 ± 622.0 cells/mm2 (

p
=
0.735

) in the LI and lensectomy groups, respectively. Conclusions. Approximately 26% of eyes with APAC were resolved after the initial medical treatment, and subsequent surgical treatments, such as LI and lensectomy, were required in 33% and 40% of eyes, respectively. We found no significant differences in the BSCVA, the IOP, or the ECD among LI and lensectomy treatment groups.
[Retracted] 3D Simulation Design and Application of Traditional Hanfu Based on Internet of Things
Authors: Lin Li , Gan Wen
Published: May 2022

Chinese traditional Hanfu is a kind of clothing that can reflect the changes of Chinese history, culture, and dynasties. With the improvement of people’s aesthetic ability and the pursuit of national culture, Hanfu has shown a state of revival. The study of Hanfu has become a research hotspot in today’s era. However, there is a big difference between the design of traditional Hanfu and the design of modern clothing. It not only needs to consider people aesthetics and preferences but it also needs to further consider the historical and cultural information represented by traditional Chinese Hanfu. This is a more critical and difficult point for Hanfu designers. If Hanfu cannot be well combined with history and culture, this will easily lead to a misinterpretation of Hanfu. In this study, the feasibility of the 3D simulation design of Hanfu was fully studied by combining the Internet of Things technology and the convolutional neural network method. The research results show that the Internet of Things technology can efficiently and accurately collect the characteristics of patterns, colors, shapes, and historical information of Hanfu. The reliability of IoT technology also improves the accuracy of CNN methods in predicting Hanfu eigenvalues. The largest prediction error is only 2.84%. CNN can also well capture the relationship between historical information features of Hanfu and dynasties, and all predicted feature values are within the 95% confidence interval.
Application of Computer-Aided Precious Metal Materials in Electrochemistry of Ceramic Jewelry Design
Authors: Li Jing
Published: May 2022

In order to solve the electrochemical application of precious metal materials in ceramic jewelry design, a computer-aided design method of precious metal materials in ceramic jewelry was proposed. First, the potential energy surface analyzed in this paper is composed of the sum of disomy and trisomy, with different proportions of disomy and trisomy. Therefore, in the fitting process, the above two relations can be used to measure the contribution of the two-body term and the three-body term, respectively; secondly, from the viewpoint of lattice dynamics, precious metals are of special significance, because they are simple fcc lattice and large and pure single crystals can be obtained. Therefore, their accurate phonon dispersion curves can be obtained experimentally; finally, the phonon dispersion curves along the highly symmetric vector direction are given, and the calculated results are in good agreement with the experimental data. This shows that the new analytical potential energy surface accurately reproduces the interactions inside these crystals. The new analytical potential energy surfaces of the three noble metals correctly reproduce the macroscopic properties of the system, including elastic modulus, cohesive energy, and phonon dispersion curve, as well as important surface features. For all three systems, the order of the surface energies of the unreconstituted surfaces is (110) > (100) > (111), which is also correct. At the same time, the new potential energy surface gives the correct relaxation behavior of the unreconstituted surface.