bluuebunny/crossref_metadata_2025 huggingface dataset:
An Improved TCN Considering Data Augmentation in Enabling Load Classification
Authors: Han Ding , Bai Hongkun , Wang Yuanyuan , Wang Shiqian , Zhang Jie , Liu Yang
Published: May 2022

In modern power system, along with the developments of the data collecting technologies, the intensive and high-dimensional load data collection can be achieved. Therefore, to deeply reveal the patterns and behaviors hidden in the load dataset using load classification is of great significance for improving the service quality and the user experience of the power system. However, inevitable issues, for example the data missing and class imbalance are frequently reported in the present load dataset, which deteriorates the performance of the classification algorithms. Also, due to the special features, for example the time series, periodicity, and fluctuation of the load data, the traditional data classification algorithms also encounter performance defects. Therefore, this paper presents a data augmentation based enhanced temporal convolutional network (TCN) algorithm in enabling load classification. In the data augmentation phase, first an LRTC-TSVD algorithm is presented to implement the missing data completion. Second, a WGAN based class balancing approach is further presented to solve the class imbalance issue. Then, in the enhanced TCN phase, a WeightNorm, exponential linear unit (ELU) activation function, residual connection, and bidirectional feature fusion techniques based improved TCN (ITCN) algorithm is presented to carry out the accurate load data classification. Combining the data augmentation and the enhanced TCN phases, the ITCN algorithm is finally conducted. Based on the benchmark load datasets, the performances of the presented ITCN are evaluated. The experimental results report that the presented data augmentations can improve the quality of the dataset, moreover the classification algorithm is able to achieve the satisfied classification accuracy.
THE NEXUS BETWEEN CASH CONVERSION CYCLE, WORKING CAPITAL FINANCE, AND FIRM PERFORMANCE: EVIDENCE FROM NOVEL MACHINE LEARNING APPROACHES
Authors: MAHMOOD FAISAL , SHAHZAD UMEAIR , NAZAKAT ALI , AHMED ZAHOOR , RJOUB HUSAM , WONG WING-KEUNG
Published: May 2022

This study examines the moderating role of the cash conversion cycle (CCC) while investigating the effects of working capital finance (WCF) on firm performance. Using more than 18000 observations from Chinese manufacturing firms, we computed several proxies for each variable of the study and merged these proxies via Principal Component Analysis (PCA) to create one master proxy for each variable. These master proxies contain all the essential information of individual proxies. Hence, they are more useful in producing reliable results than individual proxies. We also compared the predicting power of 15 econometric and machine learning estimators to select the best estimator. Based on the highest [Formula: see text] value, we used two machine learning estimators, K-Nearest Neighbors (KNN), and Artificial Neural Networks (ANN) for subsequent analysis. To strengthen the empirical analysis, we employed another machine learning technique, i.e., the Bagging method, which is an ensembling technique that uses multiple estimators simultaneously to improve the accuracy and generalization of results. We used the Bagging method with 50[Formula: see text]KNN estimators. The findings unfold that the sensitivity level of firm performance to short-term debts shifts when the CCC period of firms fluctuates. More precisely, the WCF–performance relationship in firms with extended CCC is more sensitive compared with this relationship in the full sample. On segregating the three elements of CCC, we observe that the WCF–performance relationship in firms carrying extended account receivable (AR) days or extended Inventory days is more sensitive than the full sample. These findings are useful for firms’ management for revising the optimal level of short-term debts according to CCC fluctuation. Also, the lending agencies can use these results for the assessment of firms’ risk levels and adjustment of the interest rate.
Space history of the High Possil and Strathmore meteorites from Ne and Ar isotopes
Authors: Carracedo A. , Stuart F.M. , Di Nicola L. , Faithfull J.W.
Published: May 2022

The High Possil and Strathmore L6 chondrites fell in Scotland in 1804 and 1917 respectively. Unravelling their cosmic-ray exposure (CRE) ages provides crucial information about when they were ejected from the parent body, how they were delivered to Earth and is ultimately important for understanding the dynamics of small bodies in the solar system. Here we use new measurements of the Ne and Ar isotopic composition to determine CRE ages of both meteorites. Duplicated cosmogenic
21
Ne and
38
Ar concentrations yield CRE ages of 44.6 ± 4.6 Ma for High Possil and 15.4 ± 1.3 Ma for Strathmore. These coincide with well-established peaks in the ejection record for the L6 chondrites. They yield
40
Ar gas retention ages in excess of 3.15 Ga, which is consistent with both meteorites originating at depth within the parent body at the time of asteroidal break-up.

Thematic collection:
This article is part of the Early Career Research collection available at:
https://www.lyellcollection.org/cc/SJG-early-career-research
Successive Phase Transitions and Multiferroicity in Deformed Triangular-Lattice Antiferromagnets Ca3MNb2O9 (M=Co, Ni) with Spatial Anisotropy
Authors: Huang Q. , Lee M. , Choi E. S. , Ma J. , Dela Cruz C. , Zhou H. D.
Published: May 2022

We constructed the magnetic field-temperature phase diagrams of new quasi-two-dimensional isosceles triangular lattice antiferromagnets (TLAF) Ca3MNb2O9 (M=Co, Ni) from dc and ac magnetic susceptibilities, specific heat, dielectric constant, and electric polarization measurements on single crystalline samples. Ca3CoNb2O9 with effective spin-1/2 Co2+ ions undergoes a two-step antiferromagnetic phase transition at T
N1 = 1.3 K and T
N2 = 1.5 K and enters a stripe ordered state at zero magnetic field. With increasing field, successive magnetic phase transitions, reminiscent of the up-up-down (uud) and the oblique phases, are observed. The dielectric constant of Ca3CoNb2O9 shows anomalies related to the magnetic phase transitions, but clear evidence of ferroelectricity is absent. Meanwhile, Ca3NiNb2O9 with spin-1 Ni2+ ions also shows a two-step antiferromagnetic transition at T
N1 = 3.8 K and T
N2 = 4.2 K at zero field. For Ca3NiNb2O9, the electric polarization in the magnetic ordered phases was clearly observed from the pyroelectric current measurements, which indicates its coexistence of magnetic ordering and ferroelectricity.
Remote Monitoring and Management System of Intelligent Agriculture under the Internet of Things and Deep Learning
Authors: Zhu Meirong , Shang Jie
Published: May 2022

Based on the Internet of Things (IoT) technology and deep learning algorithm, a greenhouse intelligent agriculture management system was established to analyse the application value of the intelligent agriculture remote monitoring management system in the greenhouse planting industry. Based on the analysis of greenhouse planting demand and environmental factors, the intelligent agriculture monitoring system is established based on the IoT, and the greenhouse system controller is designed based on the adaptive proportion integration differentiation (PID) algorithm. The noise data removal method is established based on the furthest priority strategyk-means (FPKM) algorithm, and the greenhouse data management system is established mainly by the business platform and management platform. The data set of air temperature during the cultivation of Flammulina velutifolia in a factory from October 2020 to January 2021 was selected as the research data to analyse the ability of the IoT-based IARMM system to collect greenhouse temperature, carbon dioxide, and light data. In addition, the application of the greenhouse data management system in greenhouse data monitoring and control is analysed. The processing capability of agricultural environment monitoring data based on the FPKM algorithm is analysed. The results show that the intelligent agriculture monitoring system based on IoT and machine learning can effectively monitor the data on greenhouse temperature, carbon dioxide, light, and other environmental factors, and the greenhouse data management system can effectively ensure the normal operation of equipment and data storage. After being processed by the FPKM algorithm, outliers are identified and effectively removed. Under random seeds, the iteration times of the FPKM algorithm and thek-means algorithm are significantly different. The iteration number of the FPKM algorithm is basically stable at approximately 2 times, while the iteration number of thek-means algorithm obviously fluctuates. Based on the IoT and FPKM algorithm, the intelligent agriculture monitoring system covering the user monitoring center, data center module, and mobile phone client module is established. This work establishes a practical remote monitoring and management system for intelligent agriculture based on the IoT and machine learning algorithm, which provides a new idea for intelligent agricultural management.
Multimodal Sarcasm Detection: A Deep Learning Approach
Authors: Bharti Santosh Kumar , Gupta Rajeev Kumar , Shukla Prashant Kumar , Hatamleh Wesam Atef , Tarazi Hussam , Nuagah Stephen Jeswinde
Published: May 2022

In the modern era, posting sarcastic comments on social media became the common trend. Sarcasm is often used by people to taunt or pester others. It is frequently expressed through inflexion, tonal stress in speech or in the form of lexical, pragmatic, and hyperbolic features present in the text. Most of the existing work has been focused on either detecting sarcasm in textual data using text features or audio data using audio features. This article proposed a novel approach by combining textual and audio features together to detecting sarcasm in conversational data. This hybrid method takes a combined vector of extracted audio and text features from their respective models as the input. This combined features will compensated the shortcomings of only text features and vice-versa. The obtained result of hybrid model outperforms both the individual model significantly.
The AI-Based Channel Prediction Scheme for the 5G Wireless System in High-Speed V2I Scenarios
Authors: Zhang Zhengyu , Xiong Lei , Yao Dongpin , Wang Yuanjie
Published: May 2022

Now, the fifth-generation (5G) system plays a more and more important role in the high-speed vehicle-to-infrastructure (V2I) scenario. In order to realize the high-reliability and high-efficiency transmission, it is essential to obtain accurate channel state information (CSI) for the 5G system. However, due to the fast time-varying and nonstationary characteristics of the channel in high-speed V2I scenarios, channel estimation is a challenging issue. In this paper, an artificial intelligence- (AI-) based channel prediction scheme, called AI-ChannelNet, is proposed to improve the CSI prediction performance in high-speed V2I scenarios. Specifically, AI-ChannelNet is trained in real time based on the historical channel estimation on the reference signal (RS) to realize accurate channel prediction and then recovers the received signal according to the predicted channel information. The integration of the convolutional neural network (CNN) and long short-term memory (LSTM) is designed to extract temporal features of the channel. And an online RS-based training algorithm is proposed, enabling AI-ChannelNet to track the channel variation. Evaluated by experiments, the proposed scheme outperforms conventional methods a lot, and more improvement could be achieved at a higher speed. Besides, the proposed scheme performs well without modification of the 5G radio frame and loss of transmission efficiency.
Application of Cross-Linked and Non-Cross-Linked Hyaluronic Acid Nano-Needles in Cosmetic Surgery
Authors: Huang Yiming , Yang Ping
Published: May 2022

The common feature of non-cross-linked hyaluronic acid nano-needles is that they penetrate the skin and dissolve rapidly, and the non-cross-linked hyaluronic acid will migrate under the skin, so it is difficult to maintain the long-term expansion effect in a fixed position. In order to achieve the relatively long-term antiwrinkle effect, a kind of cross-linked and non-cross-linked compound hyaluronic acid microne was prepared. By inserting the microne under the skin, dissolving the non-cross-linked part under the skin and introducing the cross-linked gel particles under the skin, the effect of extending the microne was achieved. The mechanical properties, permeability, and degradation rate of cross-linked and non-cross-linked hyaluronic acid composite nano-needles were studied in detail. Experimental results show that the higher the content of CHA, the slower the degradation rate of the microneedle, and the skin swelling of the HA_CHA (1 : 1) microneedle is the most lasting. With the increase of CHA content in microneedle matrix materials, the degree of epidermal expansion decreased. The preparation of cross-linked and non-cross-linked hyaluronic acid microneedles has the potential to be effectively used as dermal fillers in cosmetics or antiaging treatments.
Sharp Constants for
q
-Analogue of Hausdorff Operators on Central
q
-Morrey Spaces
Authors: Wei Mingquan , He Qianjun , Li Xiang , Wang Zequn
Published: May 2022

In this paper, we establish the sharp constant for

q

-analogus of Hausdorff operators on central

q

-Morrey spaces. As applications, the sharp constants for the

q

-analogus of Hardy operator and its dual operator, the

q

-analogue of Hardy-Littlewood-Pólya operator, and the

q

-analogue of Hilbert operator on central

q

-Morrey spaces are deduced.
Diagnostic Value of Magnetic Resonance Susceptibility-Weighted Imaging Scanning in Different Types of Early Prostate Cancer
Authors: Gao Ruihui , Liu Jiayuan , Zhu Hengcheng
Published: May 2022

To investigate the cost of MRI-sensitive imaging (SWI) for early-stage prostate cancer. In 2019, the research group included a total of 60 leukemia patients, all of whom were diagnosed with prostate-specific antigen (PSA). According to the range of PSA values, they were group A (18 cases), group A 0-44 mg/ml (18 cases), and group B 4-1010 mg/ml (26 cases). 10 mg/ml was divided into C group (16 cases). Another 60 patients with benign prostatic hyperplasia treated at the same time served as a control group. All patients underwent sensitive MRI scanning, followed by diagnostic and clinical evaluation of weighted MRI scanning to diagnose various types of prostate cancer. The results showed that there was no difference in Ve levels among the three groups (

P
>
0.05

); the SUSE score and Ktrans and Kep levels of the patients in group C were higher in groups B, A, and A (

P
<
0.05

). In patients with early leukemia, SUSE score was significantly correlated with Ktrans and Kep levels (

P
<
0.05

), but not with Ve and

P
>
0.05

levels. Magnetic resonance imaging can be used to diagnose prostate cancer. It can differentiate and diagnose different types of prostate cancer early. This is important for evaluating the benefits of prostate cancer screening and treatment.
[Retracted] Analysis and Research on Audience Satisfaction of Performing Arts Projects in Tourist Scenic Spots Based on the ASCI Model and Big Data
Authors: Ding Jiaran , Yu Lin
Published: May 2022

The development trend of tourism performance networking, although convenient for audience consumption, also makes the performance information present the development trend of big data. In the mass of information, how to accurately locate products and improve audience satisfaction is an urgent problem to be solved. In order to better explore the evaluation of tourism performance by the customer satisfaction evaluation model, analyze the development prospect of tourism in Jiangxi Province in the future, improve the customer satisfaction evaluation model with rough set, and propose a composite customer satisfaction evaluation model. By setting the adjustment value of the evaluation index, the model not only avoids the “false eigenvalue” of the satisfaction evaluation result but also simplifies the calculation process of the model and improves the accuracy, calculation efficiency, and single data processing capacity of the satisfaction evaluation. According to the MATLAB simulation results, the composite customer satisfaction evaluation model constructed in this study is better, the calculation accuracy is >97%, and the calculation time is 40 seconds, which are better than the original customer satisfaction evaluation model. Therefore, the composite customer satisfaction evaluation model can be applied to the evaluation of tourism performance products to provide data support for the evaluation price of audience satisfaction in Jiangxi Province.
Effect of Different Dielectric and Magnetic Nanoparticles on the Electrical, Mechanical, and Thermal Properties of Unidirectional Carbon Fiber-Reinforced Composites
Authors: Ahmad Hafiz Shehbaz , Hussain Tanveer , Nawab Yasir , Salamat Shuaib
Published: May 2022

Carbon fiber-reinforced particulate composites are immensely used in commercial and military applications due to their excellent functional and mechanical performance. Several studies have been reported to use nanofiller in carbon fiber-reinforced composites to improve their functional and mechanical performance. However, a comparative study was required to depict the best dielectric and magnetic nanofillers with excellent functional and mechanical performance. The current research was performed to compare the effect of different dielectric and magnetic nanoparticles on the electrical, mechanical, and thermal properties of carbon fiber-reinforced composites. The objective was to identify a nanofiller with excellent electrical, mechanical, and thermal properties with the same weight ratio and a potential candidate for EMI shielding application. Unidirectional composite prepregs containing 2% (by weight) of each magnetic and dielectric nanofillers were fabricated on an in-house developed lab-scale UD prepreg manufacturing setup. Among the dielectric nanofillers, the composite samples containing MWCNT nanofiller showed the highest electrical, thermal, and mechanical properties. The composite samples containing titanium oxide nanofillers showed better flexural, electrical, and thermal properties among magnetic nanofillers.
Plants with Therapeutic Potential for Ischemic Acute Kidney Injury: A Systematic Review
Authors: Ali Arif , Lima Sampaio Tiago , Khan Haroon , Jeandet Philippe , Küpeli Akkol Esra , Bahadar Humaira , Costa Martins Alice Maria
Published: May 2022

Acute kidney injury (AKI) is a complex condition which has an intricate pathology mostly involving hemodynamic, inflammatory, and direct toxic effects at the cellular level with high morbidity and mortality ratios. Renal ischemic reperfusion injury (RIRI) is the main factor responsible for AKI, most often observed in different types of shock, kidney transplantation, sepsis, and postoperative procedures. The RIRI-induced AKI is accompanied by increased reactive oxygen species generation together with the activation of various inflammatory pathways. In this context, plant-derived medicines have shown encouraging nephroprotective properties. Evidence provided in this systemic review leads to the conclusion that plant-derived extracts and compounds exhibit nephroprotective action against renal ischemic reperfusion induced-AKI by increasing endogenous antioxidants and decreasing anti-inflammatory cytokines. However, there is no defined biomarker or target which can be used for treating AKI completely. These plant-derived extracts and compounds are only tested in selected transgenic animal models. To develop the results obtained into a therapeutic entity, one should apply them in proper vertebrate multitransgenic animal models prior to further validation in humans.
Circulating Galectin-3 and Aldosterone for Predicting Atrial Fibrillation Recurrence after Radiofrequency Catheter Ablation
Authors: Ruan Zhong-bao , Gao Run-feng , Wang Fei , Chen Ge-cai , Zhu Jun-guo , Ren Yin , Zhu Li
Published: May 2022

Background. Circulating galectin-3 (Gal-3) and aldosterone (ALD) are involved in fibrosis and inflammation. However, their potential value as predictors of atrial fibrillation (AF) recurrence after radiofrequency catheter ablation (RFCA) is unknown or controversial. Therefore, the aim of this study was to assess the relationship between baseline Gal-3, ALD levels, and AF recurrence in patients performing RFCA. Methods. 153 consecutive patients undergoing RFCA were included. Gal-3 and ALD were measured at baseline. Univariate and multivariate Cox regressions were performed to determine the predictors of AF recurrence. Receiver operating characteristic (ROC) curve and Kaplan-Meier (K-M) curve were used to assess the value of predictors. Results. There were 35 (22.88%) cases of AF recurrence after RFCA. The recurrence group had significantly higher preoperative serum levels of Gal-3 and ALD than the nonrecurrence group. Univariate and multivariate analysis showed that Gal-3 (

HR
=
1.28

, 95% CI: 1.04-1.56,

p
=
0.02

) and ALD (

OR
=
1.02

, 95% CI: 1.00-1.03,

p
<
0.03

) were significantly associated with AF recurrence after RFCA. The area under the curve (AUC) of preoperative serum Gal-3, ALD, and 2 combined to predict the recurrence of AF patients after RFCA was 0.636, 0.798, and 0.893, respectively, while sensitivity was 65.32%, 71.69%, and 88.61%, respectively and specificity was 77.46%, 78.53%, and 86.0%, respectively. Patients with Gal-3 above the cutoff value of 14.57 pg/ml had higher frequent AF recurrence than the patients with

Gal
−
3
≤
14.57
 
pg
/
ml

(35% vs. 12%,

p
<
0.001

) during a follow-up. Meanwhile, patients with ALD above the cutoff value of 243.61 pg/ml also had a higher AF recurrence rate than those with

ALD
≤
243.61
 
pg
/
ml

(37% vs. 11%,

p
<
0.001

) during a follow-up. The recurrence rate in patients with

Gal
−
3
>
14.57
 
pg
/
ml
+
ALD
>
243.61
 
pg
/
ml

was higher than that in patients with baseline

Gal
−
3
>
14.57
 
pg
/
ml

or

ALD
>
243.61
 
pg
/
ml

and patients with

Gal
−
3
≤
14.57
 
pg
/
ml
+
ALD
≤
243.61
 
pg
/
ml

(57% vs. 14% vs. 9%,

p
<
0.01

, respectively). Conclusion. AF recurrence after RFCA had higher baseline Gal-3 and ALD levels, and higher preoperative circulating Gal-3 and ALD levels were independent predictors of AF recurrence for patients undergoing RFCA, while combination of preoperative Gal-3 and ALD levels has higher prediction accuracy.
Effect Investigation of Ultraviolet Ageing on the Rheological Properties, Micro-Structure, and Chemical Composition of Asphalt Binder Modified by Modifying Polymer
Authors: Sun Xiaolong , Xu Qin , Fang Guotao , Zhu Yongqiang , Yuan Zhengbing , Chen Qian , Yuan Junshen
Published: May 2022

In order to investigate the effect of nano polymer materials on the UV aged performance of asphalt binder, a nano PA modifying agent was selected to prepare modified asphalt. Under the effect of UV radiation, the modifying effect of nano PA on the rheological properties of asphalt was studied. With the extension of UV ageing time, the microstructure variation of PA modified asphalt was characterized by using a focused ion beam scanning electron microscope (FIB-SEM). The thermophysical properties of PA modified asphalt were investigated by thermogravimetric analysis (TG). Furthermore, the functional group compositions of PA modified asphalt were investigated by dynamic FTIR. The results showed that with the extension of UV ageing time, the PA modifier could mitigate the ageing effect of UV radiation on the asphalt binder. PA modifier could achieve an increasing effect on the viscoelasticity of asphalt during the UV ageing process. PA modifier suppressed the generation of microcracks in the surface microzone of UV aged asphalt samples. PA modifier could promote the thermal stability improvement of asphalt binder when subjected to UV radiation. The generation of carbonyl and sulfoxide groups in asphalt was inhibited during the UV ageing period, which indicated that the UV induced reaction of asphalt could be postponed by the PA modifying agent.
Deep Learning-Based Text Sentiment Analysis in Chinese International Promotion
Authors: Yao Ge
Published: May 2022

The importance of teaching Chinese as a foreign language has grown in tandem with the rapid advancement of China’s politics and economy. The Chinese language’s international promotion strategy has taken shape, and it has become a major cause for our country and nation. Under such a new situation, the content and form of Chinese cultural communication have taken on new characteristics. Foreign friends will use a variety of ways to express their emotions and attitudes toward the Chinese on the Internet, most of which are mainly text comments. Sentiment analysis of text comments can provide valuable emotional information for our Chinese international communication and promotion activities. Text sentiment analysis using deep learning algorithms has advanced considerably in recent years. For that purpose, this study proposes a bidirectional long- and short-term memory network, as well as a text sentiment analysis model with a self-attentive mechanism, and applies it to comments on Chinese language promotion. Experiments show that our model achieves a good recognition situation and has application value.
Research on Feature Fusion Speech Emotion Recognition Technology for Smart Teaching
Authors: Zhang Shaoyun , Li Chao
Published: May 2022

At present, there are numerous intelligent teaching applications based on various advanced pattern recognition technologies, such as face sign-in, classroom action recognition, student facial expression recognition, and other systems which have been gradually applied to major schools. Speech emotion recognition can analyze the characteristics of current teaching emotions, so as to discover the rules and details of teachers’ grasp of emotions. In order to realize the task of emotion classification in the process of intelligent teaching through machine learning technology, a teaching speech emotion recognition method with multifeature fusion and deep learning is proposed. The proposed method front-end processes the speech spectrum features in a multifeature fusion manner and combines them with an artificial neural network classifier to form the final speech emotion recognition model. First, after speech preprocessing, three features are selected and fused features using a network structure trained by parallel subnetworks. Then, the classifier used is a hybrid neural network classifier combining a convolutional neural network and a recurrent neural network. Finally, 100 open web courses were used to train and test the model. The test results show that the hybrid neural network sound model using multifeature fusion has good teaching speech emotion recognition capability.
Life Prediction of Iron Ore Tailings Concrete under Freeze-Thaw Cycle Based on Weibull Distribution
Authors: Han Jie , Fu Chun , Liu Songyang , Li Haijun , Wang Lunan , Sun Hai , Wu Haotian
Published: May 2022

It is urgent to improve the comprehensive utilization rate of tailings, especially to solve the problem of fine iron ore tailings treatment and the shortage of natural sand, so iron ore tailings concrete with different replace rates was prepared in this paper. At the same time, in order to further popularize the wide application of iron tailings concrete, it is of great significance to study the frost resistance and life prediction of it in cold regions. Thereby, a series of experimental research on iron ore tailings concrete under freezing-thawing cycles was carried out to analyze the attenuation law of quality, compressive strength, and relative dynamic elastic modulus after different freezing-thawing cycles. In this paper, the relative dynamic elastic modulus was used to define the damage factor, and the freezing-thawing damage model of iron ore tailings concrete was established based on Weibull distribution. Here, the specific function form of two-parameter Weibull distribution of iron ore tailings concrete under freezing-thawing cycle was proposed, and the model was used to predict life of it. The results showed that, compared with the replacement rates of 20%, 60%, and 80%, the iron ore tailings with 40% replacement rate had the best improvement effect on the frost resistance of concrete and can delay the attenuation of the compressive strength of concrete. This model can not only predict the durability life of iron ore tailings concrete under freezing-thawing conditions, but also provide theoretical reference for the application of iron ore tailings concrete in cold areas.
Method for Optimizing Energy Consumption in Machining Manufacturing Process
Authors: Kong Tengqiao , Nhg Dong Ren , Shi Van Tinh
Published: May 2022

With the rapid development of the economy and the continuous maturity of various industries and departments, the total amount of energy required by enterprises in the process of production and operation is also increasing year by year. To achieve sustainable development, it is necessary to adjust the current production and operation mode, reasonably evaluate the current state of resources, use advanced technology to optimize each link of production, and regard low-energy consumption and low carbon as the key to production improvement. In this paper, the integrated realization method of process planning and production scheduling based on intelligent algorithm is adopted, and the integrated model is solved by using the chromosome hierarchical coding genetic algorithm. When the alternative process schemes generated for each part through nonlinear process planning are given, the integrated model can weigh the optimization objectives and decide the suitable process route, machine tool selection scheme, and corresponding production scheduling scheme for each part. In this paper, a case study on the energy-saving effect of energy consumption optimization methods in machining and manufacturing processes is carried out. Taking a manufacturing enterprise as the background, the effectiveness of the proposed energy-saving method is verified by comparing the energy consumption of a batch of mechanical product parts in the process planning and production scheduling integrated mode and the traditional serial working mode.
Intelligent Planning of Tourist Routes Based on Cloud Computing and Marching Algorithm
Authors: Lu Junli
Published: May 2022

In order to improve the effect of modern tourism route planning, this article combines the cloud computing advancement algorithm to construct a tourism route intelligent planning system and combines the current people's tourism needs to carry out intelligent tourism route planning. Based on the fast forward algorithm of the program function equation, this article uses the fast forward algorithm to solve the discrete nonlinear program function equation and directly obtain the cloud computing data. In addition, the self-intersection phenomenon of the wave front must be considered when describing the characteristics of the cloud computing information field by using the process of the equivalent cloud computing information front expanding to the surrounding. Finally, this article constructs the intelligent system structure. The research results show that the intelligent travel route planning system based on cloud computing and marching algorithm proposed in this article can play an important role in modern smart tourism.
Forwarding Collision Assessment with the Localization Information Using the Machine Learning Method
Authors: Guo Lei , Jia Yizhen , Hu Xianghui , Dong Feihong
Published: May 2022

Freeway crashes occupied 30% of total crashes. The advanced driver-assistance system (ADAS) often underestimates or omits the necessary collision warning. To investigate the forward collision in complex traffic conditions, the TTC (time-to-collision) is regarded as a surrogate for collision risk assessment. The study aims to design a forward-collision warning method for ADAS in the urban freeway scenario. The testing vehicle is equipped with sensors and a satellite navigation system. The TTC was collected from the Xi’an Rao Cheng expressway for the car-following scenario for three days. A comprehensive Gaussian model, which consists of three sub-GMM models is applied to describe the TTC distribution. The vehicle trajectories were extracted in the car-following state. To improve the efficiency of the forwarding collision system, four seconds are chosen as an analysis window in the car-following state. Two time-series machine models were used to predict TTC in advance. The TTC prediction models were constructed on the basis of the long short-term memory (LSTM). The prediction result was compared with the deep belief network (DBN) model. The comparison results show that the LSTM model is faster than the DBN model. The number of iterations is 100. The loss function of the LSTM is 0.06. The LSTM outperforms the DBN model and is suitable for car-following warnings.
Comprehensive Characterizations of Immune Receptor Repertoire in Tumors and Cancer Immunotherapy Studies
Authors: Song Li , Ouyang Zhangyi , Cohen David , Cao Yang , Altreuter Jennifer , Bai Gali , Hu Xihao , Livak Kenneth J. , Li Heng , Tang Ming , Li Bo , Liu X. Shirley
Published: May 2022

We applied our computational algorithm TRUST4 to assemble immune receptor (T-cell receptor/B-cell receptor) repertoires from approximately 12,000 RNA sequencing samples from The Cancer Genome Atlas and seven immunotherapy studies. From over 35 million assembled complete complementary-determining region 3 sequences, we observed that the expression of CCL5 and MZB1 is the most positively correlated genes with T-cell clonal expansion and B-cell clonal expansion, respectively. We analyzed amino acid evolution during B-cell receptor somatic hypermutation and identified tyrosine as the preferred residue. We found that IgG1+IgG3 antibodies together with FcRn were associated with complement-dependent cytotoxicity and antibody-dependent cellular cytotoxicity or phagocytosis. In addition to B-cell infiltration, we discovered that B-cell clonal expansion and IgG1+IgG3 antibodies are also correlated with better patient outcomes. Finally, we created a website, VisualizIRR, for users to interactively explore and visualize the immune repertoires in this study.

See related Spotlight by Liu and Han, p. 786
Associations among Audiometric, Doppler Hydroacoustic, and Subjective Outcomes of Venous Pulsatile Tinnitus
Authors: Hsieh Yue-Lin , Wu Yongzhen , Wang Hai , Xu Xiaobing , Guo Ping , Wang Xing , Hsieh Yue-Da , Lu Hanyu , Wang Wuqing
Published: May 2022

Objective: Venous pulsatile tinnitus (PT) has received increasing attention recently. As analyses of psychophysical and neuropsychological dimensions of venous PT are lacking, this study aimed to quantitatively and qualitatively investigate the correlation among audiometric, hydroacoustic, and subjective outcomes in patients with PT. Methods: Fifty-five venous PT patients, with or without sigmoid sinus wall anomalies (SSWAs), were subdivided into SSWAs (n = 30) and non-SSWAs (n = 25) groups. Audiometric and hemodynamic evaluations were assessed. Questionnaires including the Tinnitus Handicap Inventory, Hospital Anxiety and Depression Scale (HADS), and Athens Insomnia Scale (AIS) were deployed to evaluate the psychological impacts of PT. Results: Among 55 subjects, PT frequency-related pure-tone audiometry (PTA) was significantly different between ipsilesional non-PT frequency-related PTA (p < 0.01), ipsilateral jugular vein compression PTA (p < 0.01), and contralesional ear PTA (p < 0.01). In contrast with the pulsatility index and flow velocity, bilateral EOET and flow volume were significantly different (p < 0.01). Of the 3 questionnaire types, there was a strong correlation between HADS anxiety and AIS scores (r = 0.658, p < 0.01). The duration of PT was not correlated with subjective outcomes, and there was no statistical significance found among audiometric, hemodynamic, and subjective outcomes between SSWAs and non-SSWAs groups. Conclusions: (1) The duration of PT was irrelevant to the increase of PTA. (2) Venous PT is the perception of vascular flow sound, in which hydroacoustic characteristics can be highly independent. (3) Anxiety, depression, and sleep disorders commonly prevail among PT patients.
Giant Koenen Tumors as the Presenting and Only Clinical Sign of Tuberous Sclerosis Complex in a 56-Year-Old Man and Its Surgical Management
Authors: Olvera-Rodríguez Valeria , Barrera Garibay Andrea C. , Domínguez-Cherit Judith
Published: May 2022

Introduction: Tuberous sclerosis complex (TSC) is a genetic multisystem disorder with prominent skin involvement. Multiple ungual fibromas, also known as Koenen tumors (KTs), are one of the major diagnostic criteria and occur approximately in 50% of patients with TSC. They are disfiguring, painful, and challenging to treat as they frequently recur. There are 2 previous cases in the literature of KTs as the only clinical sign of TSC. Case Presentation: A 56-year-old male patient with intellectual disability presented with a history of ungual growths that had gradually increased in size and number for 20 years. The diagnosis of KTs was established on clinical grounds, without the requirement of histological confirmation. No additional clinical evidence of TSC was found. Complete surgical excision of the tumors located in the proximal nail matrix, periungual folds, and nail bed of each toe was successfully performed. Discussion: The association between KTs and intellectual disability with TSC supported the clinical diagnosis. To date, there is no standard first-line treatment for KTs. Complete surgical excision up to the proximal base of the tumor offers satisfactory results in terms of functionally and esthetic appearance and could be considered the preferred therapeutic modality for patients with severe functional and cosmetic impairment. Prompt recognition of the many signs and symptoms associated with TSC is important to achieve early diagnosis, preventing further complications.
Moxibustion plus Acupuncture for the Treatment of Poststroke Shoulder Pain: A Randomized Controlled Pilot Study
Authors: Zhao Hong-Bo , Lou Ya-Bing , Zhou Tian , He Jing , You Xin , Yang Ao-Ran , Gong Wei-Jun
Published: May 2022

Background: In China, 45% of stroke patients suffer from poststroke shoulder pain, which brings about many obstacles to further rehabilitation. To date, there have been a few studies evaluating the effects of acupuncture or massage in treating poststroke shoulder pain, and good effects have been shown. However, better clinical treatments are still needed. Objective: To explore a more effective treatment for poststroke shoulder pain, the clinical effects of moxibustion plus acupuncture were assessed. Methods: Sixty patients were randomly divided into the control and intervention groups. The control group received a standard stroke treatment protocol including acupuncture, and the intervention group was given moxibustion combined with acupuncture. The visual analogue scale (VAS), National Institutes of Health Stroke Scale (NIHSS), Fugl-Meyer motor assessment, Barthel Index, and 17-item Hamilton Rating Scale for Depression (HAMD-17) were applied, and differences were analyzed. Results: After 4 weeks of treatment, compared with the control group, the intervention group demonstrated significant improvement in Fugl-Meyer motor assessment and HAMD-17 (both p < 0.01) as well as in the VAS, NIHSS, and Barthel Index (all p < 0.05). Conclusion: Moxibustion plus acupuncture treatment can alleviate poststroke shoulder pain, improve upper limb motor function and the ability to perform activities of daily living, and relieve patients’ depression.
Detection of Cavitated Proximal Carious Lesions in Permanent Teeth: A Visual and Radiographic Assessment
Authors: Muñoz-Sandoval Cecilia , Gambetta-Tessini Karla , Botelho Juliana N. , Giacaman Rodrigo A.
Published: May 2022

Detection of proximal carious lesions involves the combination of clinical and radiographic methods, both with inherent difficulties. The present cross-sectional study is aimed at estimating the prevalence of cavitation in proximal carious lesions, based on a direct clinical assessment of previously detected radiographic lesions, in permanent molars and premolars. Proximal dental surfaces were radiographically evaluated using the ADA coding system and cavitation was determined through clinical visual examination of the surfaces after separation with elastomeric bands. One-hundred and twenty-six patients attending the dental clinics at the University of Talca were examined, comprising 508 proximal surfaces with radiographic codes ranging from E1 to D3. Two examiners were trained and calibrated for radiographic and clinical detection of proximal lesions. Most participants were females (61.9%). The age mean of participants was 28.7 (0.8) years old. A total of 22.2% of the examined surfaces were cavitated. Only few lesions coded as E1 (n = 4; 2.1%) and E2 (n = 9; 9.8%) were cavitated. Fifty D1 (35.5%) and 22 D2 (41.5%) lesions were cavitated after separation. Most lesions coded as D3 (n = 28; 84.8%) were cavitated. The multilevel binary regression model (p = 0.003) demonstrated that sex, age, jaw, tooth type, surface, and side were not associated with the likelihood of having proximal cavitation. Challenging conventional wisdom, most D1 and D2 lesions were not cavitated. Combining detection methods seems desirable to increase the accuracy in assessing approximal posterior lesions. The low proportion of cavitated lesions reinforces the idea of cautiously indicating invasive approaches for managing proximal carious lesions.
Neural Reinstatement of Overlapping Memories in Young and Older Adults
Authors: Lee Kyoungeun , Mirjalili Soroush , Quadri Ayesha , Corbett Brittany , Duarte Audrey
Published: May 2022

When we update our episodic memories with new information, mnemonic competition between old and new memories may result because of the presence of shared features. Behavioral studies suggest that this competition can lead to proactive interference, resulting in unsuccessful memory updating, particularly for older adults. It is difficult with behavioral data alone to measure the reactivation of old, overlapping memories during retrieval and its impact on memory for new memories. Here, we applied encoding–retrieval representational similarity (ERS) analysis to EEG data to estimate event-specific encoding-related neural reinstatement of old associations during the retrieval of new ones and its impact on memory for new associations in young and older adults. Our results showed that older adults' new associative memory performance was more negatively impacted by proactive interference from old memories than that of young adults. In both age groups, ERS for old associative memories was greater for trials for which new associative memories were forgotten than remembered. In contrast, ERS for new associative memories was greater when they were remembered than forgotten. In addition, older adults showed relatively attenuated target (i.e., new associates) and lure (i.e., old associates) ERS effects compared to younger adults. Collectively, these results suggest that the neural reinstatement of interfering memories during retrieval contributes to proactive interference across age, whereas overall attenuated ERS effect in older adults might reflect their reduced memory fidelity.
Temporal Expectation Improves Recognition Memory for Spatially Attended Objects
Authors: Jones Alexander , Ward Emma V. , Csiszer Enida L. , Szymczak Joanna
Published: May 2022

Recent evidence suggests that temporal expectation is beneficial to memory formation. Rhythmic presentation of stimuli during encoding enhances subsequent recognition and is associated with distinct neural activity compared with when stimuli are presented in an arrhythmic manner. However, no prior study has examined how temporal expectation interacts with another important form of facilitation—spatial attention—to affect memory. This study systematically manipulated temporal expectation and spatial attention during encoding to examine their combined effect on behavioral recognition and associated ERPs. Participants performed eight experimental blocks consisting of an encoding phase and recognition test, with EEG recorded throughout. During encoding, pairs of objects and checkerboards were presented and participants were cued to attend to the left or right stream and detect targets as quickly as possible. In four blocks, stimulus presentation followed a rhythmic (constant, predictable) temporal structure, and in the other four blocks, stimulus onset was arrhythmic (random, unpredictable). An interaction between temporal expectation and spatial attention emerged, with greater recognition in the rhythmic than the arrhythmic condition for spatially attended items. Analysis of memory-specific ERP components uncovered effects of spatial attention. There were late positive component and FN400 old/new effects in the attended condition for both rhythmic and arrhythmic items, whereas in the unattended condition, there was an FN400 old/new effect and no late positive component effect. The study provides new evidence that memory improvement as a function of temporal expectation is dependent upon spatial attention.
The Network Society Today
Authors: Fernández-Ardèvol Mireia , Ribera-Fumaz Ramon
Published: May 2022

2021 marked the 25th Anniversary of Manuel Castells’ The Rise of the Network Society, the first volume of the Information Age trilogy. The Trilogy immediately became one of the most influential works to understand the societal change in the wake of the digital revolution. More than two decades later, many of the emerging processes theorised and analysed in the Trilogy have reached full maturity, if not evolved in unexpected ways. Also, several theoretical and epistemological trends have developed or consolidated in the social sciences that have either been influenced by or challenged the Trilogy position. In this scenario, is the Network Society Theory still relevant for understanding today’s digitalised society? How should we develop the Network Society approach now? This special issue aims to answer these questions. In particular, in this collection of papers, we identify three interrelated dimensions: new developments in the evolution or disruption of the Network Society, the articulation between network logics and other spatial forms, and the relation of the Network Society with recurrent topics in Castells’ work beyond the Information. The papers are a selection of the contributions to the online workshop The Network Society Today: (Revisiting) the Information Age Trilogy (November 2–30, 2020), in which Prof. Castells also participated. This volume brings together a wide range of established and emerging scholars from a diversity of Social Sciences disciplines with plural theoretically informed papers tackling rich empirical case studies across the world, spanning throughout America, Europe, Africa and Asia. Contributions conclude with a reflection by Manuel Castells on them and his work.
Physical accessibility in Malaysian higher educational institutions: Voices of students with disabilities
Authors: Chan Cheong Chong , Yusof Yusmarhaini , Ahmad Ramli Fatimah Zailly , Hillaluddin Azlin Hilma , Mat Saad Zarina
Published: May 2022

In Malaysia, inclusiveness for people with disabilities in higher education remains a challenge. This study addresses the perception of 52 students with disabilities of their campuses’ physical accessibility. The survey shows partial dissatisfaction with facilities, with seniors displaying the highest discontent. In addition, interviews with 14 students reveal opinion discrepancies between students with visual impairments and those with other physical disabilities. The overall findings imply that inclusive education for students with disabilities is far from achieved. Thus, Malaysian social work has a critical role in intervening and advocating for inclusiveness in higher education.