bluuebunny/crossref_metadata_2025 huggingface dataset:
A HEURISTIC COMPUTING APPROACH USING SEQUENTIAL QUADRATIC PROGRAMMING TO SOLVE THE FIFTH KIND OF INDUCTION MOTOR MODEL
Authors: SABIR ZULQURNAIN , RAJA MUHAMMAD ASIF ZAHOOR , MAHMOUD S. R. , GUIRAO JUAN L. G. , SÁNCHEZ JUAN M.
Published: August 2022

The purpose of the current investigation is to solve the fifth kind of induction motor model using an advanced computational scheme by operating the artificial neural networks (ANNs), global scheme as genetic algorithm (GA) along with the rapid local search sequential quadratic programming technique (SQPT), i.e. ANN-GA-SQPT. ANNs are implemented to discretize the fifth kind of induction motor model to express the merit function based on the mean square error. The numerical presentation of the proposed ANN-GA-SQPT is pragmatic for three different problems based on the fifth kind of induction motor model to authenticate the efficacy, consistency and importance of the proposed ANN-GA-SQPT. Moreover, statistical representations are provided in order to check the precision, convergence and accuracy of the present ANN-GA-SQPT.
PASSIVITY AND PASSIVATION OF FRACTIONAL-ORDER NONLINEAR SYSTEMS
Authors: HAN ZHIMIN , WANG YI , JI QUANBAO , ALODHAIBI SULTAN
Published: August 2022

Although the passivity of integer-order systems has been extensively analyzed, the research outcomes on the passivity of fractional-order nonlinear systems (FONSs) are scarce. This paper presents some theoretical results on passivity and passivation of FONSs. Based on the definition of the passivity of FONSs, and by using the Lyapunov stability theory and the linear matrix inequality (LMI) method, some conditions are derived to assure the FONSs is passive, which enrich the existing theoretical knowledge about the passivity of FONSs. Moreover, an observer-based output passive control is established to ensure that the corresponding closed-loop system is passive by means of LMI technique and matrix singular value decomposition (SVD). Ultimately, the practicality of our yielded results is revealed by two numerical simulations.
COMPUTATIONAL MODEL OF A FRACTIONAL-ORDER CHEMICAL REACTOR SYSTEM AND ITS CONTROL USING ADAPTIVE SLIDING MODE CONTROL
Authors: ALLAHEM ALI , KARTHIKEYAN ANITHA , VARADHARAJAN MANISEKARAN , RAJAGOPAL KARTHIKEYAN
Published: August 2022

Dynamics of chemical reactor systems are found with highly nonlinear behavior. Computational modeling of a fractional-order chemical reactor system and investigating nonlinear dynamical changes and its control are the main focus of this research work. Chaos theory is a blooming fertile field in recent years, which is used widely to quantify nonlinear behaviors such as quasi-oscillations, bi-stability and bifurcation. The work starts from deriving state-space model of the system with first-order differential equations. There are six equilibrium points and the Jacobian matrix is derived for investigating the stability of the equilibrium points. Eigenvalues of each equilibrium point are calculated. Based on the sign of the real part of the eigenvalues and the existence of imaginary part, we found two equilibrium points behave as saddle spirals and the remaining four equilibrium points are saddle nodes. The stability of the system for different parameter values is investigated and presented. The influence of parameters in the system dynamics is discussed and significant parameter values are highlighted for further study. We considered Caputo’s definition for formulating the fractional-order (FO) model of the system based on the advantages highlighted in various literatures. The stable and unstable regions are portrayed with parameter variations. The results clarified that the analysis can be refined using fractional-order treatment of chaotic systems. We proceeded with our investigation towards obtaining different oscillations, particularly chaotic oscillations. The challenges lie in finding the proper fractional order to handle the system. We showed the bifurcation diagram for a range of fractional-order values and clarified the transitions from periodic oscillations to chaotic behavior and period-doubling bifurcations. The phase portraits are presented to show the limit cycle oscillations for fractional-order 0.95, period-doubling during 0.98, and chaotic oscillations for higher values. We proceeded with our investigation with fractional-order as 0.99. Bifurcation plots for parameter variation are obtained. Chaotic regions, periodic oscillations, period-halving and period-doubling are observed and the influences are discussed. We emphasize the intricate properties which are not addressed during the integer-order treatment of the system and nail the importance of fractional-order treatment. An adaptive sliding mode (ASM) controller is derived and implemented to control the system precisely. The effectiveness is shown by providing simulation results of the system with parameter estimation and controlled state time history plots. The work can be extended to verify the simulated results with equivalent electronic circuits.
SOME MEASURES INFORMATION FOR GENERALIZED AND q-GENERALIZED EXTREME VALUES AND ITS PROPERTIES
Authors: ZAID ESRAA OSAMA ABO , ATTWA RASHA ABD EL-WAHAB , RADWAN TAHA
Published: August 2022

Asymmetrical models like the generalized and q-generalized extreme value distributions have been widely used to describe a variety of random events observed in studies including survival, finance, and dependability. The q-analogues, with the extra parameter q, provide for more modelling freedom. In this paper, Shannon entropy, Varentropy and Varexentropy measures are computed in closed form in cases of generalized and q-generalized extreme value distributions. Maximum likelihood estimation method is applied for computing the values of Shannon entropy, Varentropy and Varexentropy measures.
MODIFIED FINITE ELEMENT NUMERICAL METHOD FOR SOLVING CONFORMABLE SPACE-TIME FRACTIONAL NONLINEAR PARTIAL DIFFERENTIAL EQUATIONS
Authors: HADHOUD ADEL RASHAD , ABD ALAAL FAISAL EZZ-ELDEEN , RADWAN TAHA
Published: August 2022

This paper shows how to approximate the solution to a nonlinear conformable space-time fractional partial differential equations. The proposed method is based on the Cubic B-spline polynomials and Galerkin method. Two test problems show that the approach we use to approximate the proposed equation is accurate and efficient. We apply the Von Neumann approach to show that stability requires some conditions.
Improving LiDAR Object Classification Based on PointNet in Noisy Environments
Authors: Lin Shih-Lin , Li Xian-Qing
Published: August 2022

The recognition and detection of 3D point cloud data are important research tools in the field of computer vision, with important applications in many significant fields, such as in unmanned driving, high-precision mapping, and robot-assisted vision. At the same time, with the development of deep learning technology, research on the recognition and detection of 3D point cloud data combined with deep learning technology is receiving more and more attention. One of the main problems with the current self-driving cars is that the detection ability of the optical radar’s echo can be affected by bad weather such as heavy rain, snow, thick smoke, or thick fog. The real signal is attenuated and often very weak or submerged in a large amount of noise, which affects its judgment of the outside environment, meaning that the autonomous vehicle is unable to move. Therefore, it is urgent to solve this problem to improve the accuracy of post-stereoscopic images. This study uses LiDAR to collect point cloud data, and then applies PointNet for deep learning training. Random noise added to the original point cloud data is filtered out with a filter. The accuracy of the original signal state and the signal after filtering the noise is compared. There is an improvement of 60.8% in the method detailed in this study. This method can be widely developed and applied to improve the LiDAR technology in the future.
Feature Clustering of Noisy Data and Application in the Currency Market
Authors: Seidpisheh Mohammad , Babayi Salman , Mohammadpour Adel
Published: August 2022

With the increase in high-dimensional data, researchers pay more attention to dimensionality reduction techniques because there are many noisy, redundant and irrelevant features in high-dimensional data. The existence of noisy features leads to decrease performance when analyzing high-dimensional data. Also, unsupervised dimensionality reduction techniques are widely used due to the lack of available labels. Feature clustering is an unsupervised dimensionality reduction technique to partition features into clusters in which features are strongly related. In addition, the Pearson correlation coefficient is widely used as a similarity tool for feature clustering. However, the Pearson correlation coefficient is easily influenced by outliers and noises, thus leading to misleading results. This paper focuses on the influence of dissimilarity measures on the clustering of noisy features. Heavy-tailed distributions are used for modeling data with outliers and noises. Therefore, we introduce a new dissimilarity measure based on a new dependence coefficient of heavy-tailed distributions. The performance of feature clustering using the proposed dissimilarity is evaluated using ARI and internal criteria on artificial and real currency market datasets. Experiment results have demonstrated the effectiveness of the proposed feature clustering method.
Temporal Analysis of the Flows of the Rivers that form the Hydrographic Basin of Moquegua (Peru)
Authors: Toledo O. C. , da Silva Filho A. M. , Silva A. B. , Zebende G. F.
Published: August 2022

The study of water sources such as rivers and lakes is increasingly important in the modern world, mainly due to their scarcity and the large number of cities flooded by heavy rains. In this paper, we aim to analyze the dynamics of the daily flow of water in the Torata, Tumilaca, and Huaracane rivers, which form the Moquegua watershed (Peru). To study these fluctuations, we apply the DFA method (estimate long-range autocorrelation in non-stationary time series) and the DCCA cross correlation coefficient (which strongly dominates the standard Pearson coefficient in time series analysis) to analyze the flow in the basin of Moquegua. Among the rivers that we analyzed descriptively, we identified greater variability in flows in the Huaracane River and less in the Torata, and in general a seasonal component of approximately one year. With the modeling via DFA, it was possible to identify persistent behavior and also annual seasonality. With the DCCA coefficient (cross correlation), as a function of the time scale, positive values of cross correlation are found between river flows at different levels (weak, medium, strong). With this study, considering the properties of the applied methods, it is possible to predict the oscillations of one river in relation to another, which can help the authorities in the management of freshwater over time.
Modeling of Drying Kinetics of Banana (Musa spp., Musaceae) Slices with the Method of Image Processing and Artificial Neural Networks
Authors: Ozden Semih , Kılıç Faruk
Published: August 2022

In this study, modeling of thin banana slices dried on 316 stainless steel shelves is carried out in an oven working with serial controlled and concentric blower-resistor couple. Changes occurred in banana slices (area and color) during drying process have been recorded by a camera. Additionally, weight has been measured with a load cell which is under the shelf and energy consumption has been measured with electricity consumption meter which is tied to energy input. The main aim of the study is to conduct the drying process of banana slices according to the data obtained from camera. Besides, obtained data have been tested with a powerful modeling technique like Artificial Neural Networks (ANN), and it has been seen that drying process could be modeled according to the data obtained from camera. Energy consumption data have been added in order to increase the performance of ANN and strengthen the modeling. Thus, an automatic drying system that can learn by itself using only a camera without any other sensors will be installed. This has been caused an increase in performance. However, it is obvious that it increases cost. According to the results of modeling process, 99% of “goodness of fit” has been obtained by using the change in banana slices and the number of pixels. It has been found that the developed model performed adequately in predicting the changes of the moisture content. Thus, it has been available to control the food drying process with a digital camera.
Climate Change and Emergency Management
Authors: Houser Ryan Scott
Published: August 2022

The continually worsening threat of the impacts of climate change will have detrimental impacts on the ability of emergency managers to prepare for and respond to various disasters. Emergency management in the climate change era is at the intersection of human interaction and the physical world. Emergency managers must be able to understand the threats and vulnerabilities of the natural hazards that may exist in a community as well how the public will respond to any threats. There are unique collaborations between human, social, and economic vulnerabilities that outline a country's resilience to a disaster. Climate change has the potential to cause devastating consequences for the health, security, and stability of a nation. Emergency preparedness and response officials must consider all the unique needs of their region when engaging in planning and recovery efforts in order to ensure resilience in the face of worsening threat matrices that are a complication of climate change.
Research on the Functional Relationship between Emergency Management and Potential Safety Hazard
Authors: Wang Fei , Yang Yuzhong , Wu Liyun , Peng Lei , Meng Han
Published: August 2022

Since 2018, China has entered a new era of “Great Emergency Management” of all disasters from the traditional single disaster. Accident Safety Management is a part of Emergency Management, the prevention and preparation before safety accidents of Accident Safety Management is a very important tool to comprehensively reduce the probability of safety accidents, which includes the Supervision of Potential Safety Hazards (SPSH). Effective SPSH can greatly reduce the incidence and mortality of safety accidents. From the SPSH before safety accidents, this paper studies the functional relationship between Emergency Management and Potential Safety Hazards (PSH) to provide theoretical guidance for improving the level of Emergency Management in the future.
The Use ofTwitterby Official Institutions in Disaster Risk Communication and Resilience
Authors: Inal Onal E , Tekeli-Yeşil S , Okay N
Published: August 2022

This study aims to explore the use of Twitter by Disaster and Emergency Management Authority (AFAD) in 2021, which is determined as the year of disaster education. Within the scope of this study, the tweets of the AFAD Presidency in the media section between January 1, 2021, and December 31, 2021, were examined. The tweets were categorized considering hazard types (geological, hydrological and climatological, biological, technological accidents and Chemical Biological Radiological Nuclear (CBRN), forest fires, migration, and other) and phases of the disaster management cycle (pre-disaster (mitigation, and preparedness), response, and post-disaster recovery). Five hundred and eighty tweets related to disasters were identified including the number of 88 disaster irrelevant tweets. Most of the tweets were related to hydrological and meteorological hazards. Regarding the biological disaster-induced COVID-19, only two tweets specific to the response process were identified. This study provides an overview of the characteristics and the potential role of social media in risk communication. These institutions can provide the risk information and work closely with the media to reach and share with the community.
Association of Cytokine Gene Polymorphisms with Prostate Cancer Risk from a Study in Central China
Authors: Xu Shun , Hu Yongtao , Zhang Ligang , Yue Shaoyu , Zhang Li , Liang Chaozhao
Published: August 2022

Our study intended to investigate five cytokine gene single nucleotide polymorphisms (SNPs) and their associations with prostate cancer risk. Genotypes of five cytokine gene SNPs were detected by MassARRAY for blood samples from a group of patients with prostate cancer (n = 90) and a control group (n = 140) in central China. The differences in tumor clinical stages, Gleason scores, and PSA values in patients with prostate cancer were also investigated. The frequencies of the five cytokine gene SNPs (L‐1β rs16944, IL‐4 rs2070874, IL‐4rs2227284, IL‐16 rs7175701, and IL‐16 rs11556218) genotypes were not found to be significantly mutated in prostate cancer patients compared with the control group. In addition, for five cytokine gene SNPs genotypic comparisons, patients with different Gleason scores, clinical stages, and PSA values were grouped into two subgroups. There was also no statistically significant association in all these subgroups. Our study suggests that cytokine gene polymorphisms may not be a risk factor for prostate cancer in a central Chinese population. Nevertheless, more large‐scale studies on the Chinese population are necessary to examine our conclusions. The discovery of cytokine gene polymorphisms related to prostate cancer could update our understanding of the etiology and improve our knowledge of the early detection, diagnosis, and treatment of prostate cancer.
Application of PSO Improved Algorithm in Motor Fault Diagnosis Simulation
Authors: Shan Yingjie
Published: August 2022

Aiming at the shortcomings of the traditional fault diagnosis methods of electric motors, the author proposes a method based on the application of improved PSO algorithm in the simulation of motor fault diagnosis. The method optimizes the fault diagnosis method of BP neural network by adopting the adaptive mutation particle swarm algorithm. Firstly, the fault features are extracted from the response signals of the measurable points of the motor to be tested, and wavelet packet decomposition and normalization are performed to construct a sample set; then, the particle swarm improvement algorithm is used to optimize the weights and thresholds of the BP neural network, so as to realize the training and testing of the motor to be tested. In the fault diagnosis of a certain motor, it is found that the fault diagnosis time and diagnosis rate of this method are significantly improved compared with the previous ones, and the diagnosis rate reaches 99% when the center deviation range is 0.3, the efficiency of the fault diagnosis model for parameter optimization through the improved PSO algorithm is higher, and the accuracy of the diagnosis results is further improved.
Application of Face Recognition Technology in Intelligent Education Management in Colleges and Universities
Authors: Xiang Donghong
Published: August 2022

The application of artificial intelligence technology can help colleges and universities effectively improve the efficiency of campus management and teaching quality. The traditional educational management concepts and models in colleges and universities can no longer meet the growing needs of students. In this paper, the application of artificial intelligence technology in intelligent education management in colleges and universities is proposed. The face recognition technology is constructed through the volume neural network model and the hog algorithm. The experimental results show that the face recognition system can meet the real-time requirements of face recognition and improve the accuracy of face recognition. In addition, in the dormitory management application experiment, the face recognition system proposed in this paper has more advantages than the traditional algorithm in recognition accuracy. The face recognition system in this paper can identify the problems existing in class attendance and provides a certain reference value for the classroom on campus.
Construction of 3D Reconstruction System for Building Construction Scenes Based on Deep Learning and IoT
Authors: Wang Lixiang
Published: August 2022

The developing intricacy and extent of building projects, as well as the way that construction schedule management is still mostly done by hand, has resulted in low efficiency in construction schedule management, resulting in cost overruns and legal disputes as a result of schedule delays in many projects. Existing 3D reconstruction algorithms frequently result in large there may be holes, distortions, or hazy regions in remade 3D models, but AI-based 3D remaking strategies regularly reestablish straightforward isolated parts and portray them as 3D boxes. Accordingly, these algorithmic systems are generally not sufficient for certifiable use. The primary objective of this paper is to apply the creation ill-disposed network strategy to 3D recreation works on the nature of the underlying 3D recreation model via preparing a generative ill-disposed network model to a joined state. As solo examples, just recently noticed 2D pictures are required, with no dependence on earlier information on the 3D hidden shape or reference insights. Test results show that this algorithmic structure outflanks present status of-the-workmanship 3D reproduction approaches on an average 3D recreation test set. On the common 3D remaking test set, exploratory outcomes uncover that this algorithmic structure beats the current cutting edge 3D reproduction techniques.
The Effect on Quality of Life after Three-Dimensional Intensity-Modulated Radiation Therapy in Patients with Low-Grade Glioma
Authors: Chen Huili , Rao He , Huang Yong
Published: August 2022

Objective. To investigate the effect of three-dimensional intensity-modulated radiation therapy (IMRT) that accurately target delineation on quality of life (Qol) in patients with low-grade gliomas. Methods. From February 2015 to December 2019, 100 patients with low-grade gliomas were randomly divided into three-dimensional conformal radiotherapy control group (

n
=
50

) and three-dimensional IMRT research group (

n
=
50

). The scores of the Mini-Cog Assessment (Mini-Cog) and Montreal Cognitive Assessment Scale (MoCA), the self-care ability score (BI), and the effect of symptom improvement and the quality of life SF-36 score were compared between the two groups. Results. After radiotherapy, the self-care ability of patients in the two groups was significantly improved, and the improvement of study group was better than that of the control group (

P
<
0.05

). The Mini-Cog and MOCA scores in the study group were significantly higher than those in the control group (

P
<
0.05

). In addition, the symptom improvement effect and quality of life of the patients in the study group were also significantly better than those in the control group (

P
<
0.05

). The scores of SDS and SAS of patients who underwent three-dimensional conformal IMRT were significantly lower than those of the control group. There was no significant difference in mortality between the two groups. Conclusion. Three-dimensional conformal intensity-modulated radiation therapy can delineate the target volume more accurately, regulate the intensity of radiation, and improve the symptoms and quality of life of patients with low-grade gliomas.
Adaptive Recommendation Method of IoT Apps and Ideological and Political Teaching Resources
Authors: Hu Yanhua
Published: August 2022

In view of the current poor nature of online ideological and political teaching and the deficient impact of the executive teaching resource recommendation, this paper advances the examination on the versatile recommendation technique for online ideological and political teaching resources under the school enterprise cooperation mode, gathers and deals with the ideological and political teaching data in view of the teaching qualities of the school enterprise cooperation mode, and develops the assessment calculation of teaching data the board. At last, through tests, it is affirmed that the versatile recommendation technique for online ideological and political teaching resources under the school enterprise cooperation mode has high practicability and fully meets the research requirements.
Evaluation of Zn Adenine-Based Bio-MOF for Efficient Remediation of Different Types of Dyes
Authors: Salama Eslam , Hamdy Ali , Hassan Hassan S. , Amer Wael A. , Ebeid El-Zeiny M. , Ossman Mona , Elkady Marwa F.
Published: August 2022

As an eco-friendly material, Zn-adeninate bio-metal-organic framework (bio-MOF) was investigated as an efficient adsorbent for both anionic and cationic dyes. The adsorption capability of the synthesized Zn-adeninate bio-MOF was confirmed by its notable surface area of 52.62 m2 g−1 and total pore volume of 0.183 cm3 g−1. The bio-MOF adsorption profiles of anionic direct red 81 (DR-81) and cationic methylene blue (MB) dyes were investigated under different operating parameters. The optimum dosages of Zn-adeninate bio-MOF were 0.5 g L−1 and 1 g L−1 for MB and DR-81 decolorization, respectively. The pHPZC of Zn-adeninate bio-MOF was 7.2, and maximum monolayer adsorption capacity was 132.15 mg g–1 for MB, which decreased to 82.54 mg g–1 for DR-81 dye. Thermodynamic data indicated the spontaneous and endothermic nature of the decolorization processes. Additionally, the adsorption processes were in agreement with the Langmuir and pseudo-second-order kinetic models. The synthesized Zn-adeninate bio-MOF could be reused several times with high decolorization ability. These findings demonstrated that the synthesized Zn bio-MOF is an effective and promising adsorbent material for the removal of both cationic and anionic dyes from polluted water.
Differential Characteristics and the Main Controlling Factors of Shale Oil Sweet Spot Reservoirs in Lucaogou Formation, Jimsar Sag, Junggar Basin
Authors: Wang Jingmin , Han Denglin , Deng Yuan , Lin Wei , Su Ao , Wang Chenchen , Zhang Jizhen , Zhang Juan
Published: August 2022

The microscopic differences in characteristics and formation mechanism of shale oil reservoirs in the upper and lower sweet spot sections of the Lucaogou Formation in the Jimsar Depression, which has been identified as a national shale oil demonstration area in China, are still unclear. In this study, the characteristics and the main controlling factors of reservoir differences in different sweet spots of Lucaogou Formation were specified based on core observation, thin-section observation, X-ray diffraction, Rock-Eval, microscopic fluorescence of hydrocarbon inclusions, and temperature measurement of saline inclusions. Results show that the Lucaogou Formation mainly develops dissolution and primary intergranular pores. The dissolution transformation leads to obvious differences between the upper and lower sweet spots. Specifically, the upper sweet spot section mainly develops primary intergranular pores and partially develops dissolution pores; the lower sweet spot section mainly develops dissolution pores, including intergranular, intragrain, and intergranular pores. Geochemical data such as inclusions indicate that hydrocarbon generation began in the Triassic, and a large number of hydrocarbons were charged in the Middle-Late Jurassic-Early Cretaceous. As the key fluid that triggers reservoir dissolution modification, it is mainly derived from organic acids generated by thermal evolution of source rocks within shale formations. The scale and quality of source rocks in the lower sweet spot are better than those in the upper sweet spot. The former has stronger hydrocarbon generation potential, which lays a foundation for the scale difference of organic acid output in the upper and lower sweet spots. At the same time, the source rocks in the lower sweet spot are more mature due to magmatic-hydrothermal upwelling. This condition accelerates the release of organic acids from source rocks, which results in the scale difference of dissolution effects in the upper and lower sweet spots.
Internet Financial Risk Model Evaluation and Control Decision Based on Big Data
Authors: Chen Liancheng , Jiang Rong
Published: August 2022

Internet finance is the application of advanced information technology to traditional finance. Internet finance is accelerating its growth, and its performance is most obvious in the financial market. The Internet financial reduces costs of traditional financial, which makes it more civilian. The unstable factors of Internet finance, such as regulation, credit reporting, and network security, lead to a gradual increase in risks. The current Internet financial risk model is slow to deal with risks and cannot solve the financial risks that arise in time to ensure the safety of the platform. In order to solve this problem, the big data technology was applied to the Internet financial risk model to evaluate and control financial risks. The default rate, rate of return, risk control time, model performance score, and other aspects of the Internet financial risk model using big data were tested. It is found that by applying big data technology to the Internet financial risk model, the customer default rate decreased by 6.14%, the yield increased by 7.6%, the time to deal with risks was reduced by 0.46 minutes, and the model performance score was improved by 0.796 points. Big data technology can effectively control and avoid Internet financial risks and help investors avoid risks.
Evaluation Method of College Students’ Education Management Quality Based on Collaborative Filtering Algorithm and IoT Apps
Authors: Tang Lin
Published: August 2022

Considering the ongoing unfortunate evaluation impact of College Students’ education management quality, this paper advances an undergrad’ education management quality evaluation technique in light of collaborative filtering algorithm, gathers the impact indicators of College Students’ education management quality, and builds an understudies’ education management quality evaluation record framework joined with collaborative filtering algorithm. At long last, it is affirmed by tests that the quality evaluation technique for College Students’ Education Management Based on collaborative filtering algorithm has high precision and practicability during the time spent down to earth application, which gives reference and help for college education management.
Research of Crack Defect Detection in Metal Pipes Based on Microwave Antenna Array
Authors: Qiu Guohua , Tian Shanshan , Yuan Qinwen
Published: August 2022

This study evaluates the feasibility of using antenna array to detect crack defects in metal pipes. Antenna arrays are set at the port of a metal pipe in radial direction, and the microwave signal can be effectively coupled into the metal pipe. It can produce orbital angular momentum (OAM) waves. The cracks in the pipe will change the microwave transmission characteristics, and they can be inspected by time domain reflectometry (TDR) of vector network analyzer (VNA). By studying the transmission characteristics of current on the inner surface of the metal pipe, the feasibility of linearly polarized TE11 mode microwaves for crack inspection was preliminarily verified. Three galvanized metal pipes with an inner diameter of 8 cm and a total length of about 270 cm were used in the experiment. Axial slits and circumferential slits were used to simulate the crack, respectively. The slits penetrated the pipe wall with a breach of approximately

10
 
cm
×
0.7
 
cm

. The experimental results demonstrated that the radial direction antenna array can detect both the axial slit and circumferential slit through TDR and standing wave ratio (SWR) at the port, especially effective for the axial slit. It provides a new inspection method for metal pipe defect evaluation.
Description of four new species of Lepidotrigona (Hymenoptera: Apidae: Meliponini) from north-east India
Authors: VIRAKTAMATH SHASHIDHAR , THANGJAM ROJEET
Published: August 2022

We describe Lepidotrigona thenzawlensis sp. n., L. rajithae sp. n., L. amruthae sp. n. all from Thenzawl, Mizoram and L. sikkimensis sp. n. from Mamley, Sikkim with associated female and male bees and with a brief note on the nest structure of the former three species. These new species belong to the ventralis species group with body and forewing lengths less than 5 mm in females. These four species are different from the holotype of L. arcifera (from the ventralis group), the only known species from India, in morphometry and ratio of interocellar to ocellocular distance, scape length to eye length, hind tibial length to forewing diagonal length, and hind basitarsus width to hind tibial width are greater than those in L. arcifera. The new species also differ from other species of the ventralis group (L. arcifera, L. flavibasis, L. ventralis, L. satun and L. doipaensis) of the Indo-Malayan region in morphometry, pilosity, structure of male metasomal sterna and male genitalia. Each new species is distinct and can be differentiated from each other based on the structure of male metasomal sterna 4, 5 and 6 as well as genitalia. The brood cells in L. thenzawlensis and L. rajithae were arranged in single-cell thick multi-layered combs. The discovery of these four new species increases the number of species of the genus Lepidotrigona from one to five from India.
A new genus and species of Apseudidae, and a new species of Bunakenia (Crustacea: Tanaidacea: Apseudomorpha) from the Northwest Atlantic and Gulf of Mexico
Authors: DRUMM DAVID T. , HEARD RICHARD W.
Published: August 2022

Examination of material from the Campeche region of the southern Gulf of Mexico revealed the presence of a new genus and species of Apseudidae that appears to be transitional between Bunakenia Guţu and Apseudes Leach sensu lato. This new taxon, Pseudobunakenia anablesis n. gen., n. sp. is found throughout the Gulf of Mexico (GOM) and Northwest Atlantic as far north as South Carolina. It is known in the literature under the designation “Apseudes spinosa” Sars sensu Dawson and “Apseudes sp. A” (Heard et al.). Also, Bunakenia hamata n. sp. is described from offshore Georgia and is distributed from the Florida Gulf Coast and the Northwest Atlantic as far north as South Carolina. It is known in the literature under the designation “Bunakenia sp. A” (Heard et al.) and is the only known species of that genus in the GOM/NW Atlantic. It can be distinguished from its congeners by a combination of characters such as the pereonites having posterolateral apophyses, the antennule first peduncle article denticulate, the antennule accessory flagellum having five articles, and the first pereopod having four ventral propodal spiniform setae. A key to the known species is presented.
Appearances often deceive in racerunners: integrative approach reveals two new species of Eremias (Squamata: Lacertidae) from Pakistan
Authors: MASROOR RAFAQAT , KHAN MUAZZAM ALI , NADEEM MUHAMMAD SAJID , AMIR SHABIR ALI , KHISROON MUHAMMAD , JABLONSKI DANIEL
Published: August 2022

Based on newly provided morphological and previously published genetic data, we describe two new distinctive sympatric lacertid lizards of the genus Eremias (subgenus Aspidorhinus) from the arid mountains of northwestern Balochistan Province, Pakistan. The new species, Eremias killasaifullahi sp. nov. and Eremias rafiqi sp. nov. are distinguished from all other species of the subgenus Aspidorhinus (E. afghanistanica, E. fahimii, E. isfahanica, E. kopetdaghica, E. lalezharica, E. montana, E. nikolskii, E. papenfussi, E. persica, E. regeli, E. roborowskii, E. strauchi, E. suphani, and E. velox) by unique morphological characters and genetic differentiation. In the molecular phylogeny of Aspidorhinus, both new taxa are well-supported lineages differentiated from other species of this subgenus by uncorrected p distances from 8.5% to 21.6%, respectively. Both new species belong to E. persica complex where E. rafiqi sp. nov. is partly similar in dorsal color pattern to E. persica but can be distinguished from this species by unique meristic and morphometric characters. Eremias rafiqi sp. nov. is found in Pakistan, Afghanistan, and eastern Iran. Eremias killasaifullahi sp. nov. can be differentiated from E. persica by its distant distribution, dorsal color and pattern, smaller size, and less number of gulars and ventral scales. Eremias killasaifullahi sp. nov. is only known from the type locality and represents the local microendemism, along with other endemic species of reptiles reported from this part of Pakistan. We, however, expect that E. killasaifullahi sp. nov. could have a broader range in northwestern Pakistan and southeastern Afghanistan, which should be an object of following investigations. Our data show that remote areas between Hindu Kush Mountains and Indus River need attention as they most probably represent possible sources of genetic and species diversity in the region.
Two new species of Demicryptochironomus Lenz, 1941 from India with tentative phylogenetic relationship and a revised world key to known males (Diptera: Chironomidae)
Authors: MUKHERJEE BINDARIKA , HAZRA NILADRI
Published: August 2022

Demicryptochironomus (s. str.) praeacutus sp. n. and D. (Irmakia) dividuus sp. n. are described based on adult males from India. A revised world key to the known males of the genus and molecular barcodes of both species are provided. A tentative phylogenetic relationship based on morphological characters of adult males of the genus Demicryptochironomus Lenz is also proposed.
Two new species of the genus Microleon (Lepidoptera: Limacodidae) from China
Authors: LIANG JIAMIN , SOLOVYEV ALEXEY V. , WANG HOUSHUAI
Published: August 2022

Two new species of the genus Microleon Butler, 1885, Microleon dianensis sp. nov. from Yunnan Province, China and Microleon simingensis sp. nov. from Zhejiang and Sichuan Provinces, China are described. Photographs of adults and male genitalia of these new species are provided, with a key to all currently known species of Microleon. The validity of new species is well supported by the molecular analysis of the fragment of mitochondrial cytochrome c oxidase subunit I (COI).
Prognostic Nutritional Index Predicts Contrast-Induced Nephropathy in Patients with Acute Coronary Syndrome
Authors: Yuksel Yasin , Kose Sennur
Published: August 2022

This study evaluated the effectiveness of prognostic nutritional index (PNI) in predicting contrast induced nephropathy (CIN) in patients with acute coronary syndrome (ACS). This study included 925 ACS patients (mean age 62.5 ± 12.4 years, 73.5% male); 604 were diagnosed as unstable angina pectoris/non–ST-elevation myocardial infarction (USAP/NSTEMI) and 321 as ST-elevation myocardial infarction (STEMI). The PNI formula was: 10 × serum albumin (g/dL) + .005 × total lymphocyte count (/mm3). The patients were divided into two groups: CIN (n = 232) and non-CIN (n = 693). Patients without CIN had a significantly lower PNI than patients with CIN (44.3 ± 6.9 vs 54.7 ± 7.4; P < .001). In the receiver operating characteristic (ROC) curve analysis, the cut-off value for PNI of 48.6 has 80% specificity and 81% sensitivity in predicting CIN (area under the ROC curve (AUC): .87, 95% CI [.84–.89]). PNI <48.6 (odds ratio (OR): 6.765, P < .001), pre-procedural creatinine levels (OR: 6.223, P < .001), left ventricular ejection fraction (LVEF) (OR: .960, P < .001), age (OR: 1.025, P = .005), diabetes mellitus (DM) (0R: 1.768, P = .006), contrast amount (OR: 1.003, P = .038), and having STEMI (OR: .594, P = .029) were found independently associated with CIN. PNI is a strong independent predictor of CIN in ACS patients.
Risk Factors for Carotid Restenosis in Patients After Eversion Endarterectomy vs Stenting: A Single-Center Experience
Authors: Petrovic Jovan , Ilijevski Nenad , Sagic Dragan , Antonic Zelimir , Tanaskovic Slobodan
Published: August 2022

The primary aim of the presented study is to analyze and compare the rate of carotid restenosis in patients after eversion carotid endarterectomy (eCEA), primary carotid angioplasty and stenting (CASp), and stenting for carotid artery restenosis after previous eCEA (CASr). The secondary aim is to compare clinical outcomes in patients with carotid restenosis. The total number of patients with evident carotid restenosis was 223 (24.8%). In patients with eCEA, significant carotid restenosis rate was 12.7%, in the CASp group 18.7%, and CASr 6.7%. Patients with carotid restenosis were asymptomatic in 95.1% of cases. Patients in the CASp group experienced transient ischemic attack more than patients with eCEA ( P = .007), while no difference was observed regarding cerebrovascular insult (CVI). The incidence of carotid restenosis was higher in CASp patients, and increased during the follow-up. The majority of patients are asymptomatic post-procedural and the degree of carotid restenosis does not correlate with the occurrence of postoperative symptoms. High low-density lipoprotein cholesterol (LDL-C) levels, low high-density lipoprotein cholesterol (HDL-C) levels, smoking, and a history of vascular surgery correlate with higher degrees of carotid restenosis. The most important factor in the prevention of carotid restenosis is risk factor control as well as adequate pharmacological therapy.
Clinical Efficacy of Percutaneous Vegetectomy in Tricuspid and Right-Heart Indwelling Device Infective Endocarditis
Authors: Scantland Joshua , Hendrix Justin , Schmitz Adam , Casciani Thomas , Butty Sabah
Published: August 2022

Several studies have analyzed the efficacy of AngioVac for percutaneous intracardiac vegetectomy, but impact on surgical candidacy or clinical efficacy for infectious endocarditis (IE) is currently unknown. This is a single-arm, retrospective study on IE vegetectomy with impact on surgical risk scores. Analysis included 32 patients who underwent AngioVac vegetectomy for right heart IE at a single institution. The primary endpoint was improvement in the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) scores. Secondary endpoints included technical success, improved leukocytosis, procedural safety, 30-day mortality, and 60-day mortality. Findings demonstrate 90.6% (n = 29) technically successful debulking. There was improvement in mean NSQIP scores from 34.6 to 27.9 ( P = .007). Zero cases of 30-day all-cause mortality. One patient experienced a major post-procedural complication of pneumothorax, a Class D Adverse Event. 20.5% (n = 5) of valvular vegetation patients went on to have surgical tricuspid valve repair. All indwelling intracardiac devices were removed. Findings suggest that percutaneous vegetectomy improves surgical candidacy, as measured by ACS NSQIP scores, in patients with IE and right heart vegetations and is associated with low complication rates.
Exposure to Long-Term Air Pollution and Incidence of Peripheral Arterial Disease in the General Population: A Korean National Population-Based Retrospective Cohort Study
Authors: Gwon Jun Gyo , Park Ji Hun , Kim Joung Soo , Seo Hyun-Min
Published: August 2022

This study aimed to evaluate the causal relationship between long-term outdoor air pollutants and incidence of peripheral arterial disease (PAD) using the Korean National Health Insurance Service-National Sample Cohort (NHIS-NSC) database. We included 292,091 subjects from the general population who had previously not been diagnosed with PAD by the NHIS-NSC between 2008 and 2014. Hourly air pollutant data (particulate and gaseous) and climate data were collected. Correlation analysis of the collected data confirmed the relationship between air pollution and PAD incidence. For 1,836,965.4 person-years, incident cases of PAD were observed in 5243 subjects (285.4/100,000 person-years). In the Cox proportional hazard analysis, exposure to long-term average concentration of sulfur dioxide (SO2) [hazard ratio (HR), 1.686; (95% confidence interval (CI), 1.108–2.565) for .01ppm] and nitrogen dioxide (NO2) [HR, 1.200; (95% CI, 1.077–1.336) for .01 ppm] significantly increased the risk of PAD occurrence after the adjustment for several variables. This study demonstrated that SO2 and NO2 exposure are independent predictors of PAD.
The use of the term ‘occupational profile’ in occupational therapy and occupational science literature: A scoping review
Authors: Hansell Chloe , Bissett Michelle , Caine Anne-Maree
Published: August 2022

Introduction

The term ‘occupational profile’ is widely used within the occupational therapy profession; however, its use and application appear inconsistent in the literature. Understanding how occupational profile is described in existing literature can reduce ambiguity and strengthen consistent use of terminology across practice and research.

Methods

A scoping review was conducted to examine how occupational profile has been described in occupational therapy and occupational science literature.

Results

Seventy-six journal papers were included. A lack of consistent definitions, conceptualisation and measurements was identified. Key concepts relating to the conceptualisation of occupational profile included occupational history, motivation and performance. Only one measurement was used consistently with paediatric clients to identify individuals’ occupational profiles. Occupational profiles of populations and communities were not identified.

Conclusion

The lack of consistency in definitions, conceptualisation and measurement of the term ‘occupational profile’ presents significant issues for occupational therapy practice, including an inability to compare populations. Researchers should articulate their conceptualisation of occupational profile in the absence of a universally agreed-upon definition. More comprehensive measures seeking to explore the occupational profile of a variety of clients need to be developed. Occupational profiles of communities and populations should be explored to understand occupational patterns and identify potential occupational issues.
Small cell lung cancer with relapsing polychondritis: A report of one case and the review of literature
Authors: Liu Yuan , Wang Ning , Xu Jian , Bi Ying , Han Xue , Dai Meng , Liu Chunfang
Published: August 2022

The present study reports the clinical data of a patient with small cell lung cancer who developed relapsing polychondritis. We report a case of a 57-year-old female presented with cough, expectoration, and fever. A Computed Tomography (CT) scan performed at the hospital revealed diffuse thickening of bronchial walls in both lungs. Bronchoscopy revealed that the tracheal mucosa was thickened, narrowed, and collapsed, and the bronchoscope could pass through. The bronchial mucosa on both sides was thickened and edematous, the surface was rough, each bronchus was narrow, and the intervertebral ridges were widened. Needle biopsy: considering small cell carcinoma in combination with immunohistochemical results. Her symptom was not improved after anti-infective therapy. The left auricle was red and swollen, the auricle collapsed, and the left eye had subconjunctival hemorrhage during her hospitalization without obvious cause. After multidisciplinary consultation, pulmonary small cell lung cancer cT0N2Mx rumen lymph node metastasis and RP were considered. Treatment: Prednisone, orally for RP. Chemotherapy combined with radiotherapy was given for small cell lung cancer. The chemotherapy regimen was carboplatin combined with etoposide. The patient has already been followed for 1 year after receiving chemoradiotherapy; the condition of the patient is stable at present. Based on the case of our patient, for cases of RP with symptoms such as auricle chondritis, ocular inflammatory disease, and nasal chondritis, we should pay great attention to whether the case is caused by lung cancer with relapsing polychondritis. Because of the rarity of the disease, the clinician should improve the recognition of the disease in order to strive for early diagnosis and therapy.