bluuebunny/crossref_metadata_2025 huggingface dataset:
Perioperative Protocol of Ankle Fracture and Distal Radius Fracture Based on Enhanced Recovery after Surgery Program: A Multicenter Prospective Clinical Controlled study
Authors: Li Ting , Sun Zhi-Jian , Zhou Yan , Sun Wei-Tong , Wang Peng-Cheng , Cai Xin-Yu , Liang Jun-Bo , Dong Jing-Ming , Zhou Da-Peng , Yu Kai , Wu Ming-Xin , He Jiu-Sheng , Wen Liang-Yuan , Yu Bao-Qing , Wang Jian , Yang Jun , Lin Feng-Fei , Li Bing-Zuan , Shi Zong-Xin , Wang Bao-Jun , Wang Ai-Guo , Peng Gui-Ling , Sun Xu , Xiao Hong-Hao , Mi Meng , Zhao Xia , Li Chang-Run , Liu Gang , Li Shao-Liang , Gu Hang-Yu , Zhou Yuan , Tan Zhe-Lun , Wu Xin-Bao
Published: June 2022

Background. The enhanced recovery after surgery (ERAS) program is aimed to shorten patients’ recovery process and improve clinical outcomes. This study aimed to compare the outcomes between the ERAS program and the traditional pathway among patients with ankle fracture and distal radius fracture. Methods. This is a multicenter prospective clinical controlled study consisting of 323 consecutive adults with ankle fracture from 12 centers and 323 consecutive adults with distal radial fracture from 13 centers scheduled for open reduction and internal fixation between January 2017 and December 2018. According to the perioperative protocol, patients were divided into two groups: the ERAS group and the traditional group. The primary outcome was the patients’ satisfaction of the whole treatment on discharge and at 6 months postoperatively. The secondary outcomes include delapsed time between admission and surgery, length of hospital stay, postoperative complications, functional score, and the MOS item short form health survey-36. Results. Data describing 772 patients with ankle fracture and 658 patients with distal radius fracture were collected, of which 323 patients with ankle fracture and 323 patients with distal radial fracture were included for analysis. The patients in the ERAS group showed higher satisfaction levels on discharge and at 6 months postoperatively than in the traditional group (

P
<
0.001

). In the subgroup analysis, patients with distal radial fracture in the ERAS group were more satisfied with the treatment (

P
=
0.001

). Furthermore, patients with ankle fracture had less time in bed (

P
<
0.001

) and shorter hospital stay (

P
<
0.001

) and patients with distal radial fracture received surgery quickly after being admitted into the ward in the ERAS group than in the traditional group (

P
=
0.001

). Conclusions. Perioperative protocol based on the ERAS program was associated with high satisfaction levels, less time in bed, and short hospital stay without increased complication rate and decreased functional outcomes.
Estimation of Copper and Cadmium Bioavailability in Contaminated Soil Remediated by Different Plants and Micron Hydroxyapatite
Authors: Xu Lei , Xing Xiangyu , Peng Jianbiao , Ji Mingfei
Published: June 2022

A three‐year in situ remediation experiment was carried out to understand the effect of combined phytoremediation with chemical materials on the bioavailability of heavy metals in soil. Indigenous weed (Setaria pumila), energy plant (Pennisetum sp.), cadmium (Cd)‐hyperaccumulator (Sedum plumbizincicola), and copper (Cu)‐tolerant plant (Elsholtzia splendens) were used as the phytoremediation plants aided by micron hydroxyapatite (1% wt). The bioavailability of Cu and Cd in soil was evaluated during the three years. The results showed that the four plants combined with micron hydroxyapatite significantly increased soil pH and soil organic carbon (SOC), and decreased Cu and Cd fractions extracted by CaCl2 and diffusive gradients in thin films (DGT) than the untreated soils, respectively. Because of the large biomass, the accumulation of Cu and Cd is the largest in Pennisetum sp. followed by Elsholtzia splendens, Sedum plumbizincicola, and Setaria pumila. The bioavailability of Cu and Cd is significantly negatively correlated with pH, soil organic carbon, available phosphorus, and available potassium. Moreover, the correlation is mainly related to the addition of micron hydroxyapatite. The accumulation of Cu and Cd is the combined action of the soil bioavailability of Cu, Cd, and biomass. Our results suggest that Pennisetum sp. can act as an appropriate remediation plant for phytoremediation aided by amendments.
Vision-Based Mobile Manipulator for Handling and Transportation of Supermarket Products
Authors: Zia Ur Rahman Muhammad , Usman Muhammad , Farea Adhban , Ahmad Nasir , Mahmood Imran , Imran Muhammad
Published: June 2022

Robot manipulators are growing more widely employed in the retail market, mostly for warehousing, but automating them in-store logistics processes is still a difficult task. Supermarkets and large retail stores face many challenges: shortages, handling, and placement of a single product on shelves. Various issues needed to be considered to develop a robot which can manipulate products of different sizes, shapes, and weight in limited spaces on shelves. The aim of this article is to design and develop a system to address the issues of shortage, identification, moving, and placements of products in supermarkets by properly incorporating database, camera vision, and line following mobile manipulator. A four-wheeled differential drive mobile robot was designed and developed which has a 5 DOF robotic manipulator on it. The line following technique is used to move it around the warehouse. The barcode recognition technique for the localization of product sections and object detection using SIFT is successfully and efficiently employed. The demonstration of the usefulness of the method was shown by carrying out experiments in a relevant environment which imitates a real supermarket.
Longitudinal Changes of Axial Length and Associated Factors in Congenital Ectopia Lentis Patients
Authors: He Jingxin , Lian Zhangkai , Cao Qianzhong , Liu Zhenzhen , Young Charlotte Aimee , Zhang Xinyu , Zheng Danying , Jin Guangming
Published: June 2022

Purpose. To investigate the longitudinal changes and associated factors of axial length (AL) in congenital ectopia lentis (CEL) patients. Methods. In this retrospective study, medical records of CEL patients were reviewed from January 2014 to December 2019 at the Zhongshan Ophthalmic (ZOC) in China. Patients were divided into the surgery group and the nonsurgery group. Data of refractive power, best-corrected visual acuity (BCVA), and intraocular pressure (IOP) as well as ocular biometrics including AL, corneal curvature, white-to-white (WTW), and central corneal thickness (CCT) were collected at baseline and each follow-up visit. Multiple linear regression was performed to assess the potential associated factors for axial length growth in congenital ectopia lentis patients. Results. Compared with the nonsurgery group, the change rate of AL among children aged 3 to 6 years old was slower in the surgery group (0.443 ± 0.340 mm/year vs. 0.278 ± 0.227 mm/year,

P
<
0.05

). However, no statistically significant difference for the change rate of AL was detected between the surgery group and the nonsurgery group (

P
>
0.05

) among patients aged 7 years or older. For the surgery group, the results of the linear regression model showed that a higher change rate of AL was associated with younger age (older age: β = −0.009, 95% CI: −0.014 to −0.003, and

P
=
0.002

) and worse baseline BCVA (logMAR) (β = 0.256, 95% CI: 0.072 to 0.439, and

P
=
0.007

). As for the nonsurgery group, younger baseline age (older age: β = −0.027, 95% CI: −0.048 to −0.007, and

P
=
0.01

) and longer baseline AL (β = 0.073, 95% CI: 0.023 to 0.122, and

P
=
0.006

) were associated with a higher change rate of AL. Conclusions. The AL change rate was clearly associated with age both in the surgery group and in the nonsurgery group. Intervention strategies such as surgery should be performed earlier for CEL that meets the surgical criteria. Worse baseline BCVA and longer baseline AL are associated factors that would affect the growth rate of AL in the surgery and nonsurgery group, respectively.
Balanced Allocation Method of Physical Education Distance Education Resources Based on Linear Prediction
Authors: Ren Hui , Sohail Mishal
Published: June 2022

It is simple to manufacture resource fragments, waste resources, and alter the matching impact of resource performance using the balanced allocation technique of sports distance education resources. Linear prediction is used to offer a way for distributing sports distant education resources in an equitable manner. Using linear prediction, the resource demand can be calculated, and the matching model between virtual and real resources may be constructed using the performance vectors of virtual machines and servers. The balanced allocation approach for sports distance education resources was created with the goal of lowering server count, enhancing resource utilization, and balancing the use of various resources. The balanced allocation outcome is the output Pareto optimal solution set. Its average resource performance matching distance is 765, which is 284 and 465 less than that calculated using the BF and RR algorithms for 1000 virtual machines, respectively. Therefore, in terms of matching resource performance and reducing resource fragmentation, this strategy surpasses the other two.
Detecting Digital Watermarking Image Attacks Using a Convolution Neural Network Approach
Authors: Alzahrani Ali
Published: June 2022

In scientific research, one of the most significant problems of recent years has been and continues to be the protection of digital material. The advancement of Internet technology has allowed for the illicit duplication, authentication, and distribution of digital material by unauthorized individuals. For this reason, a variety of watermarking systems have been investigated for a variety of purposes, including broadcast monitoring, intellectual property protection, content authentication, and copy control. There are various types of the watermarking image attacks that impact the quality of the images; therefore, it is critical to ensure that watermarked digital images can withstand these kinds of attacks. Hence, novelty of the proposed research is to develop approaches to detect these attacks which becomes very important to guarantee a sufficient quality of watermarking images. In this paper, a deep learning method based on a convolution neural network (CNN) algorithm was proposed to detect various types of watermarking attacks, namely, median filter, Gaussian filter, salt-and-pepper, average filter, motion blur, and no attack, to improve the watermarking quality. Evaluation metrics such as peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and the normalization correlation (NC) were employed to examine the invisibility and robustness of the watermarking images. The empirical results of the CNN model show good performance for detecting watermarking attacks with different sizes (256, 128, and 64). The accuracy percentage of the testing process was 98%. A highly efficient CNN approach was developed. Very high performance of NC was found in the detection of the salt-and-pepper attack (99.02%, 99.97%, and 99.49% with respect to watermarking image sizes of 256 × 256, 128 × 128, and 64 × 64, respectively). The study concludes that the CNN model is able to detect watermarking attacks successfully.
Calculating Crossing Numbers of Graphs Using Combinatorial Principles
Authors: Su Zhenhua
Published: June 2022

The crossing numbers of graphs were started from Turán’s brick factory problem (TBFP). Because of its wide range of applications, it has been used in computer networks, electrical circuits, and biological engineering. Recently, many experts began to pay much attention to the crossing number of

G
\
e

, which obtained from graph

G

by deleting an edge

e

. In this paper, by using some combinatorial skills, we determine the exact value of crossing numbers of

K

1,4
,
n

\
e

and

K

2,3
,
n

\
e

. These results are an in-depth work of TBFP, which will be beneficial to the further study of crossing numbers and its applications.
Identification of a Genomic Instability-Related Long Noncoding RNA Prognostic Model in Colorectal Cancer Based on Bioinformatic Analysis
Authors: Liang Yu , Sun Hong-Xu , Ma Bin , Meng Qing-Kai
Published: June 2022

Background. In recent years, a growing body of research has revealed that long noncoding RNAs (lncRNAs) participate in regulating genomic instability. Materials and Methods. We obtained RNA expression profiles, somatic mutation profiles, clinical information, and pathological features of colorectal cancer (CRC) from The Cancer Genome Atlas project. We divided the cohort into two groups based on mutation frequency and identified genomic instability-related lncRNAs (GI-lncRNAs) using R software. We further analyzed the function of identified GI-lncRNAs and established a prognostic model through Cox regression. Using the established prognostic model, we divided the cohort into the high- and low-risk groups and further verified the prognostic differences between the two groups as well as the predictive power of prognosis-related lncRNAs in the genomic instability of CRC. Results. We identified a total of 143 GI-lncRNAs that were differentially expressed between the higher mutation frequency group and the lower mutation frequency group. According to Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analyses, a series of cancer-associated terms were enriched. We further constructed a prognostic model that included five GI-lncRNAs (lncRNA PTPRD-AS1, lncRNA AC009237.14, lncRNA LINC00543, lncRNA AP003555.1, and lncRNA AL109615.3). We confirmed that the expression of the five GI-lncRNAs was associated with prognosis and the mutation of critical genes in the CRC patient cohort. Conclusions. The present research further confirmed the vital function of GI-lncRNAs in the genomic instability of CRC. The five GI-lncRNAs identified in our study are potential biomarkers and need to be studied in more depth.
A Framework to Predict the Molecular Classification and Prognosis of Breast Cancer Patients and Characterize the Landscape of Immune Cell Infiltration
Authors: Zheng Kun , Luo Zhiyong , Zhou Yilu , Zhang Lili , Wang Yali , Chen Xiuqiong , Yao Shuo , Xiong Huihua , Yuan Xianglin , Zou Yanmei , Wang Yihua , Xiong Hua
Published: June 2022

It is known that all current cancer therapies can only benefit a limited proportion of patients; thus, molecular classification and prognosis evaluation are critical for correctly classifying breast cancer patients and selecting the best treatment strategy. These processes usually involve the disclosure of molecular information like mutation, expression, and immune microenvironment of a breast cancer patient, which are not been fully studied until now. Therefore, there is an urgent clinical need to identify potential markers to enhance molecular classification, precision prognosis, and therapy stratification for breast cancer patients. In this study, we explored the gene expression profiles of 1,721 breast cancer patients through CIBERSORT and ESTIMATE algorithms; then, we obtained a comprehensive intratumoral immune landscape. The immune cell infiltration (ICI) patterns of breast cancer were classified into 3 separate subtypes according to the infiltration levels of 22 immune cells. The differentially expressed genes between these subtypes were further identified, and ICI scores were calculated to assess the immune landscape of BRCA patients. Importantly, we demonstrated that ICI scores correlate with patients’ survival, tumor mutation burden, neoantigens, and sensitivity to specific drugs. Based on these ICI scores, we were able to predict the prognosis of patients and their response to immunotherapy. Together, these findings provide a realistic scenario to stratify breast cancer patients for precision medicine.
Application of Temperature Compensation Combined with Neural Network in Infrared Gas Sensor
Authors: Dong Kangning , Yang Jinfang
Published: June 2022

Due to the state of the gas to be measured, the detection mechanism of the pyroelectric detector and the temperature drift of the peripheral circuit components and the detection of the ambient temperature will interfere with the measurement accuracy of the nondispersive infrared gas sensor from many aspects. This paper proposes a temperature compensation method based on the BP neural network. The compensation function of the gas sensor is realized by programming the various functional parameters in the neural network through the program provided in the Matlab neural network toolbox. Experimental simulation results show that the proposed method effectively reduces the influence of external temperature on the gas sensor output and improves its accuracy and stability.
Application of Fuzzy Immune Algorithm and Soft Computing in the Design of 2‐DOF PID Controller
Authors: Ding Ning , Prabhakar Priti , Khosla Anita , Jagota Vishal , Ramirez-Asis Edwin , Singh Bhupesh Kumar
Published: June 2022

To solve the difficulty in selecting the crossover probability and mutation probability in genetic algorithms, a fuzzy immune algorithm based on adaptive estimation of crossover probability and mutation probability in a fuzzy reasoning system is proposed, and it is used in the parameter optimization design of a two‐degree‐of‐freedom PID controller. According to the experiment and simulation results, classic genetic algorithm evolution tends to halt after 37 generations, with a fitness value of 7.135, whereas fuzzy genetic algorithm evolution tends to stop after 20 generations, with a fitness value of 7.486. The 2‐DOF PID controller that was created can give the system strong target value following and interference suppression features at the same time.
Fast Target Detection Algorithm Based on CFAR and Target Variance Characteristics
Authors: Zhang Lijuan , Sun Donglai , Wang Lu , Wang Zhengbo , Wang Jianqiang
Published: June 2022

Target detection is a complex process that is important as an important module in computer vision applications. In particular, in many occasions where the real-time requirements are extremely high, it is very important to achieve fast and accurate detection of targets. But at this stage, there are still many problems in the research on rapid target detection, such as inefficiency and high is the first phase of automatic target recognition (ATR). For the performance of SAR image target detection, this paper proposes a CFAR fast detection algorithm based on Rayleigh. CFAR detection is divided into two steps: horizontal and vertical CFAR detection. The efficiency of parameter estimation is improved by the coincidence of adjacent point reference windows and the distribution characteristics of images. The algorithm in this paper combines the target variance characteristics to reduce the false alarm rate. The experiment was performed on the MSTAR dataset. Fast target detection algorithm based on CFAR and target variance feature has the characteristics of high detection rate, low false alarm, and high speed, and its detection performance is good. The experimental results show that the recognition efficiency of the proposed algorithm is higher than that of the traditional algorithm on different target datasets, the time is shortened by 30%, and the accuracy rate is equal to that of the traditional algorithm.
Designing an English Teaching Resource’s Information Management System Using Collaborative Recommendation
Authors: Liu Yanxia
Published: June 2022

In the modern world, English education institutions are more concerned about how to recommend the required resources to all types of learners and how to improve the application value of the resources. Therefore, this study introduces and combines the collaborative recommendation algorithm to recommend resources to the learners. The development and design of an English teaching resource information management system based on collaborative recommendation technology are in the best interests of English learners. It establishes an English teaching resource information management system to recommend appropriate teaching resources for different English learners and provide personalized recommendations. English teaching resources are used to improve efficiency and make it easier for English learners to find English teaching resources that meet their specific requirements. Firstly, this study briefly introduces the collaborative algorithm and establishes how the score of similar items or users is calculated by the user-based collaborative filtering algorithm and the item-based collaborative filtering algorithm. Based on similarity, the proposed approach recommends the architectural framework of the English teaching system to other users, describes the functions of each module of the system in detail, and detects the system’s application performance through simulation experiments. The result shows that the learning resources are sufficiently accurate. The design system, in comparison with the general information management system, can reduce the time required for users to obtain English teaching resources.
Identification of Prognosis-Related Molecular Subgroups and Construction of a Prognostic Prediction Model Using Immune-Related Genes in Pancreatic Cancer
Authors: Fei Xiang , Kong Lingming , Shi Chao , Wang Gang , Liu Chenhai , Wang Cheng , Liu Peng , Tan Xiaodong
Published: June 2022

Background. Pancreatic cancer patients with similar clinicopathological status exhibit substantially different therapeutic responses, which might be caused by the vast molecular heterogeneity of tumors. In this study, we attempted to identify specific molecular subgroups and construct a prognostic prediction model based on the expression level of immune-related genes in pancreatic cancer. The transcriptome profiling, single nucleotide variation, copy number variation, clinicopathological information, and follow-up data of pancreatic cancer patients were obtained from The Cancer Genome Atlas database. Thereafter, the immune-related genes with prognostic significance were identified for further consensus cluster analysis. The molecular characteristics and clinicopathological information were compared between the identified subgroups, and a weighted correlation network analysis was performed to identify the hub genes associated with the subgroups. Finally, the prognostic prediction model based on immune-related genes was established using the least absolute shrinkage and selection operator (LASSO) analysis. Results. A total of 67 immune-relevant genes with prognostic significance were selected and used for the consensus cluster analysis. The total samples were divided into two groups, C1 and C2. The subgroup C1 had a significantly worse prognosis than C2, as well as lower levels of immune cell infiltration, which indicate an immunosuppressed state. The mutational rate of the cancer-related genes including KRAS, TP53, and RNF43 was higher in the C1 subgroup. The C1 subgroup was associated with more advanced tumor grade and T stage and with higher mortality. Using LASSO regression, we developed a prognostic prediction model based on the expression levels of 19 immune-related genes, which we validated in three external data sets. In addition, we identified four potential therapeutic and prognostic biomarkers (TNNT1, KCNN4, SH2D3A, and PHLDA2). Conclusion. We identified two novel molecular subgroups of pancreatic cancer and developed a prognostic prediction model based on the expression levels of immune-related genes, which could be used in a clinical setting and could aid in unraveling the molecular processes leading to the development of pancreatic cancer.
Construction and Practice of Multiple Mixed Teaching Mode Based on Big Data Analysis: A Case Study of “International Trade” Course
Authors: Wu Xiaoyuan
Published: June 2022

With the progress of society, the quality requirements of international business enterprises for international business talents have been improved accordingly. So, it is urgent to conduct in‐depth research on the teaching model and the improvement of students’ practical ability. Taking international business as an example, this paper analyzes the contradiction between the supply and demand of international business technical talents by literature research. Furthermore, the convolution neural network model is used to improve the consistency between the talent cultivation of international business major and the talent demand of enterprises by interviewing teachers and questionnaire survey of students. By studying how to implement the professional training curriculum system construction and enterprise to talented person ability training requirements cohesion, this paper in view of the secondary vocational school of international business in today’s society professional training curriculum system was modified and perfected. The ultimate purpose of this paper is to meet the demand of international business for characteristic talents and constantly promote the high‐quality development of international business education.
Alpha Power Generalized Inverse Rayleigh Distribution: Its Properties and Applications
Authors: Ali Muhammad , Khalil Alamgir , Almaspoor Zahra , Hussain Sundus , Khalil Umair , El-Morshedy M.
Published: June 2022

This manuscript is related with the development of Alpha Power Generalized Inverse Rayleigh (APGIR) Distribution. The suggested model provides fit of life time data more efficiently. Some of the important characteristics of the suggested model are obtained including moments, moment generating function, quantile, mode, order statistics, stress-strength parameter, and entropies. Parameter estimates are obtained by MLE technique. The performance of the suggested model is evaluated using real-world data sets. The findings of the simulation and real data sets suggest that the newly proposed model is superior to other current competitor models.
Parameterization and Performance of Permanent Magnet Synchronous Motor for Vehicle Based on Motor-CAD and OptiSLang
Authors: Li Wei , He Yongling
Published: June 2022

With the popularity of electric vehicles, electric vehicles have become a hot research topic, and the performance of permanent magnet synchronous motor has become increasingly prominent in recent years. Therefore, the application of permanent magnet synchronous motor in electric vehicles has become a possibility. Based on the analysis of the existing permanent magnet synchronous motor technology for electric vehicles, this paper will start from the motor body design. In this paper, the performance parameters of permanent magnet synchronous motor meeting the requirements of vehicle operation are estimated by analyzing the parameters of electric vehicle, and the motor is modeled based on the motor design software Motor-CAD. In this paper, the parametric analysis module in the software is used to optimize the parameters of motor permanent magnet, stator slot width, air gap magnetic density, and air gap length. Finally, this paper uses OptiSLang software to simulate and analyze the permanent magnet synchronous motor. It improves the driving performance of automobile motor and reduces energy consumption, so that the permanent magnet synchronous motor can better meet the requirements of electric vehicles. The experimental results show that the optimal range of motor split ratio is large, in the range of 0.85~0.9.
Urban Landscape Information Construction and Visual Communication Design Based on Digital Image Matrix Reconstruction
Authors: Yu Jie , Zhang Liping
Published: June 2022

This paper adopts the matrix reconstruction method to analyze the digital image of urban landscape information in-depth and uses it to study and design the visual communication of its construction. Based on the special structure and properties of Toeplitz matrices, a stepwise structured Augmented Lagrange Multiplier (SALM) algorithm for Toeplitz matrix filling is proposed by introducing structured operators. The main idea of the algorithm is to structure the iteration matrix at each step, that is, to reassign the elements on each diagonal of the matrix by the operator. In this way, the approximation matrix always maintains the Toeplitz structure during the iterative process, and the fast singular value decomposition of the Toeplitz. A matrix can be exploited, thus saving time. The convergence theory of the new algorithm is further discussed. A lightweight progressive feature fusion module is designed to improve network learning efficiency, which consists of two components: progressive local connectivity and feature attention. Specifically, progressive local connectivity extracts multilevel features for fusion by layer-by-layer separation and local splicing. Feature attention evaluates the importance of features using both channel and spatial dual attention modules. The Oculus Rift virtual reality device system is used, and the OSG graphics rendering engine is used as the basis for the scene data transfer of the overall 3D cityscape towards the virtual reality headset display device system. With the support of the Oculus SDK, the secondary rendering of the overall 3D cityscape in the immersive virtual reality module is carried out, and the corresponding OSG camera browsing interface is constructed to realize the two-eye immersive virtual display of the 3D cityscape in a virtual reality headset display device, assisting in connecting the virtual cityscape to reality.
Biosorption of Malachite Green from Aqueous Phase by Tamarind Fruit Shells Using FBR
Authors: Murugesan Senthil Rajan , Sivakumar Vivek , Velusamy Sampathkumar , Ravindiran Gokulan , Sundararaj Premkumar , Maruthasalam Veerapathran , Thangavel Ravindaran , Ramasamy Gowri Shankar , Panneerselvam Mukesh , Periyasamy Selvakumar
Published: June 2022

The aim of this research is to remove malachite green (MG) from a created water environment utilising tamarind fruit shell (TFS) and a fixed-bed reactor (FBR) technology at room temperature. Biosorption is the finest method for dye removal among the several approaches available. It produces excellent results and may be used to remove a wide range of colouring components. It is used to weigh different options for firm things. The option which balances other ones on various counts is the finest one. Various studies have found that eating malachite green-contaminated fish poses a major health risk to people. From the FBR studies, the effect of various factors such as flow rate, initial sorbate concentration, biosorbent size, and bed depth on breakthrough of MG is assessed. The study was carried out to fix the flow rates. This is done by varying the biosorbent size with constant bed depth of 30 cm. The trend in flow rate variation appears to be similar for 0.33 and 0.6 mm sizes, whereas for 0.13 mm size, it is slightly different. The head loss and swelling of TFS particles are insignificant, during the fixed-bed studies. It is estimated that 30.9 T of crude TFS is required to get 8300 kg of 0.6 mm size of TFS. The service time obtained from design was more than the experimental breakthrough time, and calculated bed efficiency was >90%. The biosorption of MG by TFS can be well explained by the BDST approach. Acid regenerants such as 0.5 N H2SO4 and 0.5 N HCl can satisfactorily regenerate the spent TFS in the FBR system, with 0.5 N HCl being a better one.
Application of CAD in Semifinished Product Packaging Art Design
Authors: Mao Yangyang , Wu Tie
Published: June 2022

In order to solve the problem, the packaging CAD software developed in China is mostly the design software of carton and rarely involves the design of cushion liner. It is proposed to use Visual C++ program to develop this software for buffer packaging design, which liberates people from the complicated manual design, significantly shortens the product R&D cycle, and avoids the destructive test of the product. When the overall dimension, quality, brittleness value, cushioning performance parameters of cushioning materials, transportation conditions of packages, and liner parameters are known, the most economical material can be found in the database of cushioning materials through this software, and the liner size structure can be obtained. Based on this data, the structural design of corrugated box is further carried out. For the packaging of products, especially the packaging of precision electronic products, its economic benefits are considerable. Visual C++ 6.0 is used as the software development tool. Using the GUI (graphical device interface) characteristics of various tools and other high-level languages, a simple and friendly user interface is designed to verify the effectiveness of the experiment.
Statistical Modeling of Some Cancerous Diseases Using the Laplace Transform Approach of Basic Life Testing Issues
Authors: Bakr M. E. , Al-Babtain Abdulhakim A. , Khosa Saima Khan
Published: June 2022

The purpose of the nonparametric statistical test used in this study is to compare different treatment options by looking at failure behavior in recorded survival data. Patients’ survival times are documented after using the proposed approach. The observed data’s behavior was assumed to be based on used better than aged in the moment generating function order (UBAmgf) characteristic or a constant failure rate in this study (exponential scenario). Suppose that the survival data is UBAmgf, then the treatment or the machine or system in use produces a better or a higher expected total present value than an older machine governed by an exponential survival function; if the data is exponential, the suggested treatment strategy is ineffective (the recommended treatment approach has neither positive or negative effects on the patients). To guarantee that the suggested statistical test is used correctly, the efficiency and critical values are calculated and compared to those of other tests, and the technique is then applied to medical data.
Growth Series of the Braid Monoid
M

B

5

in Band Generators
Authors: Khan Muhammad Haleem , Iqbal Zaffar
Published: June 2022

Growth series is an important invariant associated with group or monoid which classifies all the words of group or monoid. Therefore, the growth series of braid monoids and Hecke algebras in Artin’s generators is presented in many scholarly published articles. The growth series of braid monoids

M

B

3

and

M

B

4

in band generators is known. In this work, we compute the complete presentation of braid monoid

M

B

5

in band generators by solving all the ambiguities of

M

B

5

. The words on the left-hand of each relation are reducible words, and the words on the right-hand side are canonical words. We partially find the growth series

 

Q

∗

5

of reducible words. Then, we construct a linear system for canonical words of

M

B

5

in band presentation and compute the corresponding growth series. We also find the growth rate of growth series of

M

B

5

in band generators.
Protecting and Expanding Railway Networks to Hedge against Disruptions: A Model with Travel Segments
Authors: Starita Stefano , Irawan Chandra Ade , Jindahra Pavitra
Published: June 2022

Railway systems are instrumental to countries’ economies. They are also vulnerable to man-made and natural disruptions and therefore need to be protected. This paper introduces an optimization model to identify the set of fortifications and network expansions to mitigate the impact of worst-case disruptions. The model incorporates multiple travel segments allowing to study the impact of different route choice behaviours. A Benders decomposition approach is developed to solve the bilevel problem alongside a more efficient nested GRASP heuristic. The algorithms are tested and compared on a set of artificial grids. A case study is developed using the Central London Tube network to provide managerial insights.
Seismic Response Analysis of Isolated and Nonisolated Continuous Girder Bridges under Multidimensional Near-Field Ground Motions
Authors: Gao Ying , Yan Xiaoyu , Chen Junjie , Zheng Liang , Han Yunshan
Published: June 2022

In this study, the responses of isolated bridges and nonisolated bridges are studied under multidimensional seismic motions. First, damage constitutive models of steel bars and concrete materials were combined with the fiber beam-column element model, and the isolated bearing model considering bearing failure was selected. The bridge numerical analysis model was then established. The seismic responses of isolated and nonisolated bridges were analyzed under near-field ground motions (fling-step and forward-directivity ground motions) and far-field ground motions. It was found that the seismic responses of nonisolated bridges, such as deck acceleration, pier displacement, pier damage, and bearing displacement under near-field ground motions, were higher than those under far-field ground motions. Under far-field ground motions, isolation bearings effectively reduced various seismic responses of structures and had isolation effects. Under forward-directivity TCU102 ground motions, the minimum isolation ratios of isolation bearings for peak acceleration of the girder in the Z direction, pier displacement, and pier shear force were −0.14, −2.65, and −0.05, respectively. The low-isolation ratio and significant damage to the isolation bearings indicate that the isolation bearings cannot be directly used under near-field conditions.
Test Verification of the Standard Compilation of “Energy-Saving Monitoring for Refrigeration Storage System” in Beijing
Authors: Ren Jing , Zhang Jinhua , Si Chunqiang , Wang Nan , Qin Bo , Ma Chao , Zhang Bao , Li Jianghong , Li Yonghui
Published: June 2022

In this paper, the feasibility and applicability of the test and evaluation methods for the temperature and energy consumption coefficient in the cold storage system are tested and verified which is specified in the Beijing local standard “Energy Conservation Monitoring of Refrigeration Storage.” It also summarizes and analyses the test verification results of the evaluation index of the location of measuring points of temperature in refrigeration storage, data-collecting time interval of temperature in refrigeration storage, energy efficiency coefficient of the refrigeration unit, and energy consumption coefficient of the refrigeration. The study work provides technical support for making the monitor and evaluation methods which applies to the standard.
Design of Sports Rehabilitation Training System Based on EEMD Algorithm
Authors: Wang Kaiwei , Wang Zhenghui , Ren Wu , Yang Chunsheng
Published: June 2022

Motor function rehabilitation training is to restore the motor function of hand injury to the maximum extent and meet the needs of patients’ daily behavior. At present, motor function evaluation and rehabilitation training work have disadvantages such as relying on the subjective experience of physicians, unable to quantitatively assess the loss of motor function, and single rehabilitation training method. Most of these methods only focus on the independent motion range of a single organ, lack of consideration of the constraint relationship between adjacent fingers, and do not build a visual model for it. To end this issue, for the purpose of sports rehabilitation, combined with the status and application of rehabilitation machines, this paper proposed a cycling rehabilitation training system based on physiological signal extraction of ensemble empirical mode decomposition (EEMD) algorithm. Results compared with the previous rehabilitation training, the muscle tension level of patients’ upper limbs decreased, and the strength of some muscles also increased. With the progress of rehabilitation training, the contralateral dominance coefficient showed an upward trend, which further confirmed the role of the proposed method in sports rehabilitation, and also provided a new idea for the evaluation of rehabilitation training effect of patients in the future.
Helicobacter pylori-Negative Advanced Gastric Cancer Arising from the Gastric Mucosa without Inflammation, Atrophy, or Intestinal Metaplasia
Authors: Hayashi Jiro , Yamatsuji Tomoki , Suehiro Mitsuhiko , Haruma Ken , Katsumata Ryo , Kawamoto Hirofumi , Kamada Tomoari , Yoshida Kazuhiro , Yoneda Masamichi , Monobe Yasumasa , Naomoto Yoshio
Published: June 2022

Gastric cancer is strongly associated with atrophic gastritis associated with Helicobacter pylori infection. The eradication of H. pylori has been reported to improve inflammation of the gastric mucosa, atrophy, and intestinal metaplasia and has also been shown to inhibit the development and growth of gastric cancer. Advanced gastric cancer from H. pylori-negative mucosa without inflammation, atrophy, or intestinal epithelialization is rarely found. We report on two cases of advanced gastric cancer without endoscopic evidence of gastric mucosal atrophy. One case was in the gastric angle 9 years after H. pylori eradication and the other case was in the pylorus of an uninfected stomach. Although gastric cancer is strongly associated with atrophic gastritis caused by H. pylori infection, postoperative histopathological examination of the stomach in both cases showed no inflammation, atrophy, or intestinal metaplasia. Poorly differentiated adenocarcinomas were confirmed at the microscopic level, and both cases were determined to be type 4 using the Borrmann classification. There is a body of evidence showing that H. pylori infection can cause gastric cancer and is the most prevalent infection-induced cancer in the world. The 2 cases here displayed different carcinogenesis than gastric mucosal atrophy caused by H. pylori infection. With the spread of H. pylori eradication treatments and an increasing number of uninfected patients, these case reports can contribute to future strategies for the diagnosis of gastric cancer.
Identification of Metastatic Conjunctival Squamous Cell Carcinoma through Neck Palpation
Authors: Nishath Thamanna , Nguyen Minh T. , Wu Michael , Marshall Desiree A. , Stacey Andrew W.
Published: June 2022

An 80-year-old male with a distant 10 pack-years smoking history and squamous cell carcinoma (SCCA) of the scalp diagnosed 15 years ago presented with a new right nasal bulbar conjunctival lesion found to be invasive SCCA. The patient was started on interferon alfa-2b for 5 months until there was no evidence of residual disease. During a follow-up visit 10 months after diagnosis and during routine ophthalmic follow-up, an enlarged right submandibular lymph node was found through neck palpation and revealed to be SCCA without extranodal extension. The lesion was likely to have metastasized from his right conjunctival squamous cell carcinoma (CSCCA). Regional lymph nodes are a commonplace of metastasis for CSCCA making neck palpation a reasonable and recommended part of clinical examination to monitor for metastasis. This is the first known case of identifying regional metastasis of CSCCA through neck palpation.
SBIDDS Syndrome: A New Spoke of the Epigenetic Machinery Wheel
Authors: Aleo Sebastiano , Pezzani Lidia , Milani Donatella , Pezzoli Laura , Marchisio Paola , Iascone Maria
Published: June 2022

Introduction: Mendelian disorders of the epigenetic machinery are a growing group of disorders exhibiting several overlapping clinical features that are probably due to common abnormalities at the epigenomic level, which lead to downstream convergence at the transcriptomic level. Case presentation: Here, we report a new case of short stature, brachydactyly, intellectual developmental disability, and seizures (SBIDDS) syndrome with a severe ocular phenotype and hypogonadism. Conclusion: Similarities and connections with other mendelian disorders of the epigenetic machinery are highlighted, confirming SBIDDS′ enrolment as a new spoke of the epigenetic machinery wheel.
Deep Learning-Based Model Significantly Improves Diagnostic Performance for Assessing Renal Histopathology in Lupus Glomerulonephritis
Authors: Shen Luping , Sun Wenyi , Zhang Qixiang , Wei Mengru , Xu Huanke , Luo Xuan , Wang Guangji , Zhou Fang
Published: June 2022

Background: Assessment of glomerular lesions and structures plays an essential role in understanding the pathological diagnosis of glomerulonephritis and prognostic evaluation of many kidney diseases. Renal pathophysiological assessment requires novel high-throughput tools to conduct quantitative, unbiased, and reproducible analyses representing a central readout. Deep learning may be an effective tool for glomerulonephritis pathological analysis. Methods: We developed a murine renal pathological system (MRPS) model to objectify the pathological evaluation via the deep learning method on whole-slide image (WSI) segmentation and feature extraction. A convolutional neural network model was used for accurate segmentation of glomeruli and glomerular cells of periodic acid-Schiff-stained kidney tissue from healthy and lupus nephritis mice. To achieve a quantitative evaluation, we subsequently filtered five independent predictors as image biomarkers from all features and developed a formula for the scoring model. Results: Perimeter, shape factor, minimum internal diameter, minimum caliper diameter, and number of objects were identified as independent predictors and were included in the establishment of the MRPS. The MRPS showed a positive correlation with renal score (r = 0.480, p < 0.001) and obtained great diagnostic performance in discriminating different score bands (Obuchowski index, 0.842 [95% confidence interval: 0.759, 0.925]), with an area under the curve of 0.78–0.98, sensitivity of 58–93%, specificity of 72–100%, and accuracy of 74–94%. Conclusion: Our MRPS for quantitative assessment of renal WSIs from MRL/lpr lupus nephritis mice enables accurate histopathological analyses with high reproducibility, which may serve as a useful tool for glomerulonephritis diagnosis and prognosis evaluation.
Efficacy of Decitabine and Venetoclax as Salvage and Bridge Therapy to Haploidentical Hematopoietic Stem Cell Transplantation in a Multiresistant Acute Myeloid Leukemia Patient
Authors: Serio Bianca , Giudice Valentina , Morini Denise , Guariglia Roberto , Vitolo Rosa , Manzo Paola , Langella Maddalena , Selleri Carmine
Published: June 2022

Treatment of relapsed/refractory or elderly unfit acute myeloid leukemia (AML) is still challenging, and hypomethylating agents in combination with venetoclax, an oral selective BCL2 inhibitor, might be successfully used as salvage therapy. However, clinical trials evaluating the efficacy and safety of this combination in the setting of multiresistant AML treatment also as a bridge to transplant are still ongoing. Here, we reported a 50-year-old male diagnosed with AML with normal cytogenetics and wild type for fms-like tyrosine kinase 3, nucleophosmin 1, and KIT, and treated with decitabine and venetoclax as the fifth line of therapy and after a relapse post-allogeneic transplant. The patient achieved a complete remission and successfully underwent a haploidentical transplant with an overall survival of 48.6 months.