bluuebunny/crossref_metadata_2025 huggingface dataset:
Putting the disability in DEI through inclusive imagery
Authors: Edwards Emory James
Published: July 2022

Disability representation---both the presence of people with disabilities and images depicting disability---is increasingly integrated into computing. But how do we make sure the processes we have for developing inclusive imagery are themselves inclusive?
Reflections on the Evolution of Computer Science Education
Authors: Venkateswaran Sreekrishnan
Published: July 2022

Computer Science education has been evolving over the years to reflect applied realities. Until about a decade ago, theory of computation, algorithm design and system software dominated the curricula. Most courses were considered core and were hence mandatory; the programme structure did not allow much of a choice or variety. This column analyses why this changed Circa 2010 when elective subjects across scores of topics become part of mainstream education to reflect the on-going lateral acceleration of Computer Science.
Implementing Domain-Driven Design (by V. Vernon)
Authors: Rogers David S.
Published: July 2022

This article provides a review of the book Implementing Domain-Driven Design, written by Vaughn Vernon and published by Addison Wesley, © 2013, ISBN-13: 978-0-32183457-7, 612 pp., $64.99.
Communication for Underwater Sensor Networks: A Comprehensive Summary
Authors: Pal Amitangshu , Campagnaro Filippo , Ashraf Khadija , Rahman Md Rashed , Ashok Ashwin , Guo Hongzhi
Published: July 2022

Sensing and communication technology has been used successfully in various event monitoring applications over the last two decades, especially in places where long-term manual monitoring is infeasible. However, the major applicability of this technology was mostly limited to terrestrial environments. On the other hand,
underwater wireless sensor networks (UWSNs)
opens a new space for the remote monitoring of underwater species and faunas, along with communicating with underwater vehicles, submarines, and so on. However, as opposed to terrestrial radio communication, underwater environment brings new challenges for reliable communication due to the high conductivity of the aqueous medium which leads to major signal absorption. In this paper, we provide a detailed technical overview of different underwater communication technologies, namely acoustic, magnetic, and visual light, along with their potentials and challenges in submarine environments. Detailed comparison among these technologies have also been laid out along with their pros and cons using real experimental results.
Reinforcement Learning for Practical Express Systems with Mixed Deliveries and Pickups
Authors: Chen Jinwei , Zong Zefang , Zhuang Yunlin , Yan Huan , Jin Depeng , Li Yong
Published: July 2022

In real-world express systems, couriers need to satisfy not only the delivery demands but also the pick-up demands of customers. Delivery and pickup tasks are usually mixed together within integrated routing plans. Such a mixed routing problem can be abstracted and formulated as Vehicle Routing Problem with Mixed Delivery and Pickup (VRPMDP), which is an NP-hard combinatorial optimization problem. To solve VRPMDP, there are three major challenges as below. (a) Even though successive pickup and delivery tasks are independent to accomplish, the inter-influence between choosing pickup task or delivery task to deal with still exists. (b) Due to the two-way flow of goods between the depot and customers, the loading rate of vehicles leaving the depot affects routing decisions. (c) The proportion of deliveries and pickups will change due to the complex demand situation in real-world scenarios, which requires robustness of the algorithm. To solve the challenges above, we design an encoder-decoder based framework to generate high-quality and robust VRPMDP solutions. First, we consider a VRPMDP instance as a graph and utilize a GNN encoder to extract the feature of the instance effectively. The detailed routing solutions are further decoded as a sequence by the decoder with attention mechanism. Second, we propose a Coordinated Decision of Loading and Routing (CDLR) mechanism to determine the loading rate dynamically after the vehicle returns to the depot, thus avoiding the influence of improper loading rate settings. Finally, the model equipped with a GNN encoder and CDLR simultaneously can adapt to the changes in the proportion of deliveries and pickups. We conduct the experiments to demonstrate the effectiveness of our model. The experiments show that our method achieves desirable results and generalization ability.
Kidney-targeted irradiation triggers renal ischemic preconditioning in mice
Authors: Khbouz Badr , Lallemand François , Cirillo Arianna , Rowart Pascal , Legouis David , Sounni Nor Eddine , Noël Agnès , De Tullio Pascal , de Seigneux Sophie , Jouret François
Published: July 2022

This study based on a mouse model of renal ischemia-reperfusion (I/R) aimed to 1) test whether and how irradiation strictly centered on the kidney protects against the I/R injury and 2) determine the shortest efficient delay of kidney irradiation to achieve such nephroprotection. Kidney irradiation increased the vascular surface in the renal parenchyma and conferred resistance against renal I/R damage, which highlights novel putative strategies in the field of ischemic acute kidney injury.
Heat acclimation ameliorated heat stress-induced acute kidney injury and prevented changes in kidney macrophages and fibrosis
Authors: Goto Hiroyasu , Nakashima Masahiro , Nakashima Hiroyuki , Noguchi Midori , Imakiire Toshihiko , Oshima Naoki , Kinoshita Manabu , Kumagai Hiroo
Published: July 2022

Heat stress could induce acute kidney injury. Although heat acclimation (HA) reportedly provides thermal tolerance, its effect on heat stress-induced kidney damage remains unclear. This study showed that 5-day HA ameliorates mouse kidney tubular damage and subsequent fibrosis caused by heat stress. It also demonstrated that HA enhances intracellular heat shock protein 70 expression in tubular cells and prevents a decrease in kidney resident macrophages, which explains the renoprotective effect of HA.
Frequency-dependent coexistence of muscle fatigue and potentiation assessed by concentric isotonic contractions in human plantar flexors
Authors: Zero Alexander M. , Paris Michael T. , Rice Charles L.
Published: July 2022

Postactivation potentiation (PAP) enhanced stimulated low frequencies (1 and 10 Hz) during muscle fatigue development when assessed with power (torque × angular velocity) in a voluntary isotonic fatiguing task. Following the task during 30 min of recovery, prolonged low-frequency force depression (PLFFD) was evident, and inducing PAP with brief maximal contractions during this state ameliorated the effects of PLFFD. PAP enhanced peak torque more than peak angular velocity during both baseline and fatiguing conditions.
Two-Step Frequency Estimation of GNSS Signal in High-Dynamic Environment
Authors: Wu Chao , Li Yafeng , Luo Liyan , Xie Jian , Wang Ling
Published: July 2022

To improve frequency accuracy which is affected by two parameters in high-dynamic acquisition, we propose a two-step frequency estimation method based on the mean frequency (MF) model for high-dynamic parameters estimation. The first step is based on the discrete chirp-Fourier transform (DCFT) for coarse MF estimation, where the MF accuracy and frequency search step are derived. In the second step, the maximum likelihood estimation process (MLEP) is adopted for fine MF estimation. Compared with state-of-art methods, it is verified that the two-step method can improve the detection probability in coarse MF estimation and improve the MF accuracy with low computational burdens under conditions with a moderate signal-to-noise ratio (SNR).
A Decision-Making Framework Based on 2-Tuple Linguistic Fermatean Fuzzy Hamy Mean Operators
Authors: Akram Muhammad , Bibi Rabia , Ali Al-Shamiri Mohammed M.
Published: July 2022

Aggregation operators are useful tools for approaching situations in the realm of multiattribute decision-making (MADM). Among the most valuable aggregation strategies, the Hamy mean (HM) operator is designed to capture the correlations among integral parameters. In this article, a series of Hamy-inspired operators are used to combine 2-tuple linguistic Fermatean fuzzy (2TLFF) information. The new 2TLFF aggregation operators that are born from this adaptation include the 2-tuple linguistic Fermatean fuzzy Hamy mean (2TLFFHM) operator, 2-tuple linguistic Fermatean fuzzy weighted Hamy mean (2TFFWHM) operator, 2-tuple linguistic Fermatean fuzzy dual Hamy mean (2TLFFDHM) operator, and 2-tuple linguistic Fermatean fuzzy weighted Hamy mean (2TLFFWDHM) operator. Furthermore, various essential theorems are stated, and special cases of these operators are thoroughly examined. Then, a renewed multiattribute group decision-making (MAGDM) technique based on the suggested aggregation operators is provided. A practical example corroborates the usefulness and implementability of this technique. Finally, the merits of the proposed MAGDM method are demonstrated by comparing it with existing approaches, namely, it can deal with MAGDM problems by considering interactions among multiple attributes based on the 2TLFFWHM operator.
Teaching Effectiveness of Postgraduate Diploma in Teaching and Integrated Curriculum Graduate Teachers: Investigating Students’ and Teachers’ Perceptions
Authors: Ahmed Endris Abdurahman , Hussen Seid Mohammed , Ahmed Abdel-Al Ibrahim Khaled
Published: July 2022

A new teacher education package has been introduced in Ethiopia by the Ministry of Education, which is called the Postgraduate Diploma in Teaching (PGDT), for secondary schools since 2011, replacing the integrated curriculum teacher education program with the purpose of equipping trainees with the knowledge and skills needed. However, little research has been carried out on the effectiveness of the PGDT in relation to the previous (integrated curriculum) programme in the actual practices in secondary schools yet. This study, therefore, aims to assess the students’ and teachers’ perceptions of the teaching effectiveness of the PGDT and integrated curriculum graduate teachers in secondary schools in North Wollo Zone, Ethiopia. Data were gathered from participant students (n = 214) and teachers (n = 16) using purposive sampling. To gather data, questionnaires were employed. The data were analyzed quantitatively using mean, standard deviations, and one-sample t-test. The findings of the study revealed that students and teachers show slightly more positive perceptions of the effectiveness of PGDT, especially in subject matter knowledge; the scores are also significant. However, the results indicated that both the PGDT and integrated curriculum graduate teachers use the lecture method of teaching. Recommendations were forwarded for teacher development, instruction, and research on PGDT. Limitations and future directions of the study are also summarized and discussed.
Pseudo-Relevance Feedback Method Based on the Topic Relevance Model
Authors: Chen Zhaofeng , Guo Naixuan , Sun Jiu , Wang Yuanyuan , Zhou Feng , Xu Sen , Wang Rugang
Published: July 2022

In the field of information retrieval, most pseudo-relevance feedback models select candidate terms from the top

k

documents returned by the first-pass retrieval, but they cannot identify the reliability of these documents. This paper proposed a new approach to obtain feedback information more comprehensively by constructing four corresponding models. Firstly, the algorithm incorporated topic-based relevance information into the relevance model RM3 and constructed a topic-based relevance model, denoted as TopRM3, with two corresponding variants. TopRM3 estimated the reliability of a feedback document in language modeling when executing pseudo-relevance feedback from both term and topic-based perspectives. Secondly, the algorithm introduced topic-based relevance information into Rocchio’s model and constructed the corresponding model, denoted as TopRoc, with two corresponding variants. Experimental results on the five TREC collections show that the proposed TopRM3 and TopRoc are effective and generally superior to the state-of-the-art pseudo-relevance feedback models with optimal parameter settings in terms of mean average precision.
University Teaching Management and Education Reform Based on Multisource Data and Edge Architecture of IoT
Authors: Zhai Nana , Qin Junping
Published: July 2022

With the rapid development of wireless sensor and network technology, learners can learn anytime and anywhere through various intelligent terminals. For this reason, this paper is research on education and teaching reform in universities that use cloud computing and big data. Teaching practice has proved that the teaching reform based on popular technology not only combines theory with practice, can improve students’ interest, and achieve good teaching effect but also is a beneficial exploration for students’ comprehensive training. Aiming at the existing problems of distributed teaching system, this paper proposes to teach the theoretical knowledge points of distributed system under the framework of cloud computing and at the same time cooperate with related teaching reform of comprehensive design.
Establishment of a Nomogram Model for Predicting Cardiovascular and Cerebrovascular Events in Diabetic Nephropathy Patients Receiving Maintenance Hemodialysis
Authors: Liu Xiaobing , Yan Caili , Niu Xiuxiu , Zeng Jiechun
Published: July 2022

Objective. The objective of this study is to explore the risk factors of cardiovascular and cerebrovascular events (CCE) in patients with diabetic nephropathy (DN) receiving maintenance hemodialysis, and to establish a nomogram model on this basis. Method. 144 patients with DN receiving maintenance hemodialysis from February 2020 to February 2021 were selected and followed up for 12 months. They were divided into the occurrence and nonoccurrence groups according to whether CCE occurred. The multivariate logistic regression analysis was used to analyze the influencing factors of CCE, and a predictive nomogram model was established. The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive effect of the nomogram model. The Hosmer-Lemeshow method was used to test the calibration degree. Results. Among the patients, 63 patients (43.75%) encountered CCE. Multivariate logistic regression analysis showed that age >60 years old, history of CCE, dialysis age >12 months, systolic blood pressure >140 mmHg, blood phosphorus level >1.5 mmol/L, triglyceride (TG) level >2.30 mmol/l, adiponectin (ADPN) level <5 mg/L, high-sensitivity-C-reactive protein (hs-CRP) level >10 mg/L, hemoglobin (Hb) level <120 g/L, serum creatinine (SCr) level >720 μmol/L, and albumin (ALB) level <40 g/L were independent risk factors for CCE. Based on the above independent risk factors, a nomogram model of CCE was created. ROC curve analysis showed that the area under curve for predicting CCE was 0.881 (95% CI: 0.833~0.919), indicating that the nomogram model had great predictive effect. The Hosmer-Lemeshow method showed that the calibration curve was in good agreement with the standard curve. Conclusion. Age, history of CCE, dialysis age, systolic blood pressure and serum phosphorus, and TG, ADPN, hs-CRP, Hb, SCr, and ALB levels are all influencing factors for the occurrence of CCE in patients with DN receiving maintenance hemodialysis, and the nomogram model has a great predictive effect on CCE.
Bioinformatics Analysis of Prognosis‐Related Genes and Expression of CXCL8 in Colorectal Cancer
Authors: Yao Zhen , Pan Xue , Chen Wenyue , Pei Yongjian , Chen Chen , Huang Yongkang , Liu Songtao , Liu Yulong
Published: July 2022

Background. Colorectal cancer (CRC), one of the main causes of death, remains a leading cause of mortality in gastrointestinal cancer and tends to affect the younger generation. However, the pathological process of colorectal cancer is unclear. Exploring potential pathogenesis and therapeutic targets of CRC is significant as its high prevalence and high mortality. Nowadays, the rapid development of bioinformatics provides us an opportunity to explore potential molecular markers of CRC. Materials and Methods. First, three CRC gene chips with paracancerous controls were downloaded from the Gene Expression Omnibus (GEO) database. Second, after combining and batch correcting the three chips using the R language and Perl language, the differentially expressed genes (DEGs) were selected to investigate how they affect the CRC occurrence and development by GO and KEGG enrichment analysis. Third, based on the STRING website and the Cytoscape software, the protein‐protein interaction (PPI) network was constructed and the core genes were screened out. Finally, through polymerase chain reaction (PCR) and immunohistochemistry (IHC), the expression and function of the core gene CXCL8 in CRC were explored. Results. GSE10950, GSE44076, and GSE75970, including 126 intestinal cancer samples and 126 paracancer samples, were screened as the datasets. 192 DEGs were screened, including 43 upregulated genes and 149 downregulated genes. Through the DEGs screened out, GO enrichment analysis, KEGG enrichment analysis, and the construction of PPI interaction network were carried out. Finally, according to the nodes and edges in the PPI network, the DEGs were sorted and the core genes were selected. Through basic experiments, the first ranked CXCL8 was further studied, and the results suggest that the expression of CXCL8 is related to the proliferation, migration, invasion, and even distant metastasis of CRC. Conclusion. The present study showed that DEGs of CRC are associated with multiple tumor‐related biological processes and signaling pathways. The core gene CXCL8 has the potential to be a new therapeutic target for CRC.
Sickle Cell Disease in Children: Knowledge and Home‐Based Management Strategies among Caregivers at a Tertiary Facility in Northern Ghana
Authors: Ajinkpang Stephanie , Anim-Boamah Oboshie , Bimpong Kingsley Appiah , Kanton Fatima Joyce , Pwavra Joyce B. P. , Abdul-Mumin Alhassan
Published: July 2022

Sickle cell disease (SCD) is a serious genetic and inherited disorder. It has a physical, psychological, and socioeconomic impact on affected individuals including children and families. Globally, about 275,000 children are born annually with SCD, with an estimated 85% of these births being in Africa. In Ghana, an estimated 2% of infants that were screened were affected by SCD. Although extensive studies have been conducted on the burden on parents of children with SCD, little is known about how parents manage the disease among their children at home in our setting. This qualitative study explored the knowledge of caregivers of children with SCD, how they recognize/monitor complications of the disease and management strategies at home. An explorative qualitative study using the nonprobability purposive method was used to interview fourteen (14) caregivers of children with SCD who were recruited from the Tamale Teaching Hospital. In‐depth interviews using an interview guide was used. A tape recorder was used to record each interview yielding a total of fourteen (14) audios. Audiotapes were transcribed verbatim. Data collected during these interviews were analyzed using inductive thematic content analysis. Caregivers have adequate knowledge of the signs and symptoms of SCD, its complications, and the various types their children have but fall short of knowledge on the cause of SCD. Knowledge acquired on SCD does not translate into caregivers’ ability to effectively identify and monitor crises or complications at home. Home management strategies used by caregivers’ were both pharmacological and nonpharmacological, and some used the combination to manage pain and monitor the health of their children. Even though the majority have used traditional medicine before, they prefer orthodox interventions which they consider more effective.
Optimal Trajectory Planning for Minimizing Base Disturbance of a Redundant Space Robot with IQPSO
Authors: Zhang Jianxia , Yang Fuchao , Nie Guanghua , Zhang Jianxin
Published: July 2022

With the development of aerospace technology, the practical application of a free-floating redundant space robot has become more and more popular. The problem of minimizing base disturbance has been paid attention among academic researchers. If the space robot moves, it would have an impact on the pose of a base. The interference on a base should be reduced, which was caused by the movements of the space robot. In the paper, the simplified model of a redundant space robot has been described, which consists of a base and a 7-joint manipulator. Using the nonholonomic redundancy features, the pose of the base has been optimized planning. First, a set of kinematic equations of the redundant space robot was founded. Second, the 5-order polynomial function could be used for the parametric 7 joints. Third, on the basis of the pose requirements, a fitness function was defined. At last, the proposed improved quantum particle swarm optimization (IQPSO) algorithm was presented. The proposed IQPSO algorithm not only searched the optimal value easily but also had a good robust performance. The advantages could be shown through the numerical experiments, compared with the quantum-behaved particle swarm optimization (QPSO) algorithm, particle swarm optimization (PSO) algorithm, and simulated annealing particle swarm (SAPSO) algorithm. Then, the proposed IQPSO algorithm was used to optimize the fitness function of trajectory planning. By the simulation results, it could be confirmed that the proposed IQPSO algorithm searched the global optimal solution not only easily but also smoothly, compared with the QPSO, PSO, and SAPSO algorithms. The proposed approach was suitable for planning an optimal trajectory.
Effectiveness of Home Care Interventions in Patients with Moderate to Severe Craniocerebral Injury Combined with Epilepsy
Authors: Zhang Luo-luo , Jiang Zi-juan , Li Yuan-yuan , Li Ping , Hua Zhan-yan , Zhou Qian , Cao Feng
Published: July 2022

Objective. To investigate the effect of a home care model on coping style and quality of life of patients with postcranial surgery complicated by epilepsy. Methods. One hundred and forty-four patients with postcranial surgery complicated by epilepsy admitted to our hospital from July 2017 to April 2018 were selected as study subjects and randomly divided into 63 cases each in the observation group and the control group. The control group was given nursing interventions including health education, psychological intervention, medication guidance, complication prevention, and follow-up management, while the observation group was jointly given collaborative family nursing interventions. At a follow-up of 6 months, indicators such as coping style, treatment compliance, and quality of life were compared between the two groups. Results. Patients in the observation group had significantly higher problem solving, help seeking, and rationalization scores and significantly lower self-blame scores than the control group (

P
<
0.01

); significantly higher treatment compliance than the control group (

P
<
0.01

); and significantly higher social functioning, emotional well-being, and energy/fatigue scores than the control group (

P
<
0.01

). Conclusion. The home care model helps to promote the development of positive coping styles, improve treatment compliance, and improve the quality of life of patients after cranial surgery.
Survival Risk Prediction of Esophageal Squamous Cell Carcinoma Based on BES-LSSVM
Authors: Wang Yanfeng , Zhang Wenhao , Sun Junwei , Wang Lidong , Song Xin , Zhao Xueke
Published: July 2022

Esophageal squamous cell carcinoma (ESCC) is one of the highest incidence and mortality cancers in the world. An effective survival prediction model can improve the quality of patients’ survival. In this study, ten indicators related to the survival of patients with ESCC are founded using genetic algorithm feature selection. The prognostic index (PI) for ESCC is established using the binary logistic regression. PI is divided into four stages, and each stage can reasonably reflect the survival status of different patients. By plotting the ROC curve, the critical threshold of patients’ age could be found, and patients are divided into the high-age groups and the low-age groups. PI and ten survival-related indicators are used as independent variables, based on the bald eagle search (BES) and least-squares support vector machine (LSSVM), and a survival prediction model for patients with ESCC is established. The results show that five-year survival rates of patients are well predicted by the bald eagle search-least-squares support vector machine (BES-LSSVM). BES-LSSVM has higher prediction accuracy than the existing particle swarm optimization-least-squares support vector machine (PSO-LSSVM), grasshopper optimization algorithm-least-squares support vector machine (GOA-LSSVM), differential evolution-least-squares support vector machine (DE-LSSVM), sparrow search algorithm-least-squares support vector machine (SSA-LSSVM), bald eagle search-back propagation neural network (BES-BPNN), and bald eagle search-extreme learning machine (BES-ELM).
[Retracted] Dynamic Combined Optimal Scheduling of Electric Energy and Natural Gas Energy Consumption in Data Center
Authors: Liu Xuehui , Hou Guisheng , Yang Lei
Published: July 2022

Energy consumption is the key factor leading to high operating costs in data center. In this paper, considering the data center service level under the premise of using electricity and gas as energy supply of energy supply and energy consumption from two angles, the data center energy scheduling model is built. The lower model is calculation scheduling model for the data center, and the upper model is data center energy supply scheduling model. Then the particle swarm algorithm is used to simulate the schedule. The results show that using natural gas as supplementary energy supply can effectively reduce the overall energy consumption of data center in considering the service delay level of data center.
Effect of Adiponectin Variant on Lipid Profile and Plasma Adiponectin Levels: A Multicenter Systematic Review and Meta-Analysis
Authors: Wang Guiqing , Wang Yufeng , Luo Zhi
Published: July 2022

Background. Adiponectin is a recognized antiatherogenic molecule; this study was aimed at clarifying the effects of adiponectin variants on lipid and adiponectin levels. Methods. By searching PubMed and Cochrane databases for studies published before March 31, 2022, a total of 86,610 individuals were included in the analysis. Results. Variants of rs2241766 and rs266729 were associated with decreased adiponectin and high-density lipoprotein cholesterol (HDL-C), as well as increased triglycerides (TG), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) levels. In contrast, the rs1501299 variant was correlated with increased adiponectin and HDL-C, as well as decreased TG, TC, and LDL-C levels. Subgroup analysis indicated that the significant effect of the rs2241766 and rs266729 variants on lipid profile was predominant in Chinese, while the significant effect of the rs1501299 variant on lipid profile was primarily in Caucasians. Moreover, a stronger effect of the rs2241766 and rs1501299 variants on LDL-C levels was observed in males, while a considerable effect of the rs266729 variant on LDL-C levels was observed in children. Conclusions. The present study indicated that Chinese with the rs2241766 and rs266729 variants were at high risk of dyslipidemia, atherosclerosis, or coronary artery disease (CAD). Males with the rs2241766 variant were at high risk of CAD. Children with the rs266729 variant had a high risk to develop dyslipidemia, atherosclerosis, and even early onset of CAD in the future. These findings are beneficial to clinical physicians to choose different management strategies for cardiovascular disease (CVD) prevention.
A New Method for Centrality Measurement Using Generalized Fuzzy Graphs
Authors: Dhanalakshmi R. , Rashid Junaid , Kim Jungeun , Sivaraman Arun Kumar , Naseem Usman , Vincent Rajiv
Published: July 2022

The fuzzy graph is the foundation of many actual structures such as networking, picture planning, and so on. Generalized fuzzy graphs (GFG) are ideal for avoiding certain constraints of fuzzy graphs. Social networks are a useful and powerful way to link citizens worldwide. A central person in a social network is to deny the leading people in it. Different centrality steps have also been established over the years. We evaluated the centrality of the social network through a general fuzzy graph in this article. An application to detect the central person in any online group like WhatsApp is described in this study by using generalized fuzzy graphs. Also, a few important results are established in this study.
Image Target Detection and Recognition Method Using Deep Learning
Authors: Sun Hongyan
Published: July 2022

Image target detection and recognition had been widely used in many fields. However, the existing methods had poor robustness; they not only had high error rate of target recognition but also had high dependence on parameters, so they were limited in application. Therefore, this paper proposed an image target detection and recognition method based on the improved R-CNN model, so as to detect and recognize the dynamic image target in real time. Based on the analysis of the existing theories of deep learning detection and recognition, this paper summarized the composition and working principle of the traditional image target detection and recognition system and compared the basic models of target detection and recognition, such as R-CNN network, Fast-RCNN network, and Faster-RCNN network. In order to improve the accuracy and real-time performance of the model in image target detection and recognition, this paper adopted the target feature matching module in the existing R-CNN network model, so as to obtain the feature map close to the same target through similarity calculation for the features extracted by the model. Therefore, an image target detection and recognition algorithm based on the improved R-CNN network model is proposed. Finally, the experimental results showed that the image target detection and recognition algorithm proposed in this paper can be better applied to image target detection and classification in complex environment and had higher detection efficiency and recognition accuracy than the existing models. The target detection and recognition algorithm proposed in this paper had certain reference value and guiding significance for further application research in related fields.
A Systematic Review on Antimicrobial and Antiparasitic Activity of Eurycoma longifolia Jack (Tongkat Ali)
Authors: Latip Mohd Qayyum Ab , Noor Mohd Hezmee Mohd , Ahmad Hafandi , Hassim Hasliza Abu , Salleh Annas , Bejo Mohd Hair , Zakaria Alif Aiman
Published: July 2022

Eurycoma longifolia or Tongkat Ali (family: Simaroubaceae) has the potential to be utilised as an antimicrobial and antiparasitic agent that correlated with its traditional use to treat jaundice, malaria, antiseptic agent, and many more. This review is aimed at systematically sieving through articles regarding the antimicrobial and antiparasitic activity of E. longifolia. A total of 123 studies have been found using suitable keywords and manually searched from previous studies through the four databases. After title screening and abstract examination, 56 articles were excluded due to duplication and not meeting the acceptance criteria. 67 articles were assessed on full‐text accessibility, 31 studies remained, and this number decreased to 20 articles after a careful examination of the full‐text articles. Among the 20 articles selected, 17 articles proved the potential of E. longifolia as an antimicrobial and antiparasitic agent efficiently. 2 selected articles showed partial positive results, which specified specific microorganisms tested. In contrast, another 1 article gave a completely negative result. As for the conclusion, current studies highlighted by this review may shed light on the future direction of studies concerning E. longifolia as a novel antimicrobial and antiparasitic agent. However, more research should be done in the future focusing on the efficiency of E. longifolia for veterinary medicine utilisation.
Regional Collaborative Forecast of Cargo Throughput in China’s Circum-Bohai-Sea Region Based on LSTM Model
Authors: Cui Junfei , Liu Bingchun , Xu Yan , Guo Xiaoling
Published: July 2022

Any developed port plays a dominant role both in domestic and international trade reflecting economic prosperity of the port and nearby regions in terms of its cargo throughput and port construction. An attempt is made in this study to use long-and short-term memory (LSTM) artificial neural network method to construct the port cargo throughput prediction model. Three ports namely, Tianjin Port, Dalian Port, and Tangshan Port from China’s Bohai Rim region are selected as research objects. The historical cargo throughput of each port for nearly ten years was used as the input index data for joint prediction. The cargo throughput of Bohai Port provides another way to improve the accuracy of port cargo throughput prediction. The prediction results show that the LSTM model can effectively predict the port cargo throughput; the cargo throughput forecasts between the three Bohai Rim ports have both an interactive relationship and differences.
An Optimization Model of English Teaching Resources Based on Distributed SOA
Authors: Du Juan , Wang Hongping , Du Ping , Chen Hongping
Published: July 2022

As a result of the growth and development of digital education, many educational resources have appeared on the Internet. On the other hand, these educational resources are scattered, unorganised, duplicated, isolated, and closed. Based on a detailed study of the characteristics and design ideas of SOA software system architecture, this paper develops an integrated and optimized system of English teaching resources based on SOA. SOA is a new service model for sharing and integrating educational resources from disparate sources that is characterized by loose coupling, platform independence, interoperability, and openness. This paper explains the system’s overall structural framework and design flow. It also explains how each layer structure’s function is realized through technology and process. Different service interfaces are used to realize various system functions, and an abstract service interface is left for future system expansion, allowing the system to be reused as much as possible. The system proposed in this paper is an open sharing platform for educational resources that has unified standards and rich content, greatly improving the situation of previously isolated educational information resources.
Anti‐CD44 and EGFR Dual‐Targeted Solid Lipid Nanoparticles for Delivery of Doxorubicin to Triple‐Negative Breast Cancer Cell Line: Preparation, Statistical Optimization, and In Vitro Characterization
Authors: Darabi Farnosh , Saidijam Massoud , Nouri Fatemeh , Mahjub Reza , Soleimani Meysam
Published: July 2022

Background. Despite being more aggressive than other types of breast cancer, there is no suitable treatment for triple‐negative breast cancer (TNBC). Here, we designed doxorubicin‐containing solid lipid nanoparticles (SLNs) decorated with anti‐EGFR/CD44 dual‐RNA aptamers, which are overexpressed in TNBC. For more efficiency in the nuclear delivery of doxorubicin, dexamethasone (Dexa) was chemically attached to the surface of nanoparticles. Methods. To prepare the cationic SLNs, 6‐lauroxyhexyl BOC‐ornithine (LHON) was synthesized and was chemically attached to dexamethasone to form Dexa‐LHON complexes. The doxorubicin‐containing SLNs were prepared via double emulsification (w/o/w) and the solvent evaporation technique. The preparation of SLNs was statistically optimized using the central composite response surface methodology. Independent factors were the GMS/lecithin concentration ratio and the amount of Tween 80, while responses considered were particle size, polydispersity index, and entrapment efficiency of the nanoparticles. The optimized nanoparticles were studied morphologically using transmission electron microscopy, and in vitro release of doxorubicin from nanoparticles was studied in phosphate‐buffered saline. Then, the designated aptamers were attached to the surface of nanoparticles using electrostatic interactions, and their cytotoxicity was assessed in vitro. Results. The size, PDI, zeta potential, EE%, and LE% of the prepared nanoparticles were 101 ± 12.6 nm, 0.341 ± 0.005, +13.6 ± 1.83 mV, 69.98 ± 7.54%, and 10.2 ± 1.06%, respectively. TEM images revealed spherical nanoparticles with no sign of aggregation. In vitro release study exhibited that 96.1 ± 1.97% of doxorubicin was released within 48 h of incubation. The electrostatic attachment of the designated aptamers to the nanoparticles’ surface was confirmed by reducing the zeta potential to −15.6 ± 2.07 mV. The in vitro experiments revealed that the SLNs/DOX/Dexa/CD44 or EGFR aptamers were substantially more successful than SLNs/DOX/Dexa at inhibiting cell proliferation. Using the MDA‐MB‐468 cell line, we discovered that SLN/DOX/Dexa/CD44/EGFR aptamers were more effective than other constructs in inhibiting cell proliferation (p < 0.001). The reduction of cell viability using this construct suggests that targeting numerous proliferation pathways is effective. Conclusion. Overall, the finding of this investigation suggested that SLNs/DOX/Dexa/CD44/EGFR could be a promising new enhanced anticancer delivery system and deserved further preclinical consideration.
Prediction Model of the Coring Asphalt Pavement Performance through Response Surface Methodology
Authors: Shaffie Ekarizan , Jaya Ramadhansyah Putra , Ahmad Juraidah , Arshad Ahmad Kamil , Zihan Mohd Afiq , Shiong Fiona
Published: July 2022

Pavement evaluations provide crucial information regarding the performance and service life of asphalt concrete (HMA). They examine the structure of an existing pavement before deciding on different maintenance alternatives. The Klang Valley, as part of one of the developing areas in the state of Selangor, generates a high volume of traffic every day due to the increasing number of vehicles crossing the area. Every day, the impact of axle loads caused by vehicles has a negative impact on flexible pavement, resulting in road deterioration due to extreme distress. Pothole failures are one of the most common causes of distress. Five research areas in the Klang Valley area that have deteriorated owing to pothole failures were chosen as case studies. The objective of the study is to investigate the existing flexible pavement conditions by means of laboratory testing consisting of physical, volumetric, and performance tests using collected core samples. As a result, the data collected was compared to the Malaysian Public Work Department’s (PWD) standard. Data from laboratory tests was analyzed using Response Surface Methodology (RSM) to determine correlations with parameters influencing distress. Historical data design was carried out between test components and responses, which consisted of laboratory parameters. Axial strain, tensile strength ratio, and stability were the responses measured in the RSM. The created models between the independent variables and responses revealed a high level of correlation. The binder content, degree of compaction, and stiffness were the most significant operating parameters from the 3D plots. Optimized performance due to asphaltic pavement failure was observed at binder content (5.1%), degree of compaction (97%), and stiffness (3.1 kN/mm) to achieve ultimate axial strain (5000 microstrains), tensile strength ratio (80%), and stability (9.2 kN). The study showed that the response surface methodology (RSM) is an effective statistical method for providing an appropriate empirical model for relating parameters and predicting the best performance of an asphaltic mixture to reduce flexible pavement failure.
Study on Steel Content Estimation of Reinforced Concrete Rectangular Pool Wall
Authors: Li Yanfang , Wang Yonghua , Ren Chao , Zhang Bo , Kang Hongzhen
Published: July 2022

For water purification plants and sewage treatment plants, there is no reference optimal steel content for the wall of reinforced concrete water pool. Focusing on the reinforced concrete water pool, this paper explores the optimal wall thickness and optimal reinforcement area at different bending moments and identifies the optimal steel content. To solve the problem, the authors established the discrete distribution function for the engineering cost per unit length of pool wall and steel content. The theoretical model was verified by numerous data through Excel numerical simulation. The research results provide a reference optimal steel content for designers and help to save the engineering cost of pool wall.
Synthesis, Characterization, and Electrochemical Activities of Ruthenium(II) Bipyridyl-Dithiocarbamate Complexes
Authors: Fudo Zintle , Ajibade Peter A. , Odularu Ayodele T.
Published: July 2022

Five heteroleptic ruthenium(II) polypyridyl complexes [Ru(FL1)(dcbpy)(NCS)] (1), [Ru(FL2)(dcbpy)(NCS)] (2), [Ru(FL3)(dcbpy)(NCS)] (3), [Ru(FL1)(dcbpy)(NCS)] (4), and [Ru(FL5)(dcbpy)(NCS)] (5) (where FL1 = aniline dithiocarbamate, FL2 = p-anisidine dithiocarbamate, FL3 = p-toluidine dithiocarbamate, FL4 = dibenzyl dithiocarbamate, and FL5 = diphenyl dithiocarbamate, dcbpy =2, 2′-bipyridine-4,4′-dicarboxylic acid, NCS = ammonium thiocyanate) have been synthesized and characterized with melting point, FTIR, UV-Vis, photoluminescence, and NMR (1H and 13C NMR) techniques, while the electrochemical activities of the complexes were studied using cyclic voltammetry. The FTIR of the heteroleptic complexes showed successful coordination of the ligands to ruthenium(II) ion, while the UV-Vis confirmed six coordinate octahedral geometry of the complexes, and the photoluminescence gave the photophysical properties with high intensities indicating potentials for dye sensitization. The electrochemical activities of the ruthenium(II) complexes showed redox potentials which could enhance the dye-sensitizing abilities.
Bacterial Performance in Crack Healing and its Role in Creating Sustainable Construction
Authors: Alemu Digafe , Demiss Wubetie , Korsa Gamachis
Published: July 2022

Building practices began with human civilization. Cement is the most commonly used building construction material throughout the world. These traditional building materials have their own environmental impact during production, transportation, and construction, but also have limitations on building quality and cost. Biological construction materials are currently emerging technology to combat emissions from the construction sector. Different civil and biotechnology researchers have turned to microorganisms for the production of bio construction materials that are environmentally friendly, socially acceptable, and economically feasible but can also produce high strength. Scanning electron microscope (SEM) and X-Ray diffraction (XRD) are the most characterization methods used to observe and ensure the production of calcite precipitate as bacterial concrete. As compared to conventional concrete, bacterial concrete was greater by 35.15% in compressive strength, 24.32% in average tensile strength, and 17.24% in average flexural strength, and it was 4 times lower in water absorption and 8 times lower in acid resistivity than conventional concrete. Genetic engineering has great potential to further enhance the mechanical strength of bacterial concrete for use in crack repairs in existing buildings.
Damped Free Vibration Analysis of Woven Glass Fiber-Reinforced Epoxy Composite Laminates
Authors: Navaneeth I. M. , Poojary Suhas , Chandrashekar A. , Razak Abdul , Hasan Nasim , Almohana Abdulaziz Ibrahim
Published: July 2022

Woven glass fiber reinforced with epoxy matrix composites are manufactured considering different glass/epoxy proportions and vibration analyses of the laminated composite plates subjected to free vibrations have been examined. The tensile and flexural strength of composites were evaluated by following ASTM standards. Free vibration of the composite specimen characteristics is studied using a Fast Fourier Transform analyzer, accelerometer using impact hammer excitation. The fast response functions are studied in order to clearly understand the vibration characteristics of the specimens. The experimentally obtained results of the rectangular composite plates are compared with the analytical results obtained from Nastran. The results showed a good agreement. It was observed that as the number of layers of the composite specimen increased, the frequency response also increased.
Precise Recognition Method of Local Fuzzy Features in Sprint Video Images
Authors: Chen Xin
Published: July 2022

In the acceleration phase, sprinters need to have enough strength to support to better complete technical movements. In order to improve the recognition effect of local features in sprint video images, this paper analyzes the sprint process based on the accurate recognition method of local fuzzy features in video images. Moreover, this paper discusses the camera calibration method, and improves the calibration method according to the camera placement and the problems and requirements in field use to obtain an engineered fast calibration method. According to the simulation research, the accurate identification method of local fuzzy features in sprint video images proposed in this paper can play a certain role in sprint video image recognition.
Automatic Recognition and Detection System Based on Machine Vision
Authors: Wang Lu , Cui Lihong
Published: July 2022

In order to realize the automation of part identification and detection and the intellectualization of part production, this paper proposes a method of automatic identification and detection of parts based on machine vision (overall method). This paper combines machine vision with motion control theory and uses pulse coupled neural network (PCNN) edge detection and recognition algorithms to preliminarily design a set of machine vision automatic recognition and detection systems and carry out detection and recognition experiments on small parts such as relay covers. The experimental results show that the whole process of part size detection and recognition, including part feeding, image acquisition, size recognition, part screening, and reset of the experimental platform, can be completed within 5 s and can carry out high-precision dynamic recognition and detection when the part moves at a speed of 1 m/s. Through the correction and compensation of dynamic error, the detection accuracy of small rectangular parts with a length of 28.87 mm and a width of 12.36 mm can reach 0.04 mm. The visual inspection and recognition automation system improves the automation degree of parts inspection, improves the dimensional accuracy, optimizes the robustness of the system, and finally realizes the real-time screening and classification of parts and the efficient production of parts.