bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of COVID-19 on ICU nurses’ psychology and influencing factors under COVID-19’s normalization, prevention and control: A cross-sectional survey
Authors: DONG YUE , BIAN WEINA , CHENG JUNXIANG , LU XUAN , XU PING , MA LIANG
Published: April 2023

Background: The first-line ICU nurses still play an important role in the nursing of patients diagnosed by designated hospitals during the normalization prevention and control of COVID-19. Discussing the mental health status of the first-line ICU nurses will help to provide more accurate measures to improve the mental status of the first-line ICU nurses and improve the quality of nursing.
Aims: To explore the impact and possible influencing factors of the novel coronavirus (COVID-19) on the psychology of ICU nurses under the normalization, prevention and control.
Design: A cross-sectional survey.
Method: We chose 40 ICU nurses working in designated hospitals for novel coronavirus pneumonia in October to December of 2021. A post-traumatic stress disorder survey scale and questionnaire were used to investigate the situation and stressors of first-line ICU nurses.
Results: The average score on post-traumatic stress disorder of first-line ICU nurses was(21.68 + 6.76 ) points under the normalization of prevention and control of COVID-19. Two nurses scored 38 points and had significant clinical symptoms, making the incidence of post-traumatic stress disorder 5%. The main stressors included the discomfort of wearing protective equipment and the concern for relatives at home.
Conclusions: This study shows COVID-19 has little effect on the mental health of front-line ICU nurses and exerts a lighter degree of pressure during the normalization of COVID-19. We can also further improve the psychological status of front-line ICU nurses by improving the quality of protective equipment, increasing ICU staff, obtaining the understanding and support of family members, hierarchical training, and the care and support of managers to further improve the quality of nursing.
Investigation of XPD, miR-145 and miR-770 expression in patients with end-stage renal disease
Authors: Citak Elif , Yalin Serkan Feyyaz , Riza Mehmet , Guven Mehmet
Published: April 2023

Background: The effective maintenance of genome integrity and fidelity is vital for the normal function of our tissues and organs, and the prevention of diseases. DNA repair pathways maintain genome stability, and the adequacy of genes acting in these pathways is essential for disease suppression and direct treatment responses. Chronic kidney disease is characterized by high levels of genomic damage. In this study, we examined the expression levels of the XPDgene, which plays a role in the NER repair mechanism, and the expression levels of miR-145 and miR-770 genes, which play a role in the regulation of the expression of the XPD gene, in hemodialysis patients with (n=42) and without malignancy (n=9) in pre- and post-dialysis conditions. We also evaluated these values with the clinical findings of the patients.
Methods & Results: Gene expression analysis was performed by real-time polymerase chain reaction (qRT-PCR). Compared to the control group (2.06 ± 0.32), the XPD gene expression was lower in the pre-dialysis condition both in hemodialysis patients without cancer (1.24 ± 0.18; p=0.02) and in hemodialysis patients with cancer (0.82 ± 0.114; p=0.001). On the other hand, we found that miR-145and miR-770 expression levels were high in both groups. We also found that expression levels were affected by dialysis processes. A statistically significant positive correlation was found between miR-145 and mir770 expression levels in the pre-dialysis group of patients with (r=-0.988. p=0.0001) and without (r=-0.934. p=0.0001) malignancy.
Conclusions: Studies on DNA damage repair in the kidney will help develop strategies to protect kidney function against kidney diseases.
Assignment of probabilities to the production rules of a conjunctive grammar
Authors: K Kanchan Devi , Subramanian Arumugam
Published: April 2023

The assignment of probabilities to the production rules of a conjunctive grammar which yields a probabilistic conjunctive grammar is a subtle task. We use the maximum likelihood estimation to obtain the probabilities for each production rule and prove that this assignment gives a probabilistic conjunctive grammar.
Mathematics Subject Classification Number: 68Q45
Potential Mechanism of Curcumin and Resveratrol against SARS-CoV-2
Authors: Wu Wei , Wu Junxi , Ji Xuxu , Liu Ji , Liu Bin , Geng Fuchang
Published: April 2023

Recently, World Health Organization predicted a near end of COVID-19 pandemic. However, the prediction should be interpreted cautiously. Due to SARS-CoV-2 continuous mutation-evolve, limited durability of infection-acquired protection in individuals with hybrid immunity, and the effects of long COVID-19 or Post-COVID-19 syndrome, COVID-19 may continue to be a worldwide threat. Alternative therapeutics are incorporated into some countries’ health guidelines for COVID-19. Qiannan herbal, an ancient medical book of Yi Nationality in China, recorded that grapes and turmeric were often used to treat respiratory diseases. Curcumin and resveratrol are the primary bioactive compounds in turmeric and grapes, respectively. The clinical trials confirmed that curcumin or resveratrol supplementation could cause moderate or marked improvements in COVID-19 patients. Exploring the potential mechanisms is of great significance. This study found that curcumin and resveratrol could effectively inhibit SARS-CoV-23CLpro activity and spike protein-mediated cell entry. Curcumin and resveratrol could significantly alleviate spike protein-mediated cytokine storm via inhibiting over-activation of NFKB, and effectively ameliorate spike protein-mediated oxidative stress through scavenging ROS and enhancing function of antioxidation system. The combined treatment showed a better effect than alone treatment. Therefore, curcumin and resveratrol could inhibit SARS-CoV-23C-like proteinase activity and Spike protein-mediated cell entry, cytokine storm, and oxidative stress.
Could be NCOA5a Novel Candidate Gene Playing a Role in MS Disease Susceptibility?
Authors: Rustemoglu Husniye , Arslan Erdem , Atasever Sema , Cevik Betul , Taspinar Filiz , Turhan Ahmet Bülent , Rüstemoğlu Aydın
Published: April 2023

Background Multiple sclerosis (MS) is an inflammatory immune-mediated demyelinating disease which characterized a challenging and disabling condition. It is known that environmental and genetic factors play a role in directing the disease state. Recent studies have shown that nuclear cofactor genes may play a role in the MS pathogenesis. NCOA5 is a nuclear receptor coactivator independent of AF2 that modulate ERa-mediated transcription. NCOA5 gene is also involved in the pathogenesis of various diseases such as psoriasis, Behçet's disease and cancer.Methods and Results We were investigated the relationship between the NCOA5 gene rs2903908 polymorphism and MS disease on 157 unrelated MS patients and 160 healthy controls by RT-PCR. The frequency of CC, CT, and TT genotypes was 19.87%, 37.82%, and 42.31% for the MS group while 5.63%, 43.75%, and 50.62% control group, respectively. In the obtained results, CC genotype and C allele were found to be significantly higher in the patient group (p = 0.0002 and 0.003, respectively). In particular, the fact that the CC genotype was found to be significantly higher in the patient group compared to the control group (p = 0.0002) and that it had a statistically significantly higher OR value (OR,95%CI = 4.16, 1.91–9.05) suggests that the C allele may recessively predispose to the MS disease for this polymorphism.Conclusions These results suggest for the first time in the literature that, the NCOA5 gene may have an effect on the occurrence MS disease through different molecular pathways which discussed in the manuscript.
Efficacy and Safety of Adalimumab in Pediatric Patients With Crohn’s Disease: A Systematic Review and Meta- analysis
Authors: Chen Bin , Zou Zhuan , Zhang Xiaoyan , Xiao Dongqiong , Li Xihong
Published: April 2023

Background:
There is no curative treatment for childhood Crohn’s disease (CD). We conducted this meta-analysis to validate the efficacy and safety of adalimumab (ADA) in pediatric patients with CD.
Methods:
We searched and investigated all relevant studies in the PubMed, Web of Science, Embase, and Cochrane Library databases. Primary outcomes were induction (≤12 week) and maintenance (up to 48 week) of remission and response. Secondary outcomes were severe adverse events, opportunistic infections to adalimumab (ADA). The Cochrane bias assessment tool was used to assess the risk of bias in randomized controlled trials (RCTs). The methodological quality of single-arm studies was assessed using the methodological index for non-randomized studies (MINORS) tool.
Results:
A total of 10 clinical trials involving 885 patients were identified. Results indicate that 59% (95% confidence interval [CI]: 39%–80%) of the subjects treated with ADA achieved induction of remission and response 60% (95% CI: 35%–86%), 57% (95% CI: 44%–70%) achieved maintenance of remission, 63% (95% CI: 26%–69%) achieved maintenance of response.
Conclusion:
Current evidence indicates that ADA is effective in children and adolescents with CD and adverse events are varied but usually not sever.
Systematic Review Registration:
https://www.crd.york.ac.uk/prospero/, identifier
CRD42023402199.
Effects of experimental bleaching gels containing co-doped titanium dioxide and niobium pentoxide combined with violet light
Authors: Matos Iago Cesar Ribeiro Teles , Kury Matheus , Melo Priscila Borges Gobbo , Souza Leticia Vasconcelos Silva , Florez Fernando Luíz Estaban , Cavalli Vanessa
Published: April 2023

Objectives
To evaluate the bleaching potential of 6% hydrogen peroxide (6% HP) gels containing NF_TiO2 or Nb2O5 irradiated with a violet LED light, and the effects on enamel mineral content and surface morphology.
Methods
Particles were synthesized, and experimental gels were chemically analyzed by preliminary and accelerated stability tests, pH, and HP decomposition rate. Enamel blocks were treated with 6% HP gels containing (n = 10): 5% NF_ TiO2, 5% Nb2O5, 2.5% NF_ TiO2 + 2.5% Nb2O5 or without particles (6% HP), irradiated or not with LED, and the control was treated with 35% HP. Color (∆E00) and whitening index (∆WID) variations, surface microhardness (SH), average roughness (∆Ra), Ca-P concentration (EDS), and enamel morphology (SEM) were assessed. Bleaching was performed in 3 sessions of 30 minutes and 7-day intervals. Data were submitted to two- (pH, decomposition rate, ∆E00, and ∆WID) or three-way ANOVA and Bonferroni (SH), Kruskal-Wallis (∆Ra), and Dunnet (α = 0.05).
Results
No changes in the gel’s color, odor, or translucency were observed, pH (6 to 6.5) remained stable over time, and light irradiation boosted the HP decomposition rate. NF_TiO2 and Nb2O5-containing gels displayed higher ΔE00 and ΔWID when light-irradiated (p < 0.05). Nb2O5 and Nb2O5 + TiO2 decreased enamel SH (p < 0.05), but no SH changes were found among the groups (p > 0.05). No differences among groups were noted in ∆Ra, Ca-P content, and enamel morphology after treatments (p > 0.05).
Conclusion
Experimental light-irradiated 6% HP gels containing NF_TiO2 or Nb2O5 were chemically stable and exhibited bleaching potential comparable with 35% HP.
Clinical Relevance
Low-concentrated HP experimental gels stand as a possible alternative to in-office bleaching.
Production and hematological parameters of heifers ½ Angus ½ Nellore raised in integrated livestock-forestry system
Authors: Gonçalves Juliene Cruz , Andrighetto Cristiana , Mateus Gustavo Pavan , Simiele Carolina Barone , Sekiya Bianca Midori Souza , Duarte Julia Paschoareli Ferro , Oba Eunice , Dias Beatriz Poletto Neris , Silva Ben Yur Aparecido da , Martinez Edgar Ramos , Oliveira Juliana Moura , Gonela Renan Fabrício
Published: April 2023

The objective of this study was to evaluate the effect of integrated livestock-forestry system (ILF) in the performance, thermal comfort, hematological and hormonal parameters of ½ Angus ½ Nellore heifers, in summer. Thirty-two heifers were distributed in randomized block design with two treatments and four replications. The treatments were: CPS: Conventional pasture system without trees; ILF: integrated livestock-forestry system with eucalyptus planted in triple lines (386 eucalyptus ha− 1). Forage dry mass (FDM), bromatological and morphological analysis of Marandu palisadegrass, animal performance, ambient temperature (TA), relative humidity (RH), and humidity index (THI), respiratory rate (RR), blood count and hormonal parameters were evaluated. FDM, stem, senescent material and dry matter were lower in the ILF (P < 0.05). The crude protein was high in ILF (P < 0.05). There were no significant difference for final weight and average daily gain between treatments (P > 0.05). The stocking rate and weight gain per area were higher in CPS (P < 0.05). The TA, RH, THI and RR were better in the ILF (P < 0.05). The leukocytes and albumin were higher in the ILF (P < 0.05). There were no significant difference between the treatments for T3, T4 and cortisol (P < 0.05). The ILF reduces FDM depending on shading and promotes relevant changes in the morphological and bromatological composition, but it is not able to change the performance of heifers. The arboreal component improves the thermal comfort indexes, which is reflected in the RR and in the greater number of leukocytes and albumin, showing that ILF is important for the heifers welfare.
A Comparative Study of Machine Learning Algorithms for Predicting Domestic Violence Vulnerability in Liberian Women
Authors: Rahman Riaz , Khan Md. Nafiul Alam , Sara Sabiha Shirin , Rahman Md. Asikur , Khan Zahidul Islam
Published: April 2023

Domestic violence against women is a prevalent issue in Liberia, with nearly half of women reporting physical violence. However, research on the biosocial factors contributing to this issue remains limited. In this study, we aim to predict women's vulnerability to domestic violence using a machine learning approach, leveraging data from the Liberian Demographic and Health Survey (LDHS) conducted in 2019–2020. To achieve this goal, we employed seven different machine learning algorithms, including ANN, KNN, RF, DT, XGBoost, LightGBM, and CatBoost. Our analysis revealed that the LightGBM and RF models achieved the highest accuracy in predicting women's vulnerability to domestic violence in Liberia, with accuracy rates of 81% and 82%, respectively. One of the key features identified across multiple algorithms was the number of people who had experienced emotional violence. These findings offer important insights into the underlying characteristics and risk factors associated with domestic violence against women in Liberia. By utilizing machine learning techniques, we can better predict and understand this complex issue, ultimately contributing to the development of more effective prevention and intervention strategies.
Network model to optimize the process of green environmental features and urban building recognition based on lightweight image search system
Authors: Huang Haibo
Published: April 2023

To promote the development of a green environment, it is necessary to build a friendly environment for green travel and increase the use of green resources.Methods based on remote sensing image processing and feature analysis have become one of the main ways to obtain ground information, and have been widely used and promoted.Therefore, ground targets the accuracy of object recognition and features have been significantly improved. In the lightweight image of the city, the terrain occupies almost 80% of the buildings and roads. Urban buildings play an important role in supporting the operation, management and planning of the city. An important technology for the construction of digital towns in the future is the city. Building identification, therefore, the research of building identification is more important in the development of the city. With the widespread application of artificial intelligence deep learning and the popularization of smart technologies, the digital images generated by the Internet and mobile smart terminals have exponentially increased. Image data provides users with a comfortable experience and convenient services, but it also brings many challenges. How to filter out the photos we are interested in from a large amount of image data and find the content we need is a data difficulty. In computer vision research, image search systems can solve the problem of searching for the same content in many digital images. This paper applies deep learning and lightweight images to search systems to promote the development of urban building recognition.
Design of artificial intelligence cultural creative industry based on machine learning
Authors: Zhao Zhice , Zhang Lei
Published: April 2023

At present, social production and people's lifestyle have been revolutionized and globally affected by the rapid development of artificial intelligence technology. This technology has been reasonably applied in many fields, such as medical treatment, economy, transportation and manufacturing, so it has been unanimously recognized and supported by the market, society and the government. At the same time, artificial intelligence is more and more applied to the field of cultural industry, which brings a new development model of cultural design creative industry and promotes its production and management reform. Based on this point, this paper focuses on the practical problems in the process of small sample single label classification of cultural and creative product images, comprehensively establishes the mainstream machine learning model, and classifies DPM data with mechanical transfer learning algorithm. From the experimental data, the prediction accuracy of the resnet50 model is 87%. Not only that, this paper also proposes a multi feature algorithm by integrating machine learning and deep learning technology, in order to solve the problem of differences between large and small types of cultural and creative products. The algorithm can combine convolution calculation and point combination for learning, so as to further improve the accuracy. Finally, it can realize that the accuracy is 5% higher than DPM data set, which is conducive to the development of cultural and creative industries. Through the in-depth analysis of artificial intelligence, it is found that the technical level of artificial intelligence needs to be improved at this stage, and there are limitations in its application; Artificial intelligence laws and regulations are imperfect and information protection is misplaced; Artificial intelligence technology is easy to be overused, which affects the healthy development of cultural industry and leads to public opinion. This paper applies machine learning and artificial skill technology to the field of cultural and creative design, so as to promote the development of cultural and creative industry.
Application of edge computing and APP Software Services in Graphic Product Art Design
Authors: Hu Haoqi , Fu Meng , Wang Fan
Published: April 2023

The design of a green city needs to improve energy efficiency and urban greening rate, and plan public green spaces in places with good natural conditions and reasonable structures.With the rapid development of embedded technology and embedded APP software services, the application range of software maintenance systems has become more and more extensive, and it has also stimulated the increasing demand for embedded software. Improve the efficiency of embedded software development, reduce complexity, cost and development cycle, and apply component-based software development technology. These are very suitable for embedded system development. Component technology is the main form of current software development, which has the characteristics of reusability, packaging and assembly. It also expands Lw CCM, component model and component container. This article analyzes the product graphic design process, and designers choose appropriate design software to improve work efficiency when performing product graphic design. The application of design software in the product design process is mainly According to the specific characteristics of forward design and reverse design. The difference is that a product with a relatively simple structure uses 3D software to design the product in the direct design process, while a product with a relatively complex and cumbersome structure uses plane software to design the product in the reverse design process. Therefore, this article uses mobile edge technology to learn the application of APP software and the art design of graphic products.
Assessing Ergonomic-Deviations in the Existing Configurations of Controls and Display Units in Locomotives of Indian Railways
Authors: Danda Subir , Sarkar Soumya , Bepari Bikash , Saha Kalyan Brata , Lahiri Balendra Nath
Published: April 2023

Train driving is a complex task, requires prompt decision making based on external and internal information received. Therefore, spatial arrangement of control and display units and their labelling play vital roles to facilitate safe driving. This study was initiated on WAG7 (Old Variant modeled) goods locomotives. The Indian Railways having a very good number of fleets of such locos to take up this research. The ambience within the workstation and arrangement of controls were recorded video-graphically for subsequent analysis. In addition to many other elements of job or tasks, loco pilots remain engaged to operate few controls by reading various operational parameters on different display units. Within the fleet, deviations in placement of the display units, indicating lack of standard practices, had been noticed. Visibility of such units was found inadequate. Labelling of instruments, appeared to have been done un-attentively/ lackadaisically, bearing the signature of untrained hands. Investigation revealed that controls and display units were not configured ergonomically; therefore, proper location, size selection and labelling of such instruments are suggested to be standardized for their easy identification and error-free reading. Discussion with workers revealed that the importance of labelling and coding system is not clear to those who maintain the locomotives in sheds/workshops.
Analysis of the microbial community diversity in various regions of the healthy oral cavity
Authors: Liu Yuchang , Qiao Feng , Meng Ge , Gu Yeqing , Wu Hongmei , Liu Dayong , Niu Kaijun
Published: April 2023

Background: To investigate the differences in microbial colony distribution in different parts of a healthy oral cavity.
Methods: We assessed four sites and two methods for sampling the bacterial community of healthy individuals, and identified the colonization of bacteria on the tooth surface and buccal mucosa. Specifically, we analyzed buccal mucosa (n=10) and tooth surface (n=20) samples from healthy individuals using 16S rDNA gene sequencing. Additionally, we detected bacterial signals in healthy individuals through fluorescence in situ hybridization (FISH), which targeted the bacterial 16S rDNA gene.
Results: The results indicate that there are no significant differences between the buccal mucosa and tooth surfaces in normal individuals. However, when detecting disease-associated pathogens such as Enterococcus faecalis and Porphyromonas gingivalis, it is important to use different methods and specific sampling sites. The statistics suggest that although there were no significant differences in colony composition, there were differences in the abundance and distribution of colonies on the dental and buccal mucosal surfaces. Compared to right tooth sampling with a curette, the swab sampling group had higher levels of Firmicutes, while Fusobacteria and Bacteroidetes were more prevalent in the curette tissues.
Conclusions: These data provide a different perspective for future investigation on healthy people’s bacterial distribution. In normal individuals, there is no difference in the bacterial composition of the oral buccal mucosa and the dental surface, differing only in abundance. Thus, the buccal mucosa can ask as a substitute for the teeth in epidemiological investigations exploring the bacterial composition of the oral cavity.
The Depression Anxiety Stress Scale 8: Investigating its cutoff scores in relevance to loneliness and burnout among dementia family caregivers
Authors: Ali Amira M. , Alkhamees Abdulmajeed A. , Al-Dwaikat Tariq N. , Khatatbeh Haitham , Al-Dossary Saeed A.
Published: April 2023

The Depression Anxiety Stress Scale 8-items (DASS-8) is a brief form of the DASS-21, which demonstrated adequate psychometrics relative to the parent scale in many studies. Aiming to determine an optimal cutoff score of the DASS-8, we recruited a convenient sample of 571 European caregivers (Mean age = 53 ± 12 years, Italian = 74.4%, Swiss = 25.6%). K-means clustering classified the sample into high- and low-distress clusters based on DASS-8 score of 19. Based on score of 48 and 7 of the Zarit Burden Interview (ZBI) and the Three-Item University of California, Los Angeles, Loneliness Scale-version 3 (UCLALS3), receiver operator curve (ROC) analysis revealed an optimal cutoff point of 12.5 and 14.5 (area under the curve (AUC) = 0.85 & 0.92, p values = 0.001, 95% CI: 0.82–0.88 & 0.89 to 0.94, sensitivity = 0.81 & 0.78, specificity = 0.76 & 0.89, Youden index = 0.57 & 0.67, respectively). Decision modeling revealed that DASS-8 scores of 9.5 and 14.5 can predict low and high ZBI and UCLALS3 categories, respectively. Based on the median cutoff of the DASS-8 (14.5), the prevalence of high distress in this sample was 50.8%. In path analysis, the ZBI, UCLALS3, care dependency, receiving help with caregiving, predicted distress, especially in older female spouse caregivers. A DASS-8 score of 14.5 can detect mental distress symptomatology and reflect key mental problems such as burnout and loneliness in this vulnerable group. Further diagnostic workup may confirm psycho-pathogenicity. More investigations in other countries and conditions are needed to confirm the validity of this score.
Art Design and Production Based on Artificial Intelligence and Improved Neural Network
Authors: Liao Zeming
Published: April 2023

The times are developing and society is progressing. In recent years, the level of random science and technology has been continuously improved, and the application of artificial intelligence technology has become more and more common in people's lives. The further combination of artificial intelligence and art design has also largely optimized the methods and expressions of art design. This article takes the decentralization of art design in the era of artificial intelligence as the main research object, and conducts an in-depth discussion and analysis of the performance and causes of art design, aiming to study the influence of artificial intelligence technology on the development of human art design in the future. This article first takes the causes of the decentralization phenomenon produced by art design as the research object, and conducts a specific analysis of the development of art design, including the extension of art design related to artificial intelligence technology, and the aesthetics of neural network technology to the public And how popular culture promotes the decentralized change of art design. Secondly, we analyzed the function and role of neural network technology in art design, and found that it not only provides a basis for the decentralization of art design, but also plays an important role in many different aspects of art design. The influence of centralization and spatial decentralization. Then, we also analyzed the specific impact of neural network intelligent technology on customer groups and customer thinking, as well as its specific embodiment in the content of art design. In the end, we came to the conclusion that although the communication method of artificial intelligence is conducive to the personalized development of art design in many aspects, it is influenced by the mass media and the specific mode of communication in the process of use, resulting in artificial intelligence technology in art. There is great innovation ability in design. Therefore, for professional art designers, they should not only complete their own commercial art design tasks, but also make contributions and efforts for the prosperity of art on this basis.
Application of Q-learning Virtual Network and Embedded Processor in Chinese English Translation Sentence Accuracy Analysis
Authors: CHEN Chen
Published: April 2023

The widely available data is exploding with the continuous development of the Internet, leading people to the era of big data. Nowadays, massive amounts of English information can generate information redundancy, which to some extent affects the user's information browsing and filtering process, and Chinese-English translation needs to be further improved in accuracy. Therefore, it is very important to summarize the information in English source text and accurately translate it into Chinese to help people effectively and quickly grasp the key points and basic knowledge of English articles, among which satisfying sentence accuracy is the most important. Based on this point, this article proposes a new type of Chinese-English translation system, which is equipped with a Q-learning virtual network and built-in processor. With the development of recent years, language recognition technology has become increasingly mature. In a sense, this technology can be said to be the "cornerstone" of fully realizing artificial intelligence technology. Nowadays, the background of embedded processor based language recognition systems is microprocessor platforms (such as chips), which can create language training models in language databases, and can match the models with speech fragments to be tested to complete recognition. In particular, recognizing non specific language has evolved from a laboratory environment to become increasingly practical. This paper designs and implements a class of Chinese-English translation systems based on embedded processors and Q-learning algorithms to optimize system speed and achieve efficient and convenient system processing.
Developing a Simple Conceptual Model for Predicting Early Recurrence and Mortality after Curative Surgery for Colorectal Cancer Patients
Authors: mahmoudi leila , Alinia Shayeste , Ahmadi Samira , Mohammadi Zahra , shirvandeh Farzaneh Rastkar , Asghari-Jafarabadi Mohammad , Safari Malihe , Roshanaei Ghodratollah
Published: April 2023

Introduction: A generalized structural equation model with accelerated failure time for survival analysis in predicting early recurrence and mortality following curative surgery in colorectal cancer patients.
Methods: This retrospective cohort study included 284 patients with colorectal cancer who underwent surgery at Imam Khomeini Clinic in Hamadan between 2001 and 2017. Demographic and other relevant data were extracted from patient records, including age at diagnosis, sex, clinical and pathological variables, first treatment type and date, tumor differentiation degree, disease stage, and treatment types (surgery, chemotherapy, and radiotherapy). Predictors were included in a generalized structural equation model for survival analysis with an accelerated failure time (AFT) model, and both unadjusted and adjusted time ratios (TRs) were calculated.
Results: The study findings indicate that patients who did not receive chemotherapy had a lower survival time ratio [TR=0.443, 0.307 - 0.637], and those who underwent multiple chemotherapy sessions had an increased survival time [TR=2.007, 1.690 - 2.383]. Female patients had longer survival times than male patients [TR=1.137, 0.981- 1.318]. Additionally, disease progression to higher stages was associated with a decrease in survival times [TR=0.433, 0.348- 0.539].
Conclusion: According to the optimal model, age, number of chemotherapy sessions, and disease stage were found to have a significant relationship. Therefore, regular screening and preventive measures are recommended for target groups to help identify and manage colorectal cancer early and potentially improve patient outcomes.
An application of stereo matching algorithm based on transfer learning on robots in multiple scenarios
Authors: Bi Yuanwei , Li Chuanbiao , Wang Guohui
Published: April 2023

Robot vision technology based on binocular vision has significant potential for development in various fields, including 3D scenes and reconstruction, target detection, autonomous driving, and other fields. To date, current binocular vision methods used in robotics engineering suffer from high costs, complex algorithms, and low reliability of the generated disparity map in multiple scenarios. Robots require a cost-effective algorithm with cross-domain generalization capabilities for multiple scenarios. To address these issues, a cross-domain stereo matching algorithm for binocular vision based on transfer learning was proposed in this paper, named Cross-Domain Adaptation and Transfer Learning Network (Ct-Net), which has shown valuable results in multiple robot scenes. First, this paper introduces a General Feature Extractor (GFE) to extract rich general feature information for domain adaptive stereo matching tasks. Then, a feature adapter is used to adapt the general features to the stereo matching network. Furthermore, a Domain Adaptive Cost Optimization Module (DACOM) was designed to optimize the matching cost. A disparity score prediction module was also embedded to adaptively adjust the search range of disparity and optimize the cost distribution. The overall framework was trained using a phased strategy, and ablation experiments were conducted to verify the effectiveness of the training strategy. On KITTI 2015 benchmark, compared with the prototype PSMNet, the 3PE − fg of Ct-Net in all regions and non-occluded regions decreased by 19.3% and 21.1% respectively. On the Middlebury dataset, the 2PE of Ct-Net achieved comparable results on all samples. The quantitative and qualitative results obtained from Middlebury, Apollo, and other datasets demonstrate that Ct-Net significantly improves the cross-domain performance of stereo matching. Stereo matching experiments in real-world scenarios have shown that it can effectively address visual tasks in multiple robot scenes.
Improvement of Image Quality in Low-Count Bone Scintigraphy Using Deep Learning
Authors: Murata Taisuke , Onoguchi Masahisa , Hashimoto Takuma , Shibutani Takayuki , Iimori Takashi , Sawada Koichi , Umezawa Tetsuro , Masuda Yoshitada , Uno Takashi
Published: April 2023

Objective To improve image quality for low-count bone scintigraphy whole-body images using deep learning and evaluate their applicability in clinical practice.Methods Five hundred fifty patients were included in the study. Low-count Original images (75%, 50%, 25%, 10%, and 5% counts) were generated from Reference images (100% counts) using Poisson resampling. Patients were randomly divided into training (500) and evaluation (50) groups. Output (DL-filtered) images were obtained after training with U-Net using Reference images as teacher data. Gaussian-filtered images were generated for comparison. Peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) to the Reference image were calculated to determine image quality. Artificial neural network (ANN) value, bone scan index (BSI), and number of hotspots (Hs) were computed using BONENAVI analysis for patients with and without bone metastases, to assess diagnostic performance. Accuracy of bone metastasis detection and area under the curve (AUC) were calculated. Original, Gaussian-filtered, and DL-filtered images were compared with Reference images.Results PSNR and SSIM for DL-filtered images were highest in all count percentages. BONENAVI analysis values for DL-filtered images did not differ significantly regardless of the presence or absence of bone metastases. BONENAVI analysis values for Original and Gaussian-filtered images differed significantly at < 25% counts in patients without bone metastases. In patients with bone metastases, BSI and Hs for Original and Gaussian-filtered images differed significantly at < 10% counts, whereas ANN values did not. Accuracy of bone metastasis detection was highest for DL-filtered images in all count percentages; AUC did not differ significantly. Accuracy of Original and Gaussian-filtered images worsened with decreasing count percentage; AUC differed significantly for Original images at < 50% counts and for Gaussian-filtered images at < 25% counts.Conclusions Our deep learning model improved image quality and bone metastasis detection accuracy for low-count bone scintigraphy whole-body images, suggesting its applicability in clinical practice.
PI-RADS-based segmented threshold of PSMA-PET SUVmax is better than traditional fixed threshold for diagnosing clinically significant prostate cancer especially for PI-RADS 3 lesions
Authors: Meng Xiaoli , Ma Wenhui , Zhang Jingliang , Quan Zhiyong , Zhang Mingru , Ye Jiajun , Shu Jun , Ren Jing , Qin Weijun , Kang Fei , Wang Jing
Published: April 2023

Purpose Our purpose was to compare the performance of prostate-specific membrane antigen (PSMA)-positron emission tomography (PET) traditional fixed threshold (FT) and newly-established Prostate Imaging Reporting and Data System (PI-RADS)-based segmented threshold (ST) for diagnosing clinically significant prostate cancer (csPCa).Methods The study retrospectively included 218 patients who underwent multiparametric magnetic resonance imaging (mpMRI) and PSMA-PET examination for suspected prostate cancer (PCa) from January 2018 to November 2021. Lesions with Gleason score (GS) ≥ 3 + 4 were diagnosed as csPCa. In PSMA-PET maximum standardized uptake value (SUVmax), the FT for all the lesions and ST for lesions with different PI-RADS score for diagnosing csPCa were determined by receiver operating characteristic (ROC) curves analysis and compared with Z test. The McNemar test was used to compare sensitivity and specificity.Results Among the 218 patients, there were 113 csPCa and 105 non-csPCa. The PSMA-PET FT was SUVmax > 5.3 (area under the curve, AUC = 0.842) and STs for PI-RADS 3/4/5 were SUVmax > 4.2/5.7/6.0 (AUCs = 0.870/0.867/0.882), respectively. The AUC of PSMA-PET ST was higher than that of PSMA-PET FT (0.872 vs. 0.842), especially for PI-RADS 3 (0.870 vs. 0.653). Multimodality diagnostic criteria combining PSMA-PET ST and PI-RADS scores of mpMRI was established and its AUC was higher than that of PSMA-PET ST (0.893 vs. 0.872), and significantly higher than that of PSMA-PET FT (0.893 vs. 0.842) with an improvement in sensitivity (93% vs. 78%, p < 0.05) without significantly sacrificing specificity (86% vs. 91%, p > 0.05).Conclusions For diagnosing csPCa, PI-RADS-based PSMA-PET ST achieved better performance than traditional FT, especially for PI-RADS 3 lesions.
Pre-deformation effect on the hot deformation behavior and microstructure of AA6011 Tube: experimentation and modelling
Authors: Bao Zhennan , Qu Shuguang , Liang Jiayu , Yang Song , Zheng Kailun , Fu Kunning , He Zhubin
Published: April 2023

Hot gas forming (HGF) is an advanced technique for fabricating complex-shaped hollow tubular parts. Practically, multi-step pre-forming involving pre-deformation is often necessary prior to HGF. This paper performs an experimental investigation to simulate the pre-forming operation evaluating the effect of pre-strain on the subsequent HGF. Firstly, the dislocation density was accumulated with uniaxial pre-stretching with different strains (5%, 10% and 15%) at room temperature, simulating the pre-forming operations. Secondly, the sub-sized specimen from the pre-stretched sample was characterized at different temperatures (350, 400 and 450 ℃) to evaluate the effect of pre-strain on successive hot deformation for simulating practical HGF. The experimental results proves the coupled influence of pre-strain and temperature on the flow stress and stress-strain variations. To thoroughly understand the micro-mechanisms, EBSD analysis of grains and grain boundary angles was carried out under different pre-deformation levels and temperatures, which shows the recrystallization phenomenon at 15% pre-strain and 450 ℃ temperature. Finally, a physical-mechanism constitutive model is established based on the determined macro and micro results where the pre-strain effect shows the accurate modeling of stress flow behavior of the material.
Noninvasive prediction for intracranial pressure related parameters in traumatic brain injury patients using computed tomography radiomic features.
Authors: Li Yihua , Shan Yingchi , Zhu Jun , Wu Xiang , Gao Guoyi
Published: April 2023

Background: Current intracranial pressure (ICP) related parameters monitoring is invasive and tends to cause complications, which limited their use to predict patients’ intracranial status and prognosis.Objective: To utilize postoperative computed tomography (CT) images radiomic features techniques to predict abnormal ICP related parameters levels consisting of an index of cerebrospinal compensatory reserve(RAP) and a pressure reactivity index (PRx)in traumatic brain injury (TBI) patients noninvasively.Methods: 48 patients were enrolled and randomized to training (n=34) and test (n=14) sets. A total of 107 radiomic features were extracted from each patients’ CT image. Their clinical and imaging data was collected and analyzed to establish prediction models of RAP and PRx respectively. Pearson correlation and univariate regression analysis were used for feature selection, multivariate logistic regression was used to develop the predicting models. The performance of models was assessed with their discrimination, calibration and clinical use.Results: The RAP model showed a good discrimination with the area under receiver operating characteristic curve (AUC) of training and test set were 0.771 and 0.727, and a good calibration; The performance of PRx model was inferior to the RAP model, but still have a significant discrimination with the AUCs of training and test were 0.713 and 0.667. Decision curve analysis indicated the prediction model have the potential clinical utility.Conclusion: The study illustrated that CT radiomic features as a clinical aid may have ability to predict ICP related parameters to reflect the intracranial condition of TBI patients noninvasively, given its potential for clinical treatment guidance and prognosis indication.
Research of dry tribochemical mechanical polishing SiC with an innovation abrasive-catalytic abrasive cluster
Authors: wang zhankui , Ding Yangyang , Wang Pengzhan , Pang Minghua , Zhao Hongyuan , Ma Lijie , Nie Fuquan , Su Jianxiu
Published: April 2023

Abrasive particles have a crucial influence on the material removal rate and surface quality of the workpiece in tribochemical mechanical polishing. Therefore, this article selects a self-made catalytic abrasive cluster to polish the 6H-SiC and explore the removal mechanism of polishin silicon carbide in the new catalytic abrasive cluster. The tribochemical mechanical polishing test and friction and wear test of 6H-SiC were carried out with three different abrasives, and the evaluation parameters such as material removal rate, surface roughness and friction coefficient were obtained. Quanta 200 scanning electron microscope(SEM) and oxfobrdinca 250 energy dispersive spectrometer (EDS) and x-ray diffraction(XRD)diffractometer were used to observe the surface, analyze the elements and determine the composition of silicon carbide workpiece after tribochemical mechanical polishing. The experimental result shows that oxygen is produced in the tribochemical mechanical polishing of silicon carbide by catalytic abrasive cluster, which makes the silicon carbide surface generate SiO2 shear film that is easy to be removed. Comparing with iron-based white corundum mixed abrasive and Al2O3 abrasive, the catalytic abrasive cluster has better processability for 6H-SiC, and the material removal rate can reach to 42.928nm/min.
Correlation of MPO expression with 18F-FDG PET/CT parameters in patients with histiocytic necrotizing lymphadenitis
Authors: Song Yingjian , Tian Ke , Han Qingqing , Wang Ruihua
Published: April 2023

Objective: To investigate the relationship between the metabolic activity of 18F-FDG in histiocytic necrotizing lymphadenitis (HNL) and its immunophenotype.
Methods: Retrospective analysis of 76 patients with pathologically confirmed HNL who underwent 18F-FDG PET/CT prior to treatment. Maximum standardized uptake value (SUVmax)，metabolic tumor volume (MTV)，and total lesion glycolysis (TLG) were measured. Analysis of the correlation of each metabolic parameter with the expression status of myeloperoxidase (MPO). The differences of PET/CT metabolic parameters between different expression states of MPO were compared and the receiver operating characteristic (ROC) curve were plotted to obtain the best cut-off values of PET/CT metabolic parameters to predict MPO expression.
Results: 23 cases were negative for MPO expression, 16 cases were weakly positive for MPO expression, and 37 cases were positive for MPO expression. SUVmax , MTV and TLG were all associated with MPO expression status in HNL (P < 0.05). MPO expression status was positively correlated with SUVmax and TLG (P < 0.05). The ROC curves of 18F-FDG PET/CT metabolic parameters for predicting MPO expression showed that SUVmax and TLG were of predictive value, with the highest diagnostic efficiency, sensitivity of 91.9% and 86.5%, and specificity of 71.8% and 76.9% when the cut-off values were 10.90 and 37.1, respectively. Conclusion：18F-FDG PET/CT metabolic parameters, especially SUVmax and TLG, correlated well with MPO expression status. 18F-FDG PET/CT can be used as an imaging tool for non-invasive assessment of MPO immune expression.