bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Wireless Transmission System for Microseismicity in Complex Mountainous Area
Authors: Xie Qingming , Wu Chunling , Liao Hongliang , Chen Lichuan , Hu Yunbin , He Guilan , Kang Yueming
Published: June 2022

A large amount of data would be generated during the process of microseismic monitoring, and data transmission with the cable has some shortcomings such as poor anti-interference, time-consuming, laborious, high cost, and low construction efficiency. On the other hand, the influence of signal diffraction and the multipath effect will greatly cut down the energy of the signal during the wireless transmission in the complex mountainous area. The wireless transmission system based on Wi-Fi is designed in this paper, which includes the base station and data transceiver. The maximum distance and transmission rate at point-to-point communication of the base station are up to 1000 m and 150 Mbps, respectively, and it provides the communication backbone line for the network. The data transceiver adopts the network protocol based on Ad Hoc, and the transmission distance is up to 200 m at the condition of complex topography and lush mountains. We have applied the system to in-site microseismic monitoring with 28 geophones of the coalbed methane fracturing in South Chongqing. It achieved a good performance with a transmission rate of 1.2 Mbps, a time delay of 1.95 ms, and a signal strength of up to −52.3 dBm for real-time data transmission in the field. The results show that the system has the advantages of low BER, fast transmission speed, long communication distance, and stable and safety hardware and has a great value for more applications of microseismicity in complex topography.
Prediction of Solitary Plasmacytoma of Bone in Elderly Patients: A Nomogram and a Risk Classification System for Overall Survival
Authors: Zhang Xi , Yang Jiahao , Tian Zhuanhua , KHABIR YOUSSEF , Wang Dan
Published: June 2022

Background. Solitary plasmacytoma of bone (SPB) is an isolated plasmacytoma of bone origin, most commonly seen in the elderly, with a poor prognosis. So far, there is no precise nomogram to predict the overall survival (OS) of elderly patients with SPB. Our goal is to construct and validate a nomogram for elderly patients with SPB. Methods. This study collected all elderly patients with SPB in the Surveillance, Epidemiology and End Results (SEER) database from 2000 to 2018, and the variables included were age, sex, race, marital status, primary site, grade, stage, surgery, chemotherapy, and radiotherapy. Independent prognostic factors were identified using univariate and multivariate Cox analysis. The nomogram was constructed to predict 1‐, 2‐, and 3‐year OS of elderly patients with SPB. The receiver‐operating characteristic (ROC) and the calibration curves were used to differentiate and calibrate the nomogram. The clinical validity of the nomogram was evaluated by decision curve analysis (DCA). The total OS scores of all elderly SPB patients were calculated and divided into two risk subgroups for comparison. Results. A total of 1837 patients diagnosed with SPB were screened from the SEER database, with a final inclusion of 1180 patients (age ≥ 60 years). Age, radiotherapy, and marital status were significantly correlated with OS. These characteristics were further incorporated into the creation of the nomogram for predicting 1‐, 2‐, and 3‐year OS of elderly patients with SPB. For this predictive model, the area under the ROC curves, calibration curves, and DCA have good performance in terms of differentiation, consistency, and validity, respectively. In addition, patients in the high‐risk group (≥96) had a worse prognosis than those in the low‐risk group (<96). Conclusion. We constructed a nomogram and a risk classification system that could provide an intuitive and effective tool for clinicians to better predict the OS of elderly SPB patients.
Effect of Substrate Material on the Electromagnetic Properties of the Photolithography Printed Antenna
Authors: Balashanmugam Thiyaneswaran , Baladhandapani Aruna Devi , Selvakumaran Palanivel Rajan , Ramachandran Dhanagopal , Muthuvel Suresh Kumar , Sivaraj Priyadharshini , Mamo Samson Alemayehu
Published: June 2022

In this study, a rectangular microstrip feed antenna on a fire-retarded substrate is presented. The antenna is designed using Computer Simulation Tool (CST) software. Different materials are used for the substrate, and the electromagnetic properties of the proposed structure are analyzed for each material. The EM property variation for each material is comparatively presented. The proposed antenna has CSRR (Complementary Split-Ring Resonator) which is engraved on the radiating element, and the shape of the CSRR is the hexagon. The proposed metamaterial-inspired antenna exhibits multiband operation at 2.1 GHz, 2.6 GHz, 4.6 GHz, 5.5 GHz, 6.1 GHz, and 7.1 GHz. With the help of material analysis, the fire-retarded substrate is chosen for the design, its excellent EM properties, and cheap cost. The photolithography-based printed antenna is validated with the help of S11, VSWR, gain, directivity, surface current distribution, and radiation pattern. Simple, compact structure, good gain, stable radiation pattern, and excellent EM properties of the fire-retarded substrates make it suitable for the GHz application.
[Retracted] Applications of Deep Learning in the Evaluation and Analysis of College Students’ Mental Health
Authors: Zhou Lanfeng
Published: June 2022

It is an important research direction of mental health discipline in the current era to evaluate and analyze college students’ mental health by using deep learning methods and form visual data characteristics and analyzable discipline conclusions. Based on this, this paper carries out the research method of convolutional neural network by using the research concept of deep learning. Firstly, the paper summarizes the fast intelligent analysis model based on the convolutional neural network system algorithm, classifies and summarizes the unique characteristics of college students’ mental health, and uses the convolutional neural network processing model to analyze, evaluate, and observe college students’ mental health combined with the big data theory. Secondly, through the expansion and utilization of multi‐layer neuron self‐coding neural network, the psychological health of college students is evaluated and analyzed in the psychological discipline, the discrete data structure is established by using the relevant psychological data, the psychological behavior of college students is analyzed, summarized, and classified, and the data model is filled to judge the mental health status of college students. Finally, through the design of confirmatory experiments, the results show that the college students’ mental health evaluation and analysis model based on deep learning is more efficient in individual data analysis. Compared with the mode of analyzing college students’ mental health through in‐depth learning, the traditional psychological research method has a large workload and is not suitable for the universality and consistency of college students. This paper solves this problem and provides a reference for relevant research.
Knowledge and Awareness of Diabetes and Diabetic Retinopathy among Patients Seeking Eye Care Services in Madang Province, Papua New Guinea
Authors: Owusu-Afriyie Bismark , Caleb Anne , Kube Lorraine , Gende Theresa
Published: June 2022

Purpose. To assess the knowledge and awareness of diabetes and diabetic retinopathy among ophthalmic patients in Madang. Materials and Methods. This was a hospital-based study conducted at Madang Provincial Hospital Eye Clinic in Papua New Guinea. The study included all patients who visited the facility during the period of the study. A structured questionnaire was used to collect data on the patients’ demographics and their knowledge and awareness about diabetes and diabetic retinopathy. Results. A total of 203 (97.6%) patients consented and participated in the study out of 208 patients who were approached. The age of participants ranged from 19 to 78 years with a median (IQR) of 41 (53–29) years. 107 (52.7%) were female participants. A majority of the participants (62.6%) had at least secondary education. A few of the participants (3.9%) had known diabetes, and 134 (66%) had no relatives or friends with diabetes. A total of 145 (71.4%) participants knew that diabetes can affect the eye. Most of the participants (93.6%) checked their eyes only when their vision was affected, 161 (79.3%) agreed that regular eye checks are necessary, and more than half (54.2%) knew that diabetes can lead to blindness. Age, gender, level of education, and whether a participant or participant’s friends and relatives had been diagnosed with diabetes were significantly associated with the knowledge and awareness of participants about diabetes and diabetic retinopathy. Conclusion. A majority of the participants had good knowledge of diabetes and diabetic retinopathy. Health education and promotion will also help increase the awareness of diabetes and diabetic retinopathy in the country.
Barnacles Mating Optimizer with Deep Transfer Learning Enabled Biomedical Malaria Parasite Detection and Classification
Authors: Dutta Ashit Kumar , Mageswari R. Uma , Gayathri A. , Dallfin Bruxella J. Mary , Ishak Mohamad Khairi , Mostafa Samih M. , Hamam Habib
Published: June 2022

Biomedical engineering involves ideologies and problem-solving methods of engineering to biology and medicine. Malaria is a life-threatening illness, which has gained significant attention among researchers. Since the manual diagnosis of malaria in a clinical setting is tedious, automated tools based on computational intelligence (CI) tools have gained considerable interest. Though earlier studies were focused on the handcrafted features, the diagnostic accuracy can be boosted through deep learning (DL) methods. This study introduces a new Barnacles Mating Optimizer with Deep Transfer Learning Enabled Biomedical Malaria Parasite Detection and Classification (BMODTL-BMPC) model. The presented BMODTL-BMPC model involves the design of intelligent models for the recognition and classification of malaria parasites. Initially, the Gaussian filtering (GF) approach is employed to eradicate noise in blood smear images. Then, Graph cuts (GC) segmentation technique is applied to determine the affected regions in the blood smear images. Moreover, the barnacles mating optimizer (BMO) algorithm with the NasNetLarge model is employed for the feature extraction process. Furthermore, the extreme learning machine (ELM) classification model is employed for the identification and classification of malaria parasites. To assure the enhanced outcomes of the BMODTL-BMPC technique, a wide-ranging experimentation analysis is performed using a benchmark dataset. The experimental results show that the BMODTL-BMPC technique outperforms other recent approaches.
M
-Lump Solution, Semirational Solution, and Self-Consistent Source Extension of a Novel

2
+
1

-Dimensional KdV Equation
Authors: Hai Rihan , Gegen Hasi
Published: June 2022

In this paper, we derive the

M

-lump solution in terms of Matsuno determinant for the combined KP3 and KP4 (cKP3-4) equation by applying the double-sum identities for determinant and investigate the dynamical behaviors of 1- and 2-lump solutions. In addition, we derive the Grammian solution for the cKP3-4 equation and construct the semirational solutions from the Grammian solution. Through the asymptotic analysis, we show that the semirational solutions describe fusion and fission of lumps and line solitons and rogue lump phenomena. Furthermore, we construct the cKP3-4 equation with self-consistent sources via the source generation procedure and present its Grammian and Wronskian solution.
Strength and Durability Parameters of Brick Aggregate Concrete Incorporating Rice Husk Ash as a Partial Replacement of Cement
Authors: Noaman Md. Abu , Karim Md. Rezaul , Islam Md. Nazrul , Mia Md. Suman
Published: June 2022

This study assessed the strength and durability parameters of brick aggregate concrete (BAC) incorporating rice husk ash (RHA) as a partial replacement of cement. For this, concrete cylinders (100 mm × 200 mm) were made with 0% (control) to 25% RHA as a partial replacement of ordinary Portland cement (OPC) at a mix proportion of 1 : 1.5 : 3 and a water-to-binder (w/b) ratio of 0.50. Specimens were immersed separately in normal water, 3% sodium chloride (NaCl), 5% sodium sulfate (Na2SO4), 5% magnesium sulfate (MgSO4), 1% hydrochloric acid (HCl), and 1% sulfuric acid (H2SO4) solutions for several immersion periods. The slump test results indicated that the workability of BAC containing RHA (RBAC) decreased about 29.69%–75.02% compared to control (0% RHA). After 90 days, the BAC containing RHA (up to 15% replacement) was found approximately 2.28%–6.64% greater compressive strength than that of control concrete. In addition, water absorption and porosity of RBAC were around 17.59%–40.73% and 12.12%–35.68% lower than that of control concrete, respectively. Similarly, RBAC (up to 25% replacement) exhibited roughly 35.62%–54.79% higher resistance against chloride attack and 0.39%–4.56% better resistance against Na2SO4 attack (up to 15% replacement), however, it exhibited inferior resistance against MgSO4 attack compared to control. Meanwhile, BAC with 10% RHA showed about 5.35% and 1.00% superior performance than that of control concrete against HCl and H2SO4 attack, respectively. The relationships between the strength and durability parameters of RBAC also suggested that RHA contributes to improving the strength and durability parameters of BAC.
Real-Time Monitoring and Early Warning Algorithm of Ozone + Nitrogen Oxides in High-Density Residential Space Based on Big Data
Authors: Fang Yuan , Meng He , Xue Chuanwen , Wei Wei , Xue Lian
Published: June 2022

In order to monitor ozone and nitrous oxide pollutants in residential space, artificial intelligence algorithm is integrated on the basis of traditional monitoring mode. Through the comparison of system detection accuracy and early warning sensitivity of different detection methods, it can be seen that the application of artificial intelligence detection system can improve the monitoring performance of ozone and realize the timeliness of large-scale monitoring coverage and data update. The accuracy and sensitivity of system detection under the two detection methods are analyzed, and the main harm caused by ozone pollution is analyzed. The significance of monitoring ozone pollution in ambient air is emphasized. The air index of high-density residential space using intelligent big data detection method is obviously superior to previous detection methods in terms of timeliness, accuracy, and early warning sensitivity of the system. It also provides an important data reference for the real-time monitoring and early warning of ozone + nitrogen oxides in high-density residential space, and also makes an important contribution to reducing the impact on residents’ health and living environment.
Large-Scale Scheduling Model Based on Improved Ant Colony Algorithm
Authors: Zhao Suyao , Li Chengyi , Tian Mengmeng , Zhang Hengyuan , Xiao Zhixuan , Hu Runjiu
Published: June 2022

With the rapid development of the city, shared bicycle travel has also entered a stage of rapid development. In order to ensure the happiness of citizens traveling, in view of the current supply and demand resources and bicycle scheduling problems, a model of supply and demand resource forecasting and multisite and multivehicle scheduling are established. Supply and demand resource prediction uses characteristic variables based on the graph structure itself as input variables of the prediction model XGBoost (extreme gradient boosting). Combined with the actual situation, the improved ant colony algorithm is used to design a reasonable scheduling for the multisite and multivehicle routing problem (VRP). Using Xiamen City shared bicycle data for simulation training, the results show that the shared bicycle scheduling method proposed in this paper has strong robustness and rationality.
The Invasion and Metastasis of Colon Adenocarcinoma (COAD) Induced by SALL4
Authors: Zhang Wenjuan , Hu Yan , Zhang Wenbing , Yi Ke , Xu Xiaohui , Chen Zhihua
Published: June 2022

Objective. The development and progression of many cancers may be related to SALL4, the role and molecular mechanism of which are unclear in colon adenocarcinoma (COAD). Methods. The SALL4 expression in adjacent normal mucosa tissues and carcinoma tissues of patients with COAD was detected through bioinformatic analysis based on TCGA database and immunohistochemistry. Single-cell analysis showed that the expression of SALL4 in normal tissue was noticeably low. GSEA analysis suggested that the SALL4 upregulated the GO and pathway of growth and cancer development and downregulated metabolization pathway. The relationship between lymph node metastasis, histological grading, clinical staging, and the expression of SALL4 in carcinoma tissues was analyzed. The upregulated or downregulated SALL4 expression of COAD cell lines was established. The influence of SALL4 on COAD cells invasion and proliferation was detected using plate cloning assay and Transwell. The expressions of EMT-related proteins E-cadherin, N-cadherin, vimentin, and Twist were detected by Western blot. The EMT phenotype was analyzed by immunofluorescence. Results. The study confirmed that the expression of SALL4 was upregulated in COAD and positively correlated with the degree of tumor differentiation, tumor staging, and metastasis. The overexpression of SALL4 was related to a poor prognosis, promoted the invasion and proliferation of colorectal cancer cells, and accelerated the occurrence of EMT, which was characterized by upregulation of Twist, vimentin, and N-cadherin expressions and downregulation of E-cadherin. The immunofluorescence staining confirmed the EMT phenotype. On the contrary, knocking out SALL4 gene reversed EMT, weakened cell proliferation and invasion, inhibited upregulation of Twist, vimentin, and N-cadherin expressions and downregulation of E-cadherin. Conclusion. To sum up, TNM grading, histological grading, and lymphatic metastasis were significantly correlated with SALL4 in tumor tissues. SALL4 played a vital role in tumor proliferation, invasion, and tumor EMT and may be a novel target for COAD.
Biomedical Analytics of Four Chinese Medicinals in Treatment of Insomnia Based on Network Pharmacology
Authors: Deng Qiyue , Huang Libing , Yu Fanjun , Lin Jiahui , Hu Lijuan , Zhao Jing , Pan Litao , Kui Yu , Wu Shiheng
Published: June 2022

Aim. Our aim is to recommend the appropriate Chinese medicinals in clinical treatment of insomnia, which are suānzăorén (Semen Ziziphi Spinosae), chuānxiōng (Rhizoma Chuanxiong), fúlíng (Poria), and báisháo (Radix Paeoniae Alba). Method. Based on network pharmacology, the active molecules and mechanism of these four Chinese medicinals treating insomnia were sought and analyzed. The components of the four Chinese medicinals with potential activity were collected and screened. Moreover, the recollected human disease‐related targets were correlated through Cytoscape 3.8.2, and the network diagram of drug component disease targets was drawn. Based on the human protein‐protein interaction database, the above network diagram was imported to establish the protein‐protein interaction (PPI) and composite target pathway (C‐T‐P) networks. After selecting important information, the pathway analysis was carried out to show the biological process, core target, and core pathway of insomnia treatment. Result. In this study, 44 active components and 81 drug‐disease common targets were obtained; 307 key targets were found in the PPI network; a core cluster composed of 14 nodes and 50 functional associations was found. Conclusion. In summary, the four Chinese medicinals’ effective components and main mechanism of in the treatment of insomnia may be related to their participation in the regulation of endocrine. Compared with the existing network pharmacological analysis results of SuānZăoRénTāng (Sour Jujube Decoction), which is commonly used in insomnia, they have similar effects on the immune system and HPA axis, while the focus of the four Chinese medicinals is mainly on endocrine regulation, and SuānZăoRénTāng (Sour Jujube Decoction) is mainly on anti‐inflammatory effect.
Reliability Analysis of Hybrid System Using Geometric Process in Multiple Level of Constant Stress Accelerated Life Test through Simulation Study for Type-II Progressive Censored Masked Data
Authors: Kamal Mustafa , Khan Shahnawaz , Rahman Ahmadur , Aldallal R. A. , El-Raouf M. M. Abd , Muse Abdisalam Hassan , Rabie Abdalla
Published: June 2022

Numerous studies have already been attempted to explore the reliability of systems considering mask data, though the mass of them has largely focused on basic series or parallel systems, where component failures are assumed to follow an exponential or Weibull distribution. However, most electrotonic products and systems are made up of numerous components integrated in parallel-series, series-parallel, and other bridge hybrid structures, and the number of studies in the area of accelerated life testing (ALT) employing masked data for hybrid systems is limited. In this paper, the constant-stress ALT (CSALT) is explored based on type-II progressive censoring scheme (TIIPCS) for a four-component hybrid system using geometric process (GmP). The failure times of the components of the system are assumed to follow the generalized Pareto (GP) distribution. The maximum likelihood estimate (MLE) technique is used to establish statistical inference for the model's unknown parameters under the premise that the failure reasons are unknown for the hybrid system. In addition, the asymptotic confidence intervals (ACIs) are also obtained by inverting the fisher information matrix. Finally, a simulation study is given to explain the proposed techniques and to evaluate the performance of the estimates. The performance of MLEs is assessed in terms of root mean square errors (RMSEs) and relative absolute biases (RABs), whereas the performance of ACIs is assessed in terms of their interval length (IL) and coverage probabilities (CPs). The findings show that the technique can deliver good estimation performance with small and intermediate sample sizes, and the estimates are more accurate when more failures are observed, showing the estimation method's efficiency.
Design of Sports Training Simulation System for Children Based on Improved Deep Neural Network
Authors: Wang Xuesheng , Han Qiuhong , Gao Feng
Published: June 2022

With the development of AI technology, human-computer interaction technology is no longer the traditional mouse and keyboard interaction. AI and VR have been widely used in early childhood education. In the process of the slow development and application of voice interaction, visual interaction, action interaction, and other technologies, multimodal interaction technology system has become a research hotspot. In this paper, dynamic image capture and recognition technology is integrated into early childhood physical education for intelligent interaction. According to the basic movement process and final node matching in children’s sports training to judge children’s physical behavior ability, attention is paid to identify the accuracy and safety of movement. The input images and questions are from the abstract clipart dataset of dynamic image recognition and the self-made 3D dataset of Web3D dynamic motion scene with the same style, which is similar to the action content in the actual preschool training teaching. Therefore, according to the idea of process capture and target recognition, on the basis of the original conditions of the recognition model, a new recognition model is developed through Zheng’s target detector. The modified model is characterized by higher accuracy. Weapons need to combine process recognition and result recognition. The experimental results show that the improved model has the obvious advantages of high precision and fast speed, which provides a new research idea for the development of children's physical training simulation.
Anticardiolipin Autoantibodies as Useful Biomarkers for the Prediction of Mortality in Septic Patients
Authors: Abouda Amal , Hajjej Z. , Mansart A. , Kaabechi W. , Mahmoud D. Elhaj , Lamine O. , Ghazouani E. , Ferjani M. , Labbene I.
Published: June 2022

Background. The detection of antiphospholipid antibodies (aPL) is of interest because of their importance in the pathogenesis of arterial or venous thrombosis. They could be a “second hit” of an inflammatory event such as infection. The aim of our study was to assess the performance of antiphospholipid antibody biomarker to predict in-hospital mortality in intensive care unit (ICU) septic patients. Methods. We conducted a prospective single-center observational study including consecutive critically ill septic adults admitted to the intensive care unit. Clinical and laboratory data including enzyme-linked immunosorbent assay for antiphospholipid antibodies (anticardiolipin (aCL), antiphosphatidylserine (aPS)) were obtained. Blood samples were collected on days 1, 3, 5, 8, and 10 of hospitalization. The primary study endpoint was ICU mortality defined as death before ICU discharge. Secondary end points included correlation between SOFA score and biological parameters. Results. A total of 53 patients were enrolled. 18.8% of patients were aPL positive. In-hospital mortality rate was 60%. Multivariate analysis showed that age and aCL at days 3 and 5 along with SOFA at day 3 were independent outcome predictors. A significant positive correlation existed between SOFA at days 3, 5, and 8 and antiphospholipid antibody concentrations. Conclusions. Our data showed that antiphospholipid was useful biomarkers for the prediction of mortality in critically ill septic patients. We found a positive correlation between SOFA score and antiphospholipid antibodies.
A Quantitative Model of International Trade Based on Deep Neural Network
Authors: Huang Xiaoxin , Chen Xiuxiu
Published: June 2022

This paper is an in-depth study of international trade quantification models based on deep neural networks. Based on an in-depth analysis of global trade characteristics, a summary of existing problems, and a comparative analysis of various prediction methods, this paper constructs the ARIMA model, BP neural network (BPNN) model, and deep neural network (DNN) model to make a comprehensive comparison of international trade quantification. The results show that the nonlinear model has a global trade quantification has some advantages over linear models, and the deep model shows better prediction performance than the shallow model. In addition, preprocessing of the time series is considered to improve the prediction accuracy or shorten the model training time. The empirical modal analysis method (EMD) is introduced to decompose the time series into eigenmodal functions (IMFs) of different scales. Then the decomposed IMF series are arranged into a matrix using principal component analysis (PCA) to reduce the dimensionality and extract the data containing the most stock index information features; these features are then input into BPNN and DNN for combined prediction, thus constructing the combined models EMD-PCA-BPNN and EMD-PCA-DNN. Based on Melitz’s heterogeneous firm trade theory and its development by Chaney, a quantitative trade model incorporating production heterogeneity is constructed through a multisector extension. This paper adopts a general equilibrium analysis, which makes the modeling process pulse clear. The completed model has high flexibility and scalability, which can be applied to quantitative analysis of various problems.
Combining BERT Model with Semi-Supervised Incremental Learning for Heterogeneous Knowledge Fusion of High-Speed Railway On-Board System
Authors: Zhou Lu-jie , Zhao Zhi-peng , Dang Jian-wu
Published: June 2022

On-board system fault knowledge base (KB) is a collection of fault causes, maintenance methods, and interrelationships among on-board modules and components of high-speed railways, which plays a crucial role in knowledge-driven dynamic operation and maintenance (O&M) decisions for on-board systems. To solve the problem of multi-source heterogeneity of on-board system O&M data, an entity matching (EM) approach using the BERT model and semi-supervised incremental learning is proposed. The heterogeneous knowledge fusion task is formulated as a pairwise binary classification task of entities in the knowledge units. Firstly, the deep semantic features of fault knowledge units are obtained by BERT. We also investigate the effectiveness of knowledge unit features extracted from different hidden layers of the model on heterogeneous knowledge fusion during model fine-tuning. To further improve the utilization of unlabeled test samples, a semi-supervised incremental learning strategy based on pseudo labels is devised. By selecting entity pairs with high confidence to generate pseudo labels, the label sample set is expanded to realize incremental learning and enhance the knowledge fusion ability of the model. Furthermore, the model’s robustness is strengthened by embedding-based adversarial training in the fine-tuning stage. Based on the on-board system’s O&M data, this paper constructs the fault KB and compares the model with other solutions developed for related matching tasks, which verifies the effectiveness of this model in the heterogeneous knowledge fusion task of the on-board system.
Structural Racism and Cancer: Calls to Action for Cancer Researchers to Address Racial/Ethnic Cancer Inequity in the United States
Authors: Best Alicia L. , Roberson Mya L. , Plascak Jesse J. , Peterson Caryn E. , Rogers Charles R. , Hastert Theresa A. , Molina Yamilé
Published: June 2022

As leaders with the American Society of Preventive Oncology (ASPO) Cancer Health Disparities Special Interest Group, we describe the role of structural racism in perpetuating cancer health inequity historically, and potential implications of COVID-19 in exacerbating the effects of structural racism on patients with cancer seeking screening, diagnostic care, treatment, and survivorship support. As a strategy to reduce cancer inequities in the United States, we provide the following calls to action for cancer researchers to help alleviate the burden of structural racism: (i) identify and name structural racism while describing its operation within all aspects of scientific research; (ii) comprehensively integrate discussions on structural racism into teaching, mentoring, and service activities; and (iii) understand and support community actions to address structural racism.
Cancer Screening Companies Are Rapidly Proliferating: Are They Ready for Business?
Authors: Fernandez-Uriarte Amaia , Pons-Belda Oscar D. , Diamandis Eleftherios P.
Published: June 2022

Cancer screening has been a major research front for decades. The classical circulating biomarkers for cancer (such as PSA, CEA, CA125, AFP, etc.) are neither sensitive nor specific and are not recommended for population screening. Recently, circulating tumor DNA (ctDNA) emerged as a new pan-cancer tumor marker, with much promise for clinical applicability. ctDNA released by tumor cells can be used as a proxy of the tumor burden and molecular composition. It has been hypothesized that if ctDNA is extracted from plasma and analyzed for genetic changes, it may form the basis for a non-invasive cancer detection test. Lately, there has been a proliferation of “for-profit” companies that will soon offer cancer screening services. Here, we comment on Grail, Thrive, Guardant, Delfi, and Freenome. Previously, we identified some fundamental difficulties associated with this new technology. In addition, clinical trials are exclusively case–control studies. The sensitivities/specificities/predictive values of the new screening tests have not been well-defined or, the literature-reported values are rather poor. Despite these deficiencies some of the aforementioned companies are already testing patients. We predict that the premature use of ctDNA as a cancer screening tool may add another disappointment in the long history of this field.
Criteria for Acceptable Dietary Intake Biomarkers
Authors: Prentice Ross L.
Published: June 2022

Dietary intake biomarkers that can be written as actual intake, plus ‘error’ that is independent of actual intake and confounding factors can substitute for actual intake in disease association analyses. Also, such biomarkers can be used to develop calibration equations using self-reported diet and participant measures, and biomarker-calibrated intakes can be calculated in larger cohorts for use in disease association analyses. Criteria for biomarkers, and for biomarker-calibrated intakes, arise by working back from properties needed for valid disease association analyses. Accordingly, arguments for a potential biomarker are strengthened if error components are small relative to actual intakes, and important sources of reduced sensitivity or specificity are not apparent. Feeding study biomarker development can then involve regression of actual intake on putative biomarkers, with regression R2 values playing a role in biomarker evaluation. In comparison, ‘predictive’ biomarker status, as argued in this issue by Freedman and colleagues for 24-hour urinary sucrose plus fructose as biomarker for total sugars, involves regression of potential biomarker on actual intake and other variables, with parameter stability across populations and limited within-person variability as criteria. The choice of criteria for biomarkers and for biomarker-calibrated intakes, is discussed here, in the context of total sugars intake.

See related article by Freedman et al., p. 1227
ABBV-011, A Novel, Calicheamicin-Based Antibody–Drug Conjugate, Targets SEZ6 to Eradicate Small Cell Lung Cancer Tumors
Authors: Wiedemeyer Wolf R. , Gavrilyuk Julia , Schammel Alexander , Zhao Xi , Sarvaiya Hetal , Pysz Marybeth , Gu Christine , You Monica , Isse Kumiko , Sullivan Theodore , French Dorothy , Lee Christina , Dang Angeline T. , Zhang Zhaomei , Aujay Monette , Bankovich Alexander J. , Vitorino Philip
Published: June 2022

In the past year, four antibody–drug conjugates (ADC) were approved, nearly doubling the marketed ADCs in oncology. Among other attributes, successful ADCs optimize targeting antibody, conjugation chemistry, and payload mechanism of action. Here, we describe the development of ABBV-011, a novel SEZ6-targeted, calicheamicin-based ADC for the treatment of small cell lung cancer (SCLC). We engineered a calicheamicin conjugate that lacks the acid-labile hydrazine linker that leads to systemic release of a toxic catabolite. We then screened a patient-derived xenograft library to identify SCLC as a tumor type with enhanced sensitivity to calicheamicin ADCs. Using RNA sequencing (RNA-seq) data from primary and xenograft SCLC samples, we identified seizure-related homolog 6 (SEZ6) as a surface-expressed SCLC target with broad expression in SCLC and minimal normal tissue expression by both RNA-seq and IHC. We developed an antibody targeting SEZ6 that is rapidly internalized upon receptor binding and, when conjugated to the calicheamicin linker drug, drives potent tumor regression in vitro and in vivo. These preclinical data suggest that ABBV-011 may provide a novel treatment for patients with SCLC and a rationale for ongoing phase I studies (NCT03639194).
Enabling Programmatic Data Mining as Musicking: The Fluid Corpus Manipulation Toolkit
Authors: Tremblay Pierre Alexandre , Roma Gerard , Green Owen
Published: June 2022

This article presents a new software toolbox to enable programmatic mining of sound banks for musicking and musicking-driven research. The toolbox is available for three popular creative coding environments currently used by “techno-fluent” musicians. The article describes the design rationale and functionality of the toolbox and its ecosystem, then the development methodology—several versions of the toolbox have been seeded to early adopters who have, in turn, contributed to the design. Examples of these early usages are presented, and we describe some observed musical affordances of the proposed approach to the exploration and manipulation of music corpora, as well as the main roadblocks encountered. We finally reflect on a few emerging themes for the next steps in building a community around critical programmatic mining of sound banks.
Comparison of geographical isolates of Bursaphelenchus tadamiensis (Tylenchomorpha: Aphelenchoididae) with remarks on its preferred habitat
Authors: Kanzaki Natsumi , Hamaguchi Keiko , Ide Tatsuya
Published: June 2022

Bursaphelenchus tadamiensis, which was initially isolated from a stag beetle, Dorcus striatipennis, collected from sap flow of Quercus crispula in Fukushima, north-eastern Japan, was re-isolated three times from sap flow of Quercus spp. in western Japan. The re-isolated populations were mostly morphologically consistent with the type population, but the male bursal flap showed high variations in the newly collected populations. Molecularly, the type and new populations showed differences in the internal transcribed spacer region of ribosomal DNA and mitochondrial cytochrome oxidase subunit I gene, suggesting that the species is genetically divided into several local populations. The isolation pattern of B. tadamiensis, i.e., the species was initially isolated from sap flow-associated beetles and subsequently isolated from sap flow, suggests that the species prefers and is adapted to the sap flow environment as its habitat.
Cosmic Order in the Microcosm: Ethical Guidance in Post-Classical Astronomy Texts
Authors: Morrison Robert G.
Published: June 2022

This article is the first to focus on statements about ethical guidance in post-classical astronomy texts. A number of astronomers in post-classical Islamic societies remarked that the study of astronomy, specifically the mathematical analysis of the uniform motions of the celestial orbs, had ethical benefits. These astronomers’ statements are significant because, through them, scholars can learn more about the role of reason in Islamic thought and about sources of ethical guidance other than Sharīʿa and philosophical ethics. The details of the ethical guidance imparted by the study of astronomy tell us more about the relationship between astronomy and the disciplines of fiqh and kalām, respectively. The existence of ethical guidance in astronomy texts is additional evidence that post-classical astronomy texts were part of an Islamic intellectual tradition.
Transcriptome Analysis of Biocontrol Strain Bacillus subtilis Pro-2 and Its Mutants
Authors: Li Qing , Ndayambaje Jean Pierre , Qian Xu , Jin Leilei , Jia Qi , Liu Minghong , Hu Xiufang , Chen Jishuang
Published: June 2022

To enhance the antagonistic ability against tobacco bacterial wilt, physical mutagenesis was in this study induced using nitrogen ion beam irradiation, and resulting mutant strain K60 of Bacillus subtilis Pro-2 effectively controlled Ralstonia solanacearum. Through transcriptome
sequencing, a total of 1291 significantly different genes were screened, including 424 up-regulated genes and 867 down-regulated genes. After enrichment by GO and KEGG metabolic pathways, there were more differential genes enriched in lipopeptide metabolic pathways. The analysis of significantly
changed differential genes showed that, among the three common lipopeptide antibacterial substances of Bacillus (surfactin, iturin and fengycin), the synthetic surfactin genes were significantly increased (P ≤ 0.01). According to transcriptome data, the srfA gene, which is related
to surfactin synthetase, had very significant change in transcription (P ≤ 0.01), and transcription of two regulatory factors (Rap, CodY) related to srfA gene expression were reduced, with CodY being significantly downregulated at the transcription level.
Environmental and Economic Impacts of Biomass Liquid Fuel Conversion and Utilization—A Review
Authors: Chen Zhuo , Lei Tingzhou , Wang Zhiwei , Li Xueqin , Liu Peng
Published: June 2022

Biomass liquid fuel, one of the most important renewable fuels, plays a key role in the energy development. This paper reviews the research progress in biomass liquid fuel conversion and utilization, environmental impact, and economic analysis. The application research of biomass liquid
fuel currently focuses on the evaluation of substitution and emission reduction effect of a single component on fossil energy. While most studies confirm that biomass liquid fuel can reduce greenhouse gas emission and current energy shortage problems, the large-scale cultivation and use of
energy crops may induce negative environmental impacts. And although second-generation biomass liquid fuel base on agricultural residues have potential development and considerable economic feasibility compared to fossil fuel, technological breakthroughs are required to reduce production costs
and achieve large-scale promotion and application. Technological breakthroughs in the multi-product comprehensive utilization of biomass liquid fuel, raw material plants in the environment, establishment of economic analysis models, and economic quantification of ecological benefits will drive
research directions in the future.
Are Surgeons of the Abdominal Core Health Quality Collaborative Following Guidelines in Umbilical and Epigastric Hernia Repair?
Authors: Malysz Oyola Anna M. , Faulkner Justin , Casas Brandon , Hooks William B. , Hope William W.
Published: June 2022

Background

Umbilical and epigastric hernias are among the top three most common hernia surgeries performed in the USA with varied techniques. The European and Americas Hernia Societies (EAHS) recently published guidelines for repair of umbilical and epigastric hernias. We evaluated how closely the general surgeons of the Abdominal Core Health Quality Collaborative (ACHQC) follow these guidelines and to identify areas for possible improvement.

Method

Data from patients undergoing elective and emergent umbilical or epigastric hernia repair from 2013 to 2021 were extracted from the ACHQC database. The procedures performed on eligible subjects were compared to those proposed by the EAHS guidelines. Data was reported as a percentage and a cutoff of 70% was selected to determine compliance.

Results

Based on these criteria, 11,088 patients were included and most of the recommendations, including appropriate preoperative antibiotic dosing (96.1% umbilical; 97.2% epigastric), permanent mesh selection (umbilical 97.8%; 96.1 epigastric), mesh fixation with suture (83.6% umbilical; 75.5% epigastric), use of mesh for open repair of hernias greater than 1 cm (83.6 umbilical; 85.7 epigastric), and primary defect closure during open (98.6% umbilical; 97.5% epigastric) and laparoscopic (99.6% umbilical; 100% epigastric) repair, were met.

Discussion

Surgeons of the ACHQC adhere to most of the published guidelines on umbilical and epigastric hernia repair. Further research is needed to reinforce or modify the existing recommendations. Standardization of surgical approach will facilitate additional research needed to improve procedural efficiency, while reducing negative outcomes and cost.
Vertical Versus Horizontal Variance in Online Reviews and Their Impact on Demand
Authors: Lee Nah , Bollinger Bryan , Staelin Richard
Published: June 2022

This article examines the differential impact of variances in the quality and taste comments found in online customer reviews on firm sales. Using an analytic model, the authors show that although increased variance in consumer reviews about taste mismatch normally decreases subsequent demand, it can increase demand when mean ratings are low and/or quality variance is high. In contrast, increased variance in quality always decreases subsequent demand, although this effect is moderated by the amount of variance in tastes. Since these theoretical demand effects are predicated on the assumption that consumers can differentiate between the two sources of variation in ratings, the authors conduct a survey to test this assumption, demonstrating that participants are indeed able to reliably distinguish quality from taste evaluations in two subsets of 5,000 reviews taken from larger data sets of reviews for 4,305 restaurants and 3,460 hotels. The authors use these responses to construct sets of reviews that they use in a controlled laboratory experiment on restaurant choice, finding strong support for the theoretical predictions. These responses are also used to train classifiers using a bag-of-words model to predict the degree to which each review in the larger data sets relates to quality and/or taste, allowing the authors to estimate the two types of review variances. Finally, the authors estimate the effects of these variances in overall ratings on establishment sales, again finding support for the theoretical results.
A New inversion method of the initial state of Annulus in killing
Authors: Liu Pu , Zhan Yonglie , Xiao Quanlin , Tang Zhengqiang , Li Xuan , Zuo Luo
Published: June 2022

Blowout is a major safety concern for well control in oil and gas well engineering and well killing is an important technical means to avoid blowout. Mastering the initial state of the wellbore is the basis to ensure well killing. The traditional gas column model cannot effectively explain the development law of wellbore pressure. Therefore, this paper is based on the actual killing conditions and the principle of gas-liquid two-phase flow. This paper establishes the physical model and mathematical model of the initial state of the wellbore annulus under overflow conditions. By means of the finite difference method and cyclic iteration calculation, the initial state of the wellbore annulus can be accurately inverted, and the calculation results are verified by an example. The results show that, when the wellhead pressure is determined, the wellbore pressure distribution and annular air phase distribution are more reasonable and the initial length of the overflow section is larger, the calculation results of the inversion method are closer to the actual engineering situation. The findings of this study can help to better understand wellbore state before killing and provide a theoretical basis for optimizing killing parameters, which is of great significance for avoiding well control safety risks during killing.
‘Without Papers I Can’t Do Anything’: The Neglected Role of Citizenship Status and ‘Illegality’ in Intersectional Analysis
Authors: Damsa Dorina , Franko Katja
Published: June 2022

Intersectionality scholarship has yet to systematically recognize the importance of citizenship status for the mutual shaping of inequalities. In this article, we bring attention to the combined structuring force of criminal law and citizenship status (and the related concepts of ‘illegal’ or ‘irregular’ status) in intersecting with other categories of social disadvantage, such as those created by racialization, class, gender and ethnicity. Drawing on ethnographic fieldwork and interviews with women in prisons for ‘foreign nationals’ and health clinics for ‘undocumented’ migrants in Norway and Denmark, this article shows how citizenship status has a central role in the co-constitution of gendered, classed and racialized social disadvantages.