bluuebunny/crossref_metadata_2025 huggingface dataset:
Grounded Task Prioritization with Context-Aware Sequential Ranking
Authors: Zhang Chuxu , Kiseleva Julia , Jauhar Sujay Kumar , White Ryen W.
Published: December 2021

People rely on task management applications and digital assistants to capture and track their tasks, and help with executing them. The burden of organizing and scheduling time for tasks continues to reside with users of these systems, despite the high cognitive load associated with these activities. Users stand to benefit greatly from a task management system capable of prioritizing their pending tasks, thus saving them time and effort. In this article, we make three main contributions. First, we propose the problem of task prioritization, formulating it as a ranking over a user’s pending tasks given a history of previous interactions with a task management system. Second, we perform an extensive analysis on the large-scale anonymized, de-identified logs of a popular task management application, deriving a dataset of grounded, real-world tasks from which to learn and evaluate our proposed system. We also identify patterns in how people record tasks as complete, which vary consistently with the nature of the task. Third, we propose a novel contextual deep learning solution capable of performing personalized task prioritization. In a battery of tests, we show that this approach outperforms several operational baselines and other sequential ranking models from previous work. Our findings have implications for understanding the ways people prioritize and manage tasks with digital tools, and in the design of support for users of task management applications.
Education and Political Participation
Authors: Willeck Claire , Mendelberg Tali
Published: December 2021

Whether education affects political participation is a long-standing and central question in political philosophy and political science. In this review, we provide an overview of the three main theoretical models that explain different causal pathways. We then synthesize the surge in research using causal inference strategies and show that this literature has generated mixed results about the causal impact of education, even when using similar methods and data. These findings do not provide clear support for any of the three theories. Our next section covers research on civic education and political participation. The quantity of civic education matters little for political participation, but how civic education is taught does matter. Namely, strategies falling under the rubric of active learning show promise. These strategies seem especially effective for historically marginalized students. Our final section calls for more research on how civic education is taught.
Methods—On the Reliability of the Electrochemical Data Recorded on Nickel Foam in Alkaline Solution: The Illusive Surface Oxide Layer
Authors: Malaie Keyvan , Heydari Zahra , Brousse Thierry
Published: December 2021

The extensive application of nickel foam (Ni foam) as current collector in supercapacitors has raised caveats on the contribution of the redox-active Ni foam to the measured capacities. However, due to the overlooked qualitative features (i.e., shapes) of the cyclic voltammograms (CVs), the redox reaction of the Ni foam oxide layer (NiFOL) has been frequently confused with the true electrochemical signature of the coated materials in alkaline solution. Herein, experimental CVs, scanning electron microscopy images, and estimations reveal that due to the high porosity of the Ni foam and its surface reactivity in alkaline solution (1–6 M KOH), the redox peak couple of the NiFOL can potentially be confused with or lead to misinterpretation of the true electrochemical features of the coatings. A classification of previous papers on a group of metal oxides investigated as battery-type or pseudocapacitive electrodes in the positive potential window is also presented to reveal the confusion between NiFOL and the coating when operated in alkaline solution.
Assessment of Larval Toxicity and the Teratogenic Effect of Three Medicinal Plants Used in the Traditional Treatment of Urinary Tract Infections in Benin
Authors: Assogba Phénix , Dougnon Victorien , Hounsa Edna , Badjabaissi Pierre , Tari Rachida Moussa , Klotoe Jean Robert , Bankole Honoré , Diallo Aboudoulatif
Published: December 2021

Objective. Mangifera indica Linn, Bridelia ferruginea Benth, and Alstonia boonei De Wild are three plants commonly used in the traditional treatment of urinary tract infections in Benin. This study sets out to assess the cytotoxic and teratogenic effects of extracts of these plants on Artemia salina larvae and hen embryos. Methods and Results. The aqueous and ethanolic extracts were obtained by maceration of the powders in solvents. Larval cytotoxicity was performed on Artemia salina larvae. The teratogenic effect of these plants was evaluated on chick embryos at 100 mg/kg and 300 mg/kg. The extracts were injected on the 7th and 14th days of incubation. The quality of the hatched chicks was evaluated by the Tona score followed by the hematological and the biochemical parameter assays. The extracts did not show cytotoxicity on the larvae. The eggs treated with plant extracts at 300 mg/kg significantly lowered the hatchability rate, except for the Mangifera indica Linn. The chicks obtained were all at the very good quality. Then, no significant variation was observed between hematological parameters except white blood cells. For the biochemical parameters, only ASAT showed some significant variations for a few extracts. It would be important to assess the genotoxicity of the plant extracts to determine more broader toxicity. These data justify the use of these medicinal plants in traditional Beninese medicine and constitute in fact a source of production of anti‐infectious drugs.
Hypoglycemic Effects of Plant Flavonoids: A Review
Authors: Sok Yen Foo , Shu Qin Chan , Tan Shi Xuan Sharryl , Jia Ying Puah , Yi Le Hong , Darmarajan Thiviya , Gunasekaran Baskaran , Salvamani Shamala
Published: December 2021

Diabetes mellitus is a metabolic disorder with chronic high blood glucose levels, and it is associated with defects in insulin secretion, insulin resistance, or both. It is also a major public issue, affecting the world's population. This disease contributes to long-term health complications such as dysfunction and failure of multiple organs, including nerves, heart, blood vessels, kidneys, and eyes. Flavonoids are phenolic compounds found in nature and usually present as secondary metabolites in plants, vegetables, and fungi. Flavonoids possess many health benefits such as anti-inflammatory and antioxidant activities, and naturally occurring flavonoids contribute to antidiabetic effects.Many studies conducted in vivo and in vitro have proven the hypoglycemic effect of plant flavonoids. A large number of studies showed that flavonoids hold positive results in controlling the blood glucose level in streptozotocin (STZ)-induced diabetic rats and further prevent the complications of diabetes. The future development of flavonoid-based drugs is believed to provide significant effects on diabetes mellitus and diabetes complication diseases. This review aims at summarizing the various types of flavonoids that function as hyperglycemia regulators such as inhibitors of α-glucosidase and glucose cotransporters in the body. This review article discusses the hypoglycemic effects of selected plant flavonoids namely quercetin, kaempferol, rutin, naringenin, fisetin, and morin. Four search engines, PubMed, Google Scholar, Scopus, and SciFinder, are used to collect the data.
Distinct Hypoxia-Related Gene Profiling Characterizes Clinicopathological Features and Immune Status of Mismatch Repair-Deficient Colon Cancer
Authors: Xu Yixin , Hu Junjie , Cao Can , Zhang Mili , Liu Youdong , Chen Haonan , Wei ShanShan , Zhu Ziyan , Yang Yuqin , Yu Liang , Li Jikun
Published: December 2021

Despite dramatic responses to immune checkpoint inhibitors (ICIs) in patients with colon cancer (CC) harboring deficient mismatch repair (dMMR), more than half of these patients ultimately progress and experience primary or secondary drug resistance. There is no useful biomarker that is currently validated to accurately predict this resistance or stratify patients who may benefit from ICI-based immunotherapy. As hypoxic and acidic tumor microenvironment would greatly impair tumor-suppressing functions of tumor-infiltrating lymphocytes (TILs), we sought to explore distinct immunological phenotypes by analysis of the intratumoral hypoxia state using a well-established gene signature. Based on the Gene Expression Omnibus (GEO) (n = 88) and The Cancer Genome Atlas (TCGA) (n = 49) databases of patients with CC, we found that dMMR CC patients could be separated into normoxia subgroup (NS) and hypoxia subgroup (HS) with different levels of expression of hypoxia-related genes (lower in NS group and higher in HS group) using NMF package. Tumoral parenchyma in the HS group had a relatively lower level of immune cell infiltration, particularly CD8+ T cells and M1 macrophages than the NS group, and coincided with higher expression of immune checkpoint molecules and C-X-C motif chemokines, which might be associated with ICI resistance and prognosis. Furthermore, three genes, namely, MT1E, MT2A, and MAFF, were identified to be differentially expressed between NS and HS groups in both GEO and TCGA cohorts. Based on these genes, a prognostic model with stable and valuable predicting ability has been built for clinical application. In conclusion, the varying tumor-immune microenvironment (TIME) classified by hypoxia-related genes might be closely associated with different therapeutic responses of ICIs and prognosis of dMMR CC patients.
Prevalence of Malaria and Associated Factors among Delivering Mothers in Northwest Ethiopia
Authors: Limenih Asmamaw , Gelaye Woynshet , Alemu Getaneh
Published: December 2021

Background. Malaria is one of the leading causes of morbidity and mortality especially in pregnant women and under‐five‐year‐old children. However, data on the prevalence among delivering mothers, potential fetal transmission, and associated birth outcomes is lacking in Ethiopia. Objective. To assess the prevalence of Plasmodium infection from peripheral, placental, and cord blood samples among delivering mothers in Kuch health center, Northwest Ethiopia. Methods. An institution‐based cross‐sectional study was conducted among 218 delivering mothers from February to May 2021 in Kuch health center. Data on sociodemographic characteristics and clinical and obstetric history of mothers were collected using a structured questionnaire. Giemsa stained blood films from maternal capillary and placental and umbilical cord blood were examined for plasmodium infection. Data were analyzed using Statistical Package for the Social Sciences version 23 software package. Results. The prevalence of maternal, placental, and umbilical cord malaria was 6.4% (14/218), 2.3% (5/218), and 0.5% (1/218), respectively. Plasmodium falciparum and Plasmodium vivax accounted 3.7% (8/218) and 2.8% (6/218), respectively, in maternal peripheral blood but only Plasmodium falciparum was detected in placental and umbilical cord blood samples. Maternal malaria had significant association with primigravida (χ2 = 12.611, p = 0.002) and low birth weight (χ2 = 8.381, p = 0.004). Placental malaria was also significantly associated with low birth weight (χ2 = 32.255, p ≤ 0.001). Conclusion. The prevalence of malaria among delivering mothers was considerable. Maternal peripheral malaria had a significant association with gravidity and birth weight. Placental and umbilical cord malaria also had a significant association with birth weight. Pregnant mothers should be examined for malaria and receive appropriate treatment to prevent adverse birth outcomes.
Research on the Construction of an e‐Commerce Marketing System Based on the Wireless Sensor Network
Authors: Zhang Chi
Published: December 2021

This paper takes e‐commerce as the research object, based on the combination of wireless sensor network research results, using relevant theoretical analysis tools to identify several major problems in the marketing of enterprises. Then, the internal environment conditions of developing e‐commerce are comprehensively analyzed through human resources, financial resources, marketing ability, and platform building ability, and the advantages and disadvantages of the enterprise itself are presented in a three‐dimensional manner to help the enterprise understand its situation. Firstly, the overall hardware structure design of this paper is analyzed, and the network marketing node hardware design is proposed as the core of the system hardware design, and the marketing node hardware design circuit diagram is given through the selection of marketing node sensors, the selection of wireless communication modules, and the selection of marketing node microprocessors. Based on the specific application of the wireless sensor network in the e‐commerce marketing system, the number of cluster selection is reduced by calculating and setting the remaining energy threshold of the cluster head for the whole network. The optimal cluster head is searched for based on the density of marketing nodes in different regions and the minimum energy consumption of the cluster after the division of the region within the cluster, and the original cluster head is replaced; the density of marketing nodes in different e‐commerce is different, and the optimal number of cluster heads is searched for based on the minimum energy consumption of the network. In summary, three strategies are implemented to improve the design of wireless sensor network routing, and the effectiveness of the algorithm is verified through experimental simulation. Through the analysis of e‐commerce operation, the intracluster congestion control is achieved by a dual‐cluster head strategy with intracluster push selection of subcluster heads; the network nonuniform hierarchy and resource scheduling strategy achieve intercluster congestion mitigation and decongestion. A minimum energy consumption multihop path tree is also proposed here, which can achieve the lowest energy consumption of marketing nodes and networks and improve the link quality relative to other transmission paths. After simulation experiments, the effectiveness and reliability of the congestion algorithm are verified. A guarantee scheme is provided for the development of e‐commerce marketing strategies to help breakthroughs and developments in marketing management, and an attempt is also made to provide a template for other enterprises to follow.
Incidence and Predictive Factors of Tibial Fracture with Occult Posterior Ankle Fractures
Authors: Wang Dafeng , Yang Jie , Dong Xiaomin , Zhou Shengtuo , Wang Chaonan
Published: December 2021

Background. Few studies exist on the predictive factors of tibial fractures with hidden posterior ankle fractures. Objective. To study the incidence and predictive factors of tibial fractures with occult posterior ankle fractures. Methods. Tibial fracture patients were prospectively selected who were admitted to our hospital from January 2016 to May 2021 and their general clinical data, X-ray images, CT images, and other imaging data were collected and then divided them into posterior malleolus fracture group and nonposterior malleolus fracture group according to the presence or absence of posterior malleolus fractures. Multivariate regression analysis and receiver operating curves (ROC) were performed to analyze the influencing factors of tibial fracture with occult posterior ankle fracture. Results. CT showed that 25 (13.44%) patients had occult posterior ankle fractures among 186 patients with tibial fracture. There was no significant difference in gender, age, and locations of tibial fracture between the two groups (

P
>
0.05

). There were statistical differences in the types, locations, and lengths of patients with tibial fracture but without posterior malleolus fractures. The length of the tibia fracture group was significantly lower than the tibia with posterior ankle fracture group (

P
<
0.05

). Logistics regression analysis showed that tibial fracture with occult posterior ankle fracture was not significantly correlated with gender, age, and location of tibial fracture (

P
>
0.05

), but was significantly correlated with tibial fracture type, location, and length (HR = 1.830,

P
=
0.035

; HR = 5.161,

P
=
0.004

; HR = 1.126,

P
=
0.030

). The ROC curve showed that the AUC of length of tibial fracture with occult posterior ankle fracture was 0.599. The YD index suggested that the best cut point for the prediction of tibial fracture with occult posterior ankle fracture was above 13.18%. The sensitivity and specificity of spiral tibial fracture and distal 1/3 tibial fracture for prediction were 88.00% and 63.35%, 92.00%, and 58.39%, respectively, which was significantly higher than that of tibial fracture length (

P
<
0.05

). Conclusion. Patients with tibial fractures have a higher incidence of occult posterior ankle fractures. Spiral tibial fractures and distal 1/3 tibial fractures have a higher predictive value for tibial fracture with occult posterior ankle fractures and can help clinical detection as soon as possible, which is a more accurate and appropriate treatment.
Hysteretic Energy Demand under Superposition of Bidirectional Ground Motions
Authors: Wang Feng , Shi Jialin , Chen Pengyan
Published: December 2021

To address the irrationality of making a structure subjected to bidirectional ground motions equivalent to an SDOF system, a new approach method is presented in this paper. The ratio between modal participation factors of the two components of the structure is expressed as γ, and the superposition of bidirectional ground motions is regarded as one-directional earthquake excitation for the equivalent SDOF system. Based on this, an energy balance equation is established, and a method used to estimate normalized hysteretic energy (NHE) is proposed. Analysis of the ratio between NHE (γ ≠ 0) and NHE (γ = 0) is suggested in order to analyze the influence of bidirectional ground motions on hysteretic energy demand, and then, “α1 = NHE (γ ≠ 0)/NHE (γ = 0)” is defined, and bidirectional ground motion records for different soil sites are selected for establishing superimposed excitations. In addition, the period range of 0–5 s for the energy spectrum is divided into 6 ranges. In each period range, the means of α1 are defined as α. The curves of α of constant ductility factors for different soil sites are established, in which α is the vertical coordinate and γ is the horizontal coordinate. Through nonlinear response history analysis, the influence of soil types at different sites, the ductility factor, the ratio of modal participation factors, and the period on the values of α are analyzed. According to the analytical results, correction coefficient αs (the simplified value of α) is obtained so that the hysteretic energy demand under bidirectional ground motions can be determined.
Combining CT Images and Clinical Features of Four Periods to Predict Whether Patients Have Rectal Cancer
Authors: Feng Yingyin , Ding Qi , Meng Chen , Wang Wenfeng , Zhang Jingjing , Lian Huixiu
Published: December 2021

In this paper, we mainly use random forest and broad learning system (BLS) to predict rectal cancer. A total of 246 participants with computed tomography (CT) image records were enrolled. The total model in the training set (combined with imaging and clinical indicators) has the best prediction result, with the area under the curve (AUC) of 0.999 (95% confidence internal (CI): 0.996–1.000) and the accuracy of 0.990 (95%CI: 0.976–1.000). Model 3, the general model in the test set, has the best prediction result, with the AUC of 0.962 (95%CI: 0.915–1.000) and the accuracy of 0.920 (95%CI: 0.845–0.995). The results of the model using random forest prediction are compared with those using BLS prediction. It can be found that there is no statistical difference between the two results. Our prediction model combined with image features has a good prediction result, and this image feature is the most important among all features. Consequently, we can successfully predict rectal cancer through a combination of the clinical indicators and the comprehensive indicators of CT image characteristics in four different periods (plain scan, vein, artery, and excretion).
Ultrasound-Assisted Modification of Insoluble Dietary Fiber from Chia (Salvia hispanica L.) Seeds
Authors: Hassan Zohaib , Imran Muhammad , Ahmad Muhammad Haseeb , Khan Muhammad Kamran
Published: December 2021

Modification of insoluble dietary fiber (IDF) to soluble dietary fiber (SDF) improves not only the various health benefits but also the functional properties for improved product development. This research aimed to examine the effects of sonication treatment on the functional and physicochemical properties with possible structural changes in chia seeds dietary fiber. Central composite design was applied to optimize the sonication treatment process (amplitude 55%, time 20 min, and temperature 40°C) based on the oil holding capacity (OHC) and water holding capacity (WHC) as responses. Under these optimum conditions, ultrasound-treated IDF exhibited better functional and physicochemical properties such as OHC, WHC, glucose adsorption capacity (GAC), and water retention capacity (WRC) than untreated IDF. Fourier-transform infrared spectroscopy further confirmed the structural changes in treated and untreated IDF to explain the changes in the studied parameters.
Acute Poisoning Cases Presented to the Addis Ababa Burn, Emergency, and Trauma Hospital Emergency Department, Addis Ababa, Ethiopia: A Cross-Sectional Study
Authors: Zemedie Biruktawit , Sultan Menbeu , Zewdie Ayalew
Published: December 2021

Background. Acute poisoning is a common reason for visits to the emergency room and hospitalization across the world, as well as a possible cause of morbidity and death. This study aimed to assess acute poisonings at Addis Ababa Burn, Emergency, and Trauma (AaBET) Hospital. Methodology. A one-year cross-sectional study was conducted at AaBET Hospital from February 1, 2018, to January 31, 2019. Data were collected using a structured and pretested questionnaire by the Emergency Medicine and Critical Care residents from acutely poisoned patients’ interviews and patient charts. Results. Data were collected from 98 acute poisoning cases, and 52% were males and 48% were females. 85 (86.7%) were less than 45 years. 52 (55.1%) were unemployed, and 33 (33.7%) were farmers. 96 (98%) cases were due to intentional poisoning, and 96 (98%) had oral ingestion. Organophosphates poisoning (27.5%) was the commonest cause, followed by 26.5% of unknown poisons and 16.3% prescribed drugs. Sixty-six percent of the patients presented to the hospital after 2 hours of ingestion. The case fatalities were 10.2% of which 40% of the cases were due to 2,4-dichlorophenoxyacetic (2, 4-D) poisoning, followed by aluminum phosphide (20%). Conclusion. This study showed farmers and the unemployed were more affected. The most common mode of poisoning was intentional poisoning, oral ingestion being the primary route. The common poisons used by the victims were organophosphates. 2, 4-D poisoning was the major cause of death.
A Data Technology Oriented to Information Fusion to Build an Intelligent Accounting Computerized Model
Authors: Xu Ziyan , Zhou Wenxue
Published: December 2021

The development of management accounting promotes the integration of business and finance, and with the continuous development of information technology and the advent of the era of big data, the development of corporate financial informatization provides tools for the integration of business and finance. This paper improves the big data technology, improves the traditional accounting process, combines the big data technology to build a computerized accounting system, and obtains scientific and effective accounting information processing results through intelligent big data processing. The design goal of the enterprise accounting management system is that the system can efficiently complete the enterprise cost budget accounting work after the design is completed and ensure the normal and stable progress of the enterprise cost budget accounting work. Through the experimental research results, it can be known that the computerized intelligent accounting system based on big data technology constructed in this article has certain effects.
The Role of RIPC in Preventing Organ Damage, Inflammation, and Oxidative Stress during Lower Limb DSA: A Randomised Controlled Trial
Authors: Kuusik Karl , Kasepalu Teele , Zilmer Mihkel , Eha Jaan , Vähi Mare , Torop Liisi Anette , Lieberg Jüri , Kals Jaak
Published: December 2021

Objective. Diagnostic digital subtraction angiography (DSA) and DSA with percutaneous transluminal angioplasty (DSA‐PTA) are common procedures for diagnosing and treating symptomatic lower extremity arterial disease (LEAD). However, organ damage following DSA and DSA‐PTA is often underrecognised and hence undiagnosed. To reduce the risk induced by invasive procedures in symptomatic LEAD patients, the method of remote ischemic preconditioning (RIPC) has been suggested. The aim of the current study was to assess the effect of RIPC intervention on the organ damage markers profile, oxidative stress, and inflammation biomarkers in LEAD patients undergoing DSA and DSA‐PTA procedure. Methods. The RIPC intervention was performed by inflating a standard blood pressure cuff on the patient’s upper arm to 200 mmHg for 5 minutes four times with 5‐minute perfusion between each cycle. The sham intervention was performed similarly, but the cuff was inflated to 20 mmHg. Changes in the cardiac and renal damage biomarkers’ profile, oxidative stress, and inflammation biomarkers were recorded before and 24 hours after DSA or DSA‐PTA. Results. A total of 111 (RIPC 54, sham 57) patients with symptomatic LEAD scheduled for endovascular procedure were randomised, and 102 patients (RIPC 47, sham 55) completed the study protocol. RIPC significantly limited the increase of adiponectine levels after DSA and DSA‐PTA, compared to sham intervention (p = 0.020), but CK‐MB levels were markedly lower in the sham group (p = 0.047) after procedure. There was no significant difference between the RIPC and the sham group in mean changes in hs‐troponin‐T (p = 0.25), NT‐proBNP (p = 0.24), creatinine (p = 0.76), eGFR (p = 0.61), urea (p = 0.95), beta‐2‐microglobuline (p = 0.34), or cystatine C (p = 0.24) levels. Conclusion. In this controlled clinical study, RIPC failed to improve the profile of renal and cardiac biomarkers in patients with LEAD periprocedurally. RIPC significantly limits the rise in adiponectin levels and may influence the decrease of CK‐MB levels 24 hours after endovascular procedure.
Application of Smart Mobile Medical Services in Maternal Health Care Management
Authors: Liu Yue , Wang Xia
Published: December 2021

In order to standardize the health management of pregnant women, improve the health level of pregnant women, and improve the outcome of pregnancy with the help of the smartphone mobile terminal app, the 100 pregnant women who gave birth in the hospital and participated in the management of the health assistant app were selected as the observation group, and the 100 hospitalized pregnant women who did not participate in the management of the app were selected as the control group. The two groups of pregnant women were compared in their knowledge of health care, compliance of prenatal examination, delivery mode, and follow-up rate. The results showed that the observation group was significantly higher than the control group in the knowledge of health care during pregnancy and perinatal period, the rate of natural childbirth, the compliance rate of prenatal examination, and the follow-up rate. After the system was launched, the number of registered pregnant women reached more than 60% of the total number of pregnant women in the hospital, the number of clicks reached more than 2 million times, the number of clinic settlement accounted for more than 30%, and the interpretation rate of fetal heart rate in outpatient and remote clinics reached more than 20%. The diagnosis and treatment process has been significantly improved, and the implementation effect has reached the expectation. O2O maternal and child service mode has been realized through mobile internet technology. It has been proved that the use of smart mobile terminals in the out-of-hospital health care management of pregnant women not only facilitates medical staff to provide timely personalized medical services for pregnant women but also is convenient for pregnant women to obtain health care knowledge through multiple channels, improve the quality of home health management for pregnant women, and effectively improve the pregnancy outcome.
Using Graph Representation in Host-Based Intrusion Detection
Authors: Hu Zhichao , Liu Likun , Yu Haining , Yu Xiangzhan
Published: December 2021

Cybersecurity has become an important part of our daily lives. As an important part, there are many researches on intrusion detection based on host system call in recent years. Compared to sentences, a sequence of system calls has unique characteristics. It contains implicit pattern relationships that are less sensitive to the order of occurrence and that have less impact on the classification results when the frequency of system calls varies slightly. There are also various properties such as resource consumption, execution time, predefined rules, and empirical weights of system calls. Commonly used word embedding methods, such as Bow, TI-IDF, N-Gram, and Word2Vec, do not fully exploit such relationships in sequences as well as conveniently support attribute expansion. To solve these problems, we introduce Graph Representation based Intrusion Detection (GRID), an intrusion detection framework based on graph representation learning. It captures the potential relationships between system calls to learn better features, and it is applicable to a wide range of back-end classifiers. GRID utilizes a new sequence embedding method Graph Random State Embedding (GRSE) that uses graph structures to model a finite number of sequence items and represent the structural association relationships between them. A more efficient representation of sequence embeddings is generated by random walks, word embeddings, and graph pooling. Moreover, it can be easily extended to sequences with attributes. Our experimental results on the AFDA-LD dataset show that GRID has an average improvement of 2% using the GRSE embedding method comparing to others.
An Empirical Study on the Employment Monitoring and Early Warning Mechanism of Medical Graduates in Universities with Big Data and Complex Computing System
Authors: Wu Haixia , Tsai Sang-Bing
Published: December 2021

Based on the management of big data, the analysis and forecast of the employment demand cycle business situation studied in this article is based on the employment cycle theory and a complete set of employment monitoring, employment evaluation, employment forecasting, and policy selection theories and strategies developed around the employment cycle fluctuations, a specific employment phenomenon. First, systematically evaluate the current state of the employment demand boom, appropriately reflect the hot and cold degree of the employment demand boom, and provide necessary information for the government’s regulatory measures, content, and timing. Secondly, it reflects the regulatory effects of graduate employment monitoring, judging whether graduate employment monitoring measures are properly applied, whether they have the effect of smoothing out employment fluctuations, and promoting the country’s employment demand; in addition, business decision makers can take advantage of the employment demand boom, by monitoring the information provided by the early warning system and timely foreseeing the upcoming macrocontrol measures, so that enterprises’ labor adjustments can adapt to the government’s regulatory measures. At the same time, the model proposes a prosperity index method for monitoring and early warning of the employment demand cycle. After selecting and dividing three types of prosperity indicators, the DI index reflecting the trend of the prosperity change and the CI index reflecting the strength of the prosperity change are calculated and constructed. The national employment demand boom monitoring and early warning signal system predicts the trend of the employment boom cycle outside the sample period. The experimental results show that the cyclic prosperity forecast results are consistent not only with the national employment demand prosperity in recent months, but also with the use of the structural measurement ARIMA (p, d, q) model. The alertness value is close, indicating that this indicator system has a good effect on the national employment demand boom monitoring and early warning.
Frequency of Cardiovascular Complications and Its Association with Prognosis of COVID‐19 Patients
Authors: Mazaherpour Hossein , Soofian Masoumeh , Farahani Elham , Masfari Farahani Fatemeh , Ghaznavi Rad Ehsanollah , Mazaherpour Sakine , Ramazani Yousef , Ashrafian Fatemeh , Ramezani Amitis
Published: December 2021

Coronavirus disease 2019 (COVID‐19) may lead to acute respiratory disease; cardiovascular, gastrointestinal, and coagulation complications; and even death. One of the major complications is cardiovascular disorders, including arrhythmias, myocarditis, pericarditis, and acute coronary artery disease. The aim of this study was to evaluate the frequency of cardiovascular complications and to determine its association with the prognosis of COVID‐19 patients. In a prospective analytic study, 137 hospitalized COVID‐19 patients were enrolled. During hospitalization, an electrocardiogram (ECG) was performed every other day, and laboratory tests such as cardiac troponin I (cTnI) and creatine kinase‐MB (CK‐MB) were done 0, 6, and 12 hours after admission. These tests were repeated for patients with chest pain or ECG changes. Patients were categorized into three groups (improved, complicated, and expired patients) and assessed for the rate and type of arrhythmias, cardiac complications, lab tests, and outcomes of treatments. There was no significant relationship among the three groups related to primary arrhythmia and arrhythmias during treatment. The most common arrhythmia during hospitalization and after treatment was ST‐T fragment changes. There was a significant age difference between the three groups (P = 0.001). There was a significant difference among the three groups for some underlying diseases, including diabetes mellitus (P = 0.003) and hyperlipidemia (P = 0.004). In our study, different types of arrhythmias had no association with patients’ outcomes but age over 60 years, diabetes mellitus, and hyperlipidemia played an important role in the prognosis of COVID‐19 cases.
Digital Music Waveform Analysis and Retrieval Based on Feature Extraction Algorithm
Authors: Jiao Yang
Published: December 2021

In order to improve the feature extraction effect of digital music and improve the efficiency of music retrieval, this paper combines digital technology to analyze music waveforms, extract music features, and realize digital processing of music features. Taking the extraction of waveform music file features as the starting point, this paper combines the digital music feature extraction algorithm to build a music feature extraction model and conducts an in-depth analysis of the digital music waveform extraction process. In addition, by setting the threshold, the linear difference between the sampling points on both sides of the threshold on the leading edge of the waveform is used to obtain the overthreshold time. From the experimental research results, it can be seen that the music feature extraction model based on digital music waveform analysis proposed in this paper has good results.
Analysis of Enterprise Financial and Economic Impact Based on Background Deep Learning Model under Business Administration
Authors: Hu Jingxiao
Published: December 2021

Enterprise finance has become an indispensable financial channel for people to invest in their lives, and business management can provide a better economic environment for the development of enterprise finance. The structure of enterprises is gradually becoming more and more complex, and business administration shoulders considerable responsibilities and obligations in the organization and supervision of today’s social management structure. How can China play its functions under the new situation after the world economic exchanges are more frequent is an important link to promote the stable development of financial markets. In view of the problems of economic activity behavior and certainty of financial index system under the background of existing business administration, this paper puts forward the deep learning model to make risk analysis, income analysis, profit and loss analysis, and so on. The formula of deep learning model is used to calculate the data graph of financial economy, and finally, various data are compared to get the research of several business management methods on the development of enterprise financial economy. Among them, the model of current management mode belongs to two modes: e-commerce and EPR management. They not only have very unique management characteristics but also greatly promote the development of modern management, and their roles also well interpret the characteristics of modern management. The experiment also analyzes the financial data under the four algorithms for uncertainty comparison, profit and loss comparison, discreteness comparison, volatility comparison, and possibility analysis. Finally, after the source of uncertainty, the risk prediction and risk management are carried out by constructing decision trees, and these structural models are used to bring comprehensive analysis to the financial economy of enterprises and to build the impact of good trends and development prospects.
Attention-Based Graph Convolutional Network for Zero-Shot Learning with Pre-Training
Authors: Wu Xuefei , Liu Mingjiang , Xin Bo , Zhu Zhangqing , Wang Gang
Published: December 2021

Zero-shot learning (ZSL) is a powerful and promising learning paradigm for classifying instances that have not been seen in training. Although graph convolutional networks (GCNs) have recently shown great potential for the ZSL tasks, these models cannot adjust the constant connection weights between the nodes in knowledge graph and the neighbor nodes contribute equally to classify the central node. In this study, we apply an attention mechanism to adjust the connection weights adaptively to learn more important information for classifying unseen target nodes. First, we propose an attention graph convolutional network for zero-shot learning (AGCNZ) by integrating the attention mechanism and GCN directly. Then, in order to prevent the dilution of knowledge from distant nodes, we apply the dense graph propagation (DGP) model for the ZSL tasks and propose an attention dense graph propagation model for zero-shot learning (ADGPZ). Finally, we propose a modified loss function with a relaxation factor to further improve the performance of the learned classifier. Experimental results under different pre-training settings verified the effectiveness of the proposed attention-based models for ZSL.
Curative Effect Observation of Applying Silver-Zinc Bacteriostatic Cream to Patients with Second-Degree Burn under Targeted Nursing Intervention and Its Effect on Wound Healing Rate
Authors: Li Bingqing , Xu Kun , Liu Xin
Published: December 2021

Second-degree burn is the most common type of burn wound in the clinics, which presents a deeper wound, skin blisters, white or red bottom, and thick and clear fluid inside, is sensitive to tenderness, and turns white by compression [1, 2]. The aim of this study is to explore the efficacy of applying silver-zinc bacteriostatic cream to patients with second-degree burn under targeted nursing intervention and its effect on wound healing rate. A total of 110 patients with second-degree burn treated in our hospital from January 2019 to June 2021 were selected as the research object for the retrospective study. Between the experimental group and the control group, no statistical differences in patients’ general information were observed (

P
>
0.05

); 1 week, 2 weeks, and 3 weeks after treatment, the visual analogue scale (VAS) pain scores of the experimental group were significantly lower (

P
<
0.05

); and the total incidence rate of adverse reactions was remarkably lower in the experimental group (

P
<
0.05

). On the basis of targeted nursing intervention, applying silver-zinc bacteriostatic cream obtains an obviously better clinical efficacy than silver sulfadiazine ointment in treating second-degree burn and works better in promoting wound healing, relieving pain sensation, and reducing adverse reactions.
Quality Prediction of Fused Deposition Molding Parts Based on Improved Deep Belief Network
Authors: Dong Hai , Gao Xiuxiu , Wei Mingqi
Published: December 2021

Tensile strength, warping degree, and surface roughness are important indicators to evaluate the quality of fused deposition modeling (FDM) parts, and their accurate and stable prediction is helpful to the development of FDM technology. Thus, a quality prediction method of FDM parts based on an optimized deep belief network was proposed. To determine the combination of process parameters that have the greatest influence on the quality of FDM parts, the correlation analysis method was used to screen the key quality factors that affect the quality of FDM parts. Then, we use 10‐fold cross‐validation and grid search (GS) to determine the optimal hyperparameter combination of the sparse constrained deep belief network (SDBN), propose an adaptive cuckoo search (ACS) algorithm to optimize the weights and biases of the SDBN, and complete the construction of prediction model based on the above work. The results show that compared with DBN, LSTM, RBFNN, and BPNN, the ACS‐SDBN model designed in this article can map the complex nonlinear relationship between FDM part quality characteristics and process parameters more effectively, and the CV verification accuracy of the model can reach more than 95.92%. The prediction accuracy can reach more than 96.67%, and the model has higher accuracy and stability.
Decentralized Multiagent Actor‐Critic Algorithm Based on Message Diffusion
Authors: Ding Siyuan , Li Shengxiang , Liu Guangyi , Li Ou , Ke Ke , Bai Yijie , Chen Weiye
Published: December 2021

The exponential explosion of joint actions and massive data collection are two main challenges in multiagent reinforcement learning algorithms with centralized training. To overcome these problems, in this paper, we propose a model‐free and fully decentralized actor‐critic multiagent reinforcement learning algorithm based on message diffusion. To this end, the agents are assumed to be placed in a time‐varying communication network. Each agent makes limited observations regarding the global state and joint actions; therefore, it needs to obtain and share information with others over the network. In the proposed algorithm, agents hold local estimations of the global state and joint actions and update them with local observations and the messages received from neighbors. Under the hypothesis of the global value decomposition, the gradient of the global objective function to an individual agent is derived. The convergence of the proposed algorithm with linear function approximation is guaranteed according to the stochastic approximation theory. In the experiments, the proposed algorithm was applied to a passive location task multiagent environment and achieved superior performance compared to state‐of‐the‐art algorithms.
Influence of GermlineBRCAGenotype on the Survival of Patients with Triple-Negative Breast Cancer
Authors: Villarreal-Garza Cynthia , Ferrigno Ana S. , Aranda-Gutierrez Alejandro , Frankel Paul H. , Ruel Nora H. , Fonseca Alan , Narod Steven , Chavarri-Guerra Yanin , Sifuentes Erika , Magallanes-Hoyos Maria Cristina , Herzog Josef , Castillo Danielle , Alvarez-Gomez Rosa M. , Mohar-Betancourt Alejandro , Weitzel Jeffrey N.
Published: December 2021

The presence of BRCA pathogenic variants (PV) in triple-negative breast cancer (TNBC) is associated with a distinctive genomic profile that makes the tumor particularly susceptible to DNA-damaging treatments. However, patients with BRCA PVs can develop treatment resistance through the appearance of reversion mutations and restored BRCA expression. As copy-number variants (CNV) could be less susceptible to reversion mutations than point mutations, we hypothesize that carriers of BRCA CNVs may have improved survival after treatment compared with carriers of other BRCA PVs or BRCA wild-type. Women diagnosed with stage I–III TNBC at ≤50 years at a cancer center in Mexico City were screened for BRCA PVs using a recurrent PV assay (HISPANEL; 77% sensitivity). Recurrence-free survival (RFS) and overall survival (OS) were compared according to the mutational status. Among 180 women, 17 (9%) were carriers of BRCA1 ex9–12del CNVs and 26 (14%) of other BRCA PVs. RFS at ten years for the whole cohort was 79.2% [95% confidence interval (CI), 72.3–84.6], with no significant differences according to mutational status. 10-year OS for the entire cohort was 85.3% (95% CI, 78.7–90.0), with BRCA CNV carriers demonstrating numerically superior OS rates other PV carriers and noncarriers (100% vs. 78.6% and 84.7%; log-rank P = 0.037 and P = 0.051, respectively). This study suggests that BRCA1 ex9–12del CNV carriers with TNBC may have a better OS, and supports the hypothesis that the genotype of BRCA PVs may influence survival by limiting treatment resistance mediated by reversion mutations among CNV carriers.

Significance:

Large CNV BRCA carriers in a cohort of young Mexican patients with TNBC had superior OS rates than carriers of other BRCA pathogenic variants (i.e., small indels or point mutations). We hypothesize that this is due to the resistance of CNVs to reversion mutations mediating resistance to therapy. If validated, these findings have important prognostic and clinical treatment implications for BRCA-associated breast cancers.
Tobacco Use in Sudan: Prevalence, Patterns, and Determinants – A Systematic Review
Authors: Elgoni Hala Elnazeer , Mohammed Mutaz
Published: December 2021

Background: The aim of this review was to investigate the published papers about prevalence, patterns, and determinants of tobacco use in Sudan. Methods: Four scientific databases were searched for relevant articles published between 1900 and 2020. Applying the inclusion criteria, which were original articles published in peer-reviewed journals, conducted on Sudanese in Sudan and about tobacco prevalence, patterns of use, or determinants, in either English or Arabic languages, 20 articles were included in this review. Results: Two articles (10%) were among the general population, 8 (40%) among schoolchildren and adolescents, 4 (20%) among medical and health professions university students, 3 (15%) studies among non-health professions university students, and 3 studies among special groups (prisoners, diabetic patients and school workers). The reported prevalence ranged from 1% to 47.5%, with significant differences between males and females. All patterns of tobacco use are practiced in Sudan. Peer pressures, having more money, and family tobacco user or friends were associated with tobacco use initiation. Conclusion: All patterns of tobacco utilization (cigarette smoking, Toombak dipping, and shisha) are practiced in Sudan as well as combined patterns. Tobacco prevalence ranges from 1–25% and 10–47.5% among adolescents and adults, respectively, indicating the need for intervention programs to enhance decreasing this high prevalence.