bluuebunny/crossref_metadata_2025 huggingface dataset:
Hiding Message Using a Cycle Generative Adversarial Network
Authors: Shi Wuzhen , Liu Shaohui
Published: March 2022

Training an image steganography is an unsupervised problem, because it is impossible to obtain an ideal supervised steganographic image corresponding to the cover image and secret message. Inspired by the success of cycle generative adversarial networks in unsupervised tasks such as style transfer, this article proposes to use a cycle generative adversarial network to solve the problem of unsupervised image steganography. Specifically, this article jointly trains five networks, i.e., a steganographic network, an inverse steganographic network, a hidden message reconstruction network, and two discriminative networks, which together constitute a hidden message cycle generative adversarial network (HCGAN). Compared with the recent image steganography based on generative adversative network, HCGAN provides more accurate supervised information, which makes the training process of HCGAN converge faster and the performance of the trained image steganography network is better. In addition, this article introduces an image steganographic network based on residual learning and shows that residual learning can effectively improve the performance of steganography. Furthermore, to the best of our knowledge, we are the first to propose an inverse steganographic network for eliminating steganographic message from steganographic images, which can be used to avoid steganographic message being discovered or acquired by a third party. The experimental results show that compared with the steganography based on generative adversarial network, the proposed HCGAN has a higher correct decoding rate, better visual quality of steganographic image, and higher secrecy.
Double Attention Based on Graph Attention Network for Image Multi-Label Classification
Authors: Zhou Wei , Xia Zhiwu , Dou Peng , Su Tao , Hu Haifeng
Published: March 2022

The task of image multi-label classification is to accurately recognize multiple objects in an input image. Most of the recent works need to leverage the label co-occurrence matrix counted from training data to construct the graph structure, which are inflexible and may degrade model generalizability. In addition, these methods fail to capture the semantic correlation between the channel feature maps to further improve model performance. To address these issues, we propose DA-GAT (a
D
ouble
A
ttention framework based on the
G
raph
A
ttention ne
T
work) to effectively learn the correlation between labels from training data. First, we devise a new channel attention mechanism to enhance the semantic correlation between channel feature maps, so as to implicitly capture the correlation between labels. Second, we propose a new label attention mechanism to avoid the adverse impact of a manually constructed label co-occurrence matrix. It only needs to leverage the label embedding as the input of network, then automatically constructs the label relation matrix to explicitly establish the correlation between labels. Finally, we effectively fuse the output of these two attention mechanisms to further improve model performance. Extensive experiments are conducted on three public multi-label classification benchmarks. Our DA-GAT model achieves mean average precision of 87.1%, 96.6%, and 64.3% on MS-COCO 2014, PASCAL VOC 2007, and NUS-WIDE, respectively, and obviously outperforms other existing state-of-the-art methods. In addition, visual analysis experiments demonstrate that each attention mechanism can capture the correlation between labels well and significantly promote the model performance.
The Function, Structure, and Origins of the ER Membrane Protein Complex
Authors: Hegde Ramanujan S.
Published: March 2022

The endoplasmic reticulum (ER) is the site of membrane protein insertion, folding, and assembly in eukaryotes. Over the past few years, a combination of genetic and biochemical studies have implicated an abundant factor termed the ER membrane protein complex (EMC) in several aspects of membrane protein biogenesis. This large nine-protein complex is built around a deeply conserved core formed by the EMC3–EMC6 subcomplex. EMC3 belongs to the universally conserved Oxa1 superfamily of membrane protein transporters, whereas EMC6 is an ancient, widely conserved obligate partner. EMC has an established role in the insertion of transmembrane domains (TMDs) and less understood roles during the later steps of membrane protein folding and assembly. Several recent structures suggest hypotheses about the mechanism(s) of TMD insertion by EMC, with various biochemical and proteomics studies beginning to reveal the range of EMC's membrane protein substrates.
Pleistocene Periglacial Processes and Landforms, Mid-Atlantic Region, Eastern United States
Authors: Merritts Dorothy J. , Rahnis Michael A.
Published: March 2022

Just as glaciers worldwide left a record of past advances and retreats that shifted latitudinally in response to oscillating Quaternary climate changes, so too have cold-climate conditions and permafrost left topographic and sedimentary signatures in former periglacial environments. This review documents widespread occurrence of past permafrost and intense frost action that led to rock fracturing, regolith production, and regolith-mantled slopes in the mid-Atlantic region of the United States during late Pleistocene cold-climate conditions. Strong signatures of thermal contraction cracking and brecciation from frost cracking exist where rocks and sediments are most frost susceptible, as with fissile shales. On sandstone hillslopes, frost weathering produced boulder-rich sediment that episodically flowed slowly down-slope during permafrost thaw, resulting in solifluction lobes and terraces in which colluvium moved cumulatively at least a kilometer. Radiocarbon dating, optically stimulated luminescence age control, and cosmogenic isotope studies constrain some periglacial features to the Last Glacial Maximum but also indicate longer residence times of regolith. ▪ Former permafrost and areas of intensive frost cracking extended over much of the mid-Atlantic region of the eastern United States during late Pleistocene cold glacial periods. ▪ Cold-climate conditions and permafrost left long-lasting topographic and sedimentary records with limited post-depositional erosion in the formerly periglacial mid-Atlantic region. ▪ Prominent relict periglacial landforms include polygon networks and frost wedges that are the result of thermal contraction cracking and brecciated rock formed by segregated ice and frost cracking. ▪ Widespread solifluction landforms are a topographic signature of freezing, thawing, and mass movement of mobile regolith produced by frost cracking, and some were active during the Last Glacial Maximum.
LSFM (OPFOS, SPIM, mSPIM, MuViSPIM) capillary techniques for CGE / CZE
Authors: Gradov Oleg
Published: March 2022

In modern systems for high-performance separation and quantification of nucleic acids, such as Fragment Analyzer, as well as in most DNA sequencing instruments using capillary electrophoresis, capillaries are available for visual observation inside the box. Hence, the front profiles can be visualized by the built-in devices or additional control and measurement systems of sensors embedded into the box or the external circuit for experimental and research purposes [1-7]. There are known differences in the front profile during laminar and electroosmotic flow, which makes possible to perform a real time parametric verification of the process in addition to the target analytical procedure. The advantage of capillary electrophoresis in the nucleic acid separation and sequencing is the path length of the detected radiation which is only n*10 μm (usually up to 50 μm). Therefore, a direct in situ observation and mapping of the sequence source by microscopic methods is possible. Working with capillary microscopy is most optimally implemented by the LSFM technique, which includes a number of branches, such as OPFOS, SPIM, mSPIM, MuViSPIM, which differ geometrically in the location and number of lenses and the possibility of relative rotation of the sample - capillary (or a turret of micro lenses around it). The presence of open protocols such as OpenSPIM and the built-in design of SPIM-like systems in standard boxes make it possible to produce separation with a small number of capillary channels using the appropriate number of SPIM heads or moving one SPIM head in space. In this case, both scanning along the entire capillary and monitoring of its specific section are possible.
Big Data Analysis Research on the Deep Integration of Intangible Cultural Heritage Inheritance and Art Design Education in Colleges and Universities
Authors: Xu Zhimin , Zou Daitie
Published: March 2022

Intangible cultural heritage involves a large number of national traditions, or folk unique knowledge, language, and customs, derived from folk dance and music as well as traditional medicine and other forms of art. China’s intangible cultural heritage plays a key role in the whole national traditional culture. Strengthening the protection of intangible cultural heritage and promoting its continuous development is an important way and inevitable choice to strengthen cultural self-confidence and build a cultural power. As the builders and successors of the socialist cause, college students must strengthen their cultural self-confidence and shoulder important responsibilities in the construction of a cultural power. Big data is a new technology in the Internet era. Using big data technology to realize the collection, preservation, retrieval, reproduction, integration, dissemination, and utilization of intangible cultural heritage information can better meet the requirements of the times, so as to provide new opportunities, conditions, and means for the inheritance and development of intangible cultural heritage. This article will discuss the use of big data to analyze the research talent training of the deep integration of intangible cultural heritage inheritance and art design education in colleges and universities. This article introduces the background and significance of intangible cultural heritage inheritance and educational integration, introduces its related methods, and then designs a new mode of intangible cultural heritage learning in colleges and universities based on big data. Finally, this article applies the model to college education and then investigates the students’ experience of the new model curriculum, and comes to the conclusion that the proportion of people who choose to like and very much like the new model is 69.3%; 83.3% of the people who chose to agree and strongly agree with the new model were helpful to themselves. In short, the application and design of the new curriculum model is still relatively successful.
Digital Finance Development and the Digital Transformation of Enterprises: Based on the Perspective of Financing Constraint and Innovation Drive
Authors: Luo Si
Published: March 2022

In the context of the digital economy, the digital transformation of enterprises, as an important accelerator of new economic and social development, cannot be separated from the support of financial resources. Based on the data of China’s A‐share listed companies from 2011 to 2020, this paper studies the influence of digital finance development on the digital transformation of enterprises and its mechanism of action. The empirical results demonstrate that digital finance development plays a significant role in promoting the digital transformation of enterprises, and the promotion effect is stronger for nonstate‐owned enterprises, but the promotion effect of digital finance development on the digital transformation of enterprises is weaker in western regions and peripheral cities than that in eastern and central regions and central cities. Digital finance development can alleviate the financing constraint of enterprises, thus facilitating the digital transformation of enterprises. Digital finance development can drive enterprise innovation, thus promoting the digital transformation of enterprises. Therefore, this paper suggests that the government should steadily advance digital finance development. Meanwhile, financial institutions should speed up the construction of digital platforms and strengthen their support for innovative projects. In addition, enterprises should actively seize the opportunities brought by digital finance development and accelerate the construction of digital transformation.
Assessment of Potential Benefits of Functional Food Characteristics of Beetroot Energy Drink and Flavored Milk
Authors: Ashraf Seema , Sayeed Syed Asad , Ali Rashida , Vohra Fahim , Ahmed Naseer , Alam Mohammad Khursheed
Published: March 2022

Objective. This study was designed to determine the antioxidant activity of the extracts of beetroot by using beetroot energy drink and flavored milk (products). Material & Methods. This experimental trial was conducted at Jinnah University for Women, Pakistan, under the approval of local institutional review board number JUW/DFST/RCB010/2020. All the materials such as beetroot, carrot, cucumber, and lemon were obtained commercially from which two products were formulated: beetroot energy drink (sample1) and flavored milk (sample 2). These formulated products were evaluated for quality analysis (pH and brix), phytochemical screening using the Keller‐Kiliani test, Salkowski’s test, Alkaline reagent test, lead acetate test, ferric chloride test, protein test, quantitative test of phenol, antioxidant activity, sensory analysis, and shelf life study. The paired t‐test was applied to detect significant differences between two samples. Results. The phytochemical analysis revealed that cardiac glycosides, phytosterol, flavonoids, and terpenoids were found in both energy booster drink (EBD) and flavored milk (FM) except phenolic compounds that were found only in EBD. The antioxidant capacity of beetroot juice was far greater than FM. The statistical sensorial analysis of FM and EBD reported a significant mean difference between most of the groups with p < 0.0001. Conclusion. This study concludes that energy drinks having beetroot indicated higher antioxidant capacity than flavored milk. The nutraceutical products (energy booster drink and flavored milk) containing beetroot are enriched with optimum quantities of proteins and fats and low carbohydrates at a stable pH with an adequate total energy content.
The Neutrophil to Lymphocyte Ratio in Poststroke Infection: A Systematic Review and Meta-Analysis
Authors: Khanzadeh Shokoufeh , Lucke-Wold Brandon , Eshghyar Fatemeh , Rezaei Katayoun , Clark Alec
Published: March 2022

Ischemic and hemorrhagic strokes have multiple downstream consequences for patients. One of the most critical is poststroke infection (PSI). The goal of this systematic review and meta-analysis was to critically evaluate the literature regarding the use of the neutrophil to lymphocyte ratio (NLR) as a reliable means to detect early PSI development, particularly poststroke pneumonia (PSP) development to help clinicians institute early interventions and improve outcomes. The following were the inclusion criteria: (1) cross-sectional, case-control, and cohort studies; (2) studies comparing NLR data from PSI or PSP patients to controls; and (3) studies with a control group of stroke patients without infection. There was not any language or publication preference. The Newcastle-Ottawa Scale was used by two writers to assess the quality of the included studies. We assessed the certainty of the associations with GRADE methods. Web of Science, PubMed, and Scopus were searched, and 25 studies were included in the qualitative review. Among them, 15 studies were included in the meta-analysis. Standardized mean difference (SMD) was reported with a 95% confidence interval (CI) for the NLR levels. Patients with PSI had significantly higher NLR levels than stroke patients without infection (

SMD
=
1.08

;

CI
 
95
%
=
0.78
‐
1.39

,

P

value < 0.001). In addition, the NLR levels of the stroke patients with pneumonia were significantly higher than those without pneumonia (

SMD
=
0.98

;

CI
 
95
%
=
0.81
‐
1.14

,

P

value < 0.001). However, data extracted from the qualitative review suggested that NLR could not predict urinary tract infection, sepsis, or ventriculitis in stroke patients. Our study indicated that NLR could be recommended as an inexpensive biomarker for predicting infection, particularly pneumonia, in stroke patients. It can help clinicians institute early interventions that can reduce PSI and improve outcomes.
Prediction Value of Epilepsy Secondary to Inferior Cavity Hemorrhage Based on Scalp EEG Wave Pattern in Deep Learning
Authors: Jiang Shishuang , He Xuenong
Published: March 2022

Objective. To search the predictive value of epilepsy secondary to acute subarachnoid hemorrhage (aSAH) based on EEG wave pattern in deep learning. Methods. A total of 156 cases of secondary epilepsy with lower cavity hemorrhage in our hospital were selected and divided into the late epilepsy group and the early epilepsy group according to seizure time, and the nonseizure group and the seizure group according to seizure condition. General data of patients were collected, the EEG types of each group were analyzed, and the disease recurrence rate, treatment effect, and symptom onset time were compared. Results. Rapid and slow and rapid blood flow velocity were the main abnormal manifestations of epilepsy secondary to inferior cavity hemorrhage, accounting for 33.3% and 18.6%, respectively. Compared with the seizure group, the proportion of type ii and type iii in the nonseizure group was higher, and the proportion of type ii and type iii in the early epilepsy group was higher than in the late epilepsy group (

P

 < 0.05). The diagnostic accuracy, missed diagnosis rate, misdiagnosis rate, specificity, and sensitivity of the EEG wave pattern were 94.9%, 3.2%, 1.9%, 91.7%, and 96.2%, respectively. Compared with the early epilepsy group, the recurrence rate of type iii and type iv in the late epilepsy group was higher (

P

 < 0.05). The effective rates of the attack group and the nonattack group were 72.7% and 97.0%, respectively. Compared with the attack group, the effective rate of the nonattack group was higher (

P

 < 0.05). The effective rates of the early epilepsy group and the late epilepsy group were 91.7% and 85.0%, respectively. Compared with the late epilepsy group, the effective rate of the early epilepsy group was higher (

P

 < 0.05). Compared with the early epilepsy group, the late epilepsy group had longer tonic-clonic seizures, atonic seizures, and absent seizures, and the difference between the groups was statistically significant (

P

 < 0.05). Conclusion. In aSAH secondary epilepsy disease prediction, based on indepth study of the scalp EEG wave type prediction, they play an important role, including aSAH high-risk secondary epilepsy wave types for V, III, and IV types, as well as early and late epilepsy associated with disease stage. Through the diagnosis method to predict the severity of disease, this builds a good foundation for clinical treatment. It is beneficial to improve the effective rate of treatment.
Creative Destruction Path Selection for Industrial Park Transformation and Upgrading under the Concept of Character Town in the Era of Big Data
Authors: Bai Yue , Li Xuewen
Published: March 2022

With the reshuffle of the global industrial structure, some industrial parks in China are facing problems such as unclear industrial positioning, unclear agglomeration effect, and lack of impetus for independent innovation. It is urgent to seek a way of transformation and upgrading. The arrival of the era of big data also provides new opportunities for the transformation of China’s industrial parks. In this context, the model of “character towns” proposed by Zhejiang Province provides a new concept for breaking the bottleneck of industrial park transformation and also provides a platform and space for the application of data technology and digital governance in the era of big data. Based on the theory of creative destruction and self-organization, this paper holds that the essence of industrial park transformation under the concept of character towns is the self-organization process of creative destruction and high-quality reconstruction. After sorting out the development process of parks in China, this paper divides industrial parks into production-oriented parks, consumption-oriented parks, and trade-oriented parks according to the economic activities classified by classical economics. By constructing a six-stage creative destruction model, this paper analyzes the path selection of transformation and upgrading of three types of parks under the concept of character towns and proposes that industrial structure replacement for the production-oriented parks, upgrading the consumption structure for the consumption-oriented parks, and change of trade control points for the trade-oriented parks are the possible transformation paths for the three types of parks.
Rhino-Orbital-Cerebral Mucormycosis in a Post-COVID-19 Patient from Peru
Authors: Ponce-Rosas Linda , Gonzales-Zamora Jose , Diaz-Reyes Nelson , Alarco-Cadillo Oliver , Alave-Rosas Jorge
Published: March 2022

Mucormycosis has been reported increasingly in patients affected by COVID-19, especially in India where the first cases were described. In Latin America, there is limited information about this association, mainly coming from Brazil, Mexico, and Peru. Herein, we report the case of a 66-year-old female that presented with rhino-orbital-cerebral mucormycosis, diabetic ketoacidosis, and COVID-19. The patient had the compromise of all the sinuses, orbital invasion, and intracranial extension. Isavuconazole was promptly initiated because amphotericin B was not available. She had a single open surgical debridement of necrotic tissues at the beginning of the diagnosis then multiple manual sessions to clear the residual or recurrent disease during approximately 5 months. Isavuconazole was effective and well-tolerated for 10 months without side effects. We highlight the importance of considering mucormycosis in post-COVID-19 patients with uncontrolled diabetes. The report emphasizes the favorable outcome of isavuconazole as an alternative therapy.
An Optimal Scheduling Method for Data Resources of Production Process Based on Multicommunity Collaborative Search Algorithm
Authors: Yin Yanlei , Wang Lihua , Tang Jun , Zhang Wanda , Niu Hongwei
Published: March 2022

Aiming at the problem of low response speed and unbalanced distribution of data resources of production process (DRPP) for the distributed workshop production environment, an optimization scheduling method of DRPP based on a multicommunity cooperative search algorithm is proposed. A heuristic data resource service scheduling framework including a load manager and dynamic scheduling engine is first built to deal with the uncertainty of data resource service response and the imbalance of resource allocation; a core scheduling optimization mathematical model with the objectives: resource service efficiency, reduced response time, and load balancing, is established. Then, a multicommunity cooperative search algorithm for the scheduling model is presented, and the mapping relationship between the particle position vector and resource allocation is established via binary coding. Thus, the optimization algorithm is mapped to discrete data space, and the multicommunity bidirectional driving evolutionary mechanism is used to realize the cooperative and interactive search between common and model community, which enhances the adaptability of the algorithm to dynamic random scheduling tasks. Finally, the effectiveness of the proposed method is verified by an example of multiprocess quality prediction service scheduling in silk production process, which provides an effective means for solving the complex scheduling problem of production process data.
Effects of Four Types of Watermelon Frost Combination Medications for the Treatment of Oral Ulcers: A Network Meta-Analysis
Authors: Liu Zhenhua , Dou Huiqin
Published: March 2022

Objective. The aim of this study is to identify the effectiveness of the four different watermelon frost combination medications in the treatment of oral ulcers through network meta-analysis and rank them based on their performances. Methods. Five randomized controlled studies of four distinct types of a combination medication for the treatment of oral ulcers were observed in numerous databases, and a network meta-analysis was conducted to evaluate the odds ratio (OR) and sequence of the diverse treatments using Stata software (version 13.0). The underlined studies were categorized into two groups: the control group (watermelon frost alone) and the observation group (one of four watermelon frost combinations). Results. The study comprised of 598 cases and the findings indicated that the pooled OR and 95% CI of oral ulcers that improved relative to watermelon frost alone were 3.26 (1.28 to 8.30) for watermelon frost and Kangfuxin fluid, 8.74 (2.94 to 26.02) for watermelon frost and erythromycin, 6.53 (1.81 to 23.50) for watermelon frost and metronidazole, and 2.62 (0.63 to 10.95) for watermelon frost and cydiodine buccal tablets. The study showed the significant efficacy of watermelon frost combination medications. In terms of clinical efficacy, the combination of watermelon frost and erythromycin was the most promising concomitant medication. It had an 86.3 surface under cumulative ranking (SUCRA). Conclusion. All the studied watermelon frost combinations were effective against oral ulcers validating the use of watermelon frost for oral ulcers. The combination of watermelon frost and erythromycin is the most promising candidate among the four combinations for the treatment of oral ulcers.
[Retracted] Correlation of Carotid Artery Intima‐Media Thickness with Calcium and Phosphorus Metabolism, Parathyroid Hormone, Microinflammatory State, and Cardiovascular Disease
Authors: Huang Peng , Tan Junhua , Gu Xianjun , Huang Meiying , Huang Feifan , Ma Ruiying , Wang Jie
Published: March 2022

The internal thickness of the carotid artery is the vertical distance between the intima of the carotid artery and the middle mold. Its normal thickness is less than 1 mm. It can be used to judge the degree of arteriosclerosis. Under normal circumstances, the change of the internal thickness of the carotid artery is caused by cardiovascular disease. The purpose of this article is to study the relationship between the thickness of the carotid artery and the metabolism of calcium and phosphorus, parathyroid hormone, microinflammatory state, and cardiovascular disease. This article uses ultrasound measurement to measure the IMT of ESRD patients and carotid arteries with normal renal function. The analysis includes blood pressure, blood phosphorus, blood calcium, blood creatinine, blood urea nitrogen, blood sugar, glycosylated hemoglobin, blood lipids, parathyroid hormone, and C reaction. The correlation between clinical indicators includes protein and carotid IMT in ESRD patients which can be used in designing a diagnostic plan for patients through correlation research. The results showed that the carotid artery IMT of ESRD nondialysis patients was 13% thicker than that of those with normal renal function, and it was significantly positively correlated with age, blood pressure, blood phosphorus, glycosylated hemoglobin, and C‐reactive protein. The correlation ratio with calcium and phosphorus was about 0.1.
Travel Matrix Enabled Delta-Based Roadside Units Deployment for Vehicular Ad Hoc Networks: A Case of Kigali City
Authors: Twahirwa Evariste , Laha Moyukh , Rwigema James , Datta Raja
Published: March 2022

Placements of Road Side Units (RSUs) are an important issue of vehicular networks in urban areas. The merged cost of procurement, installation, and maintenance of intelligent RSUs is high, and therefore, cost-effective deployment strategies are necessary. In this article, we propose a scheme that optimally deploys intelligent roadside units using a travel matrix scheme based on the classical delta strategy where urban vehicles are involved in RSUs communication in the course of their travel times. Four (4) vehicular communication modes are studied, namely, (a) travel matrix based on delta RSUs deployment communication, (b) road intersection-based RSUs deployment communication, (c) road segmentation, and (d) free vehicle-to-vehicle communication. A baseline algorithm is suggested to determine the optimal locations of RSUs in terms of their geographical positions. A travel matrix technique is proposed to trace vehicles’ routeways and travel times in some points of interest (POI). Our intention is to seek an approach that reduces the required number of RSUs and ensures greater network performance effectiveness in terms of packets delivery ratio, throughput, message delay, and jitter; from our study, travel matrix delta-based placement of RSUs becomes the best in our case study scenario. The simulation results indicate that the travel matrix deployment is a suitable deployment scheme in the case study area since it can reduce the number of RSUs while enhancing the vehicular communication abilities under different vehicle density scenarios.
Apnea in a Two-Week-Old Infant Infected with SARS-CoV-2 and Influenza B
Authors: Maddali Radhika , Cervellione Kelly L. , Lew Lily Q.
Published: March 2022

Paucity of data exists on presenting symptoms and outcomes in infants with COVID-19. Reports of coinfection with COVID-19 and influenza B are sparse in the literature. Coinfection was uncovered during evaluation of neonatal apnea. Apnea has been reported in infants with SARS-CoV-2 infection, though it is rare. We describe a 2-week-old healthy term infant presenting with apnea and coinfection. The infant had a mild clinical course and complete recovery.
MR-Pareto: A Multiattribute Opportunistic Routing Method Based on Pareto Optimal Solution for Mobile Crowdsensing
Authors: Han Xiao , Wang Huiqiang , Tan Jing , Lv Hongwu , Wang Chengbo
Published: March 2022

Mobile crowdsensing (MCS) is a new perception mode for solving large-scale mobile sensing tasks. Traditional data transmission methods are inapplicable, as the MCS is affected by coverage, user preference, and network access cost. Opportunistic network data transmission schemes in MCS have recently witnessed a surge of research efforts due to their ability of high delivery and low consumption. However, existing works only focus on the impact of the geographical location of nodes on user needs or the interaction between social information and data, which do not take into account the temporal and spatial characteristics of nodes. To address these issues, this paper proposes a multiattribute routing method based on Pareto optimal (MR-Pareto) solution to construct a balance between the energy consumption and resource constraints of nodes in transmission protocols. First, the attribute relationship between nodes is analyzed, which was aimed at selecting the nodes within a contact time threshold. Then, based on a nondominated sorting approach, we achieve a Pareto optimal set of candidate nodes. Finally, the relay nodes for forwarding messages are determined by comparing the cache size and the remaining energy. The experimental results demonstrate that our proposed method has low network overhead, low packet loss, and high message delivery rate, compared to epidemic and prophet routing strategies.
Phenotypic Diversity Assessment of Okra (Abelmoschus Esculentus (L.) Moench) Genotypes in Ethiopia Using Multivariate Analysis
Authors: Mohammed Jemal , Mohammed Wassu , Shiferaw Eleni
Published: March 2022

Okra is a minor crop that has not gained research attention in Ethiopia. Characterization of such underutilized crops has important implications for their utilization. Thus, this study was conducted to assess the genetic diversity of okra genotypes in Ethiopia using agromorphological and biochemical markers. Thirty-six okra genotypes were evaluated for 29 agromorphological and biochemical traits. The results of the analysis of variance showed significant differences among genotypes for most of the traits, except for the number of flower epicalyx and fruit diameter. Results of the principal component analysis indicated that the first eight principal component axes accounted for 3.83 to 30.54% and 82.44% of the total variability. Genetic distances estimated by Euclidean distances from 27 traits ranged from 3.55 to 14.49. The 36 genotypes were grouped into four distinct clusters from the Euclidean distance matrix using the unweighted pair group method with arithmetic mean (UPGMA). The first cluster contained 24 (66.66%) genotypes, and the second cluster contained 10 (27.77%) of the genotypes. This study showed the presence of considerable genetic variation among the genotypes for most of the traits, including fruit yield, seed yield, and nutrient content of seeds, indicating the possibility of using these genotypes to develop okra varieties with high fruit-yielding and good nutritional content.
A Sensor-Based IoT Data Collection and Marine Economy Collaborative Innovation Method
Authors: Liu Tao , Wu Fan
Published: March 2022

Traditional marine pastures have made great contributions to human beings, but traditional marine pastures have also caused major harm to the marine natural environment. Modern technology represented by artificial intelligence has broad application prospects and significant potential and has the ability to innovate and enhance the conventional marine ranching business that is currently in recession. The particularity of China’s marine ranching industry determines the combination of technologies such as underwater robots and the Internet of Things with the development of marine ranching to create a sustainable intelligent marine ranching industry in China. The growth of China’s national economy is largely influenced by the development of the country’s financial services industry. In order to better support the development of the real economy, it is necessary to establish a financial service system with controllable risks and complementary activities. This paper proposes to use the method of Internet of Things data collection combined with sensors to conduct economic analysis. By taking a number of data in recent years for research and analysis, the results show that financial service industry innovation has become an important part of improving the competitiveness of the industry and an important driving force for economic growth. The Internet of Things (IoT) business in China is a fast-growing industry with huge potential. From the perspective of international comparison, our country is currently in the early stage of the development of the Internet of Things, and a certain technology, industry, and application foundation has been established in the early stage of development. In the financial services business, the visual tracking provided by IoT technology has innovative potential. Introducing IoT technology into financial service business and identifying the driving force and process of financial innovation have practical significance for accelerating financial innovation.
Clinical Nursing Pathway Improves Therapeutic Efficacy and Quality of Life of Elderly Patients with Acute Myocardial Infarction
Authors: Zhang Yumei , Chen Guichun , Huang Dandan , Luo Shue
Published: March 2022

Purposes. To clarify the impacts of clinical nursing pathway (CNP) on therapeutic efficacy and quality of life (QOL) of senile acute myocardial infarction (AMI) patients. Methods. The clinical records of 177 elderly AMI patients who received treatment in the First Hospital of Quanzhou Affiliated to Fujian Medical University were retrospectively studied. They were assigned into the control group (the Con;

n
=
79

; from June 2019 to January 2020) and the research group (the Res;

n
=
98

; from February 2020 to July 2020). Emergency percutaneous coronary intervention (PCI) was performed in all the cases. Additionally, the Con and the Res were given routine care and CNP, respectively. The two groups were compared in total emergency treatment time, hospital stay, medical expenses, recurrence rate of myocardial infarction (MI), overall response rate (ORR), incidence of complications, cardiac function indexes, negative mood scores, QOL, and nursing satisfaction. Results. The ORR was higher, and the incidence of complications was lower in the Res versus the Con; the Res presented significantly less emergency treatment time and hospitalization and statistically lower medical expenses and recurrence rate of MI; the Res outperformed the Con in cardiac function indexes, alleviation of negative mood, QOL, and nursing satisfaction. Conclusions. While effectively improving clinical efficacy and reducing the incidence of complications, CNP can relieve the bad mood of elderly patients with AMI and improve their cardiac function, QOL, and nursing satisfaction, which is worthy of clinical promotion.
Characteristics of Middle-Lower Ordovician Ultradeeply Buried Carbonate Reservoirs in Shunbei Area, Tarim Basin—A Case Study from Well SHBP1
Authors: Chongyang Xiao , Rui Zhao , Heng Fu , Cheng Huang , Jun Han , bo Lin
Published: March 2022

Fracture-pore complexes, located at fault zones of Darriwilian carbonates, are the main exploration targets in the Shunbei area, Tarim Basin. This article focuses on the carbonate characteristics in the Lower Ordovician of Well ShunbeiPeng1 (SHBP1), the carbonate is sandwiched by two trending NW-SE deep-seated, strike-slip faults in the Shuntuoguole uplift. Based on detailed core investigation and careful petrographic examination, two main reservoir types, denoting microquartz and dolomite, are recognized. The former is mainly constrained in the lower part of the sampled core and gradually evolves to the latter with progressively decreases of silica. Integrated isotopic geochemistry (C, O, and Sr) and fluid inclusion microthermometry suggest that the fluids are hydrothermal origin and migrate along deep-seated strike-slip faults, forming favorable carbonate reservoirs. The fault-controlled hydrothermal reservoirs, characterized by the strong amplitude in the seismic profile, would be the most promising exploration area in deeply buried carbonates in the Tarim Basin, particularly in the Shuntuoguole area.
Outcomes of Congenital Nasolacrimal Duct Obstruction Surgery Converted into Balloon Dilation and Silicone Intubation due to Probing Difficulty
Authors: Sagiv Oren Yaakov , Nemet Achia , Achiron Asaf , Neumann Doron , Tuuminen Raimo , Spierer Oriel
Published: March 2022

Background. To report the outcomes of balloon catheter dilatation and silicone intubation as a sequential secondary surgery under the same anesthesia, a stepwise approach for congenital nasolacrimal duct obstruction (NLDO) when probing and irrigation as primary procedure fails. Methods. A retrospective study included children with NLDO who underwent probing and irrigation only, and those who underwent in the same surgery under anesthesia, adjunct balloon catheter dilation and silicone intubation due to difficulty of the probe passage or fluid regurgitation from the punctum. The primary outcome was surgical success defined as resolution of preoperative symptoms and signs at 1 month. Results. A total of 105 NLDO cases were included. Eighty-four cases underwent probing and irrigation only, whereas 21 cases required balloon dilation and silicone intubation consecutively after the first procedure. Patient age at surgery was higher for those requiring balloon dilatation and intubation (30.3 ± 8.0 months) when compared to those with probing and irrigation only (22.4 ± 10.3 months,

p
<
0.001

). The onset of symptoms, preoperative clinical findings regarding tearing and discharge and gender distribution of patients were comparable between the two groups. During the follow-up, the overall success rate for probing and irrigation only was 76.2% (64 out of 84 cases) and for balloon dilatation and silicone tube intubation was 90.5% (19 out of 21 cases). Conclusions. The surgical team may prepare to proceed with secondary surgery under the same anesthesia after the initial attempt of probing and irrigation. This stepwise two-stage approach in patients with congenital NLDO failing primary surgery resulted in a high success rate with minimal interventions, avoiding repeated general anesthesia.
Physical Activity Surveillance in Adolescents with Type 1 Diabetes: A Pilot Mixed-Methods Investigation
Authors: Giblin Susan , Scully Paul , Evers Julie , Dalton Niall , Hayes Grainne , Donnelly Alan , Orla Neylon O. , O’Gorman Clodagh
Published: March 2022

Type 1 diabetes (T1D) affects over 2,500 children in Ireland. Insulin replacement is the mainstay of treatment for T1D, and physical activity (PA) is an important, modifiable lifestyle factor for sustaining health. Surveillance of PA for both research and clinical purposes in paediatric T1D has been limited. This study deployed both quantitative (accelerometry) and qualitative (self-report) measures to assess habitual PA patterns in children with T1D. Twenty-one participants (9 females, 12 males) between 10 and 17 years (mean

13.7
±
1.94

years) were recruited from an Outpatients Paediatric Diabetes Clinic. Total steps, standing time (minutes (mins)) and sitting time (mins) were recorded using the activPAL 3 microactivity monitor. Clinical parameters (HbA1c, insulin regimen, and weight centiles) were measured. A self-report diary was used to measure perceived activity levels. The findings of this study show that participant children with T1D are not achieving the required steps per day to sustain physical health (recommended minimum 11,500). Females (

mean
=
7,306
 
steps
±
5,468

) achieved significantly less (

p
=
0.001

) steps per day compared to males (

10,806
 
steps
±
5,904

). No significant differences were found between genders for sitting time or standing time. Overweight or obesity was identified in 44% of female participants and 15% of male participants. Mean HbA1c for both females 8.25% (67 mmol/mol) and males 7.97% (64 mmol/mol) was above the International Society for Pediatric and Adolescent Diabetes (ISPAD) recommended <7.0% (53 mmol/mol) for children. Further research is warranted to investigate PA promotion strategies in populations of children with paediatric T1D.
Research on Urban Economic High-Performance Forecasting Method Based on Deep Confidence Network
Authors: Yang Bowen
Published: March 2022

To address the complexity of urban economic data and the problem that traditional forecasting methods do not fully utilize the correlation of data, resulting in low prediction accuracy, an urban economic forecasting model based on the fusion of deep belief neural (DBN) and long-short term memory (LSTM) is proposed. The model is based on a combination of DBN and LSTM. The model first uses bandpass filtering to denoise the urban economic data and then determines the prediction starting point of the model based on the root-mean-square and cliff features in the trend diagram of the urban economy; secondly, the optimised 4-layer DBN network is used for deep feature extraction and training and testing of the LSTM. The reliability of the proposed model is demonstrated through urban economic experiments, and the prediction results are compared with those of traditional LSTM, BP (back propagation) neural network, and DBN-BP model to verify the effectiveness of the model.
Design and Application of Interactive Algorithm for Advertising Media Screen Based on Smart Sensor
Authors: Chen Si , Cheng Dandan , Zhou Quan
Published: March 2022

Touch is one of the most important human senses. With the popularization of touch-screen mobile phones, tablet computers, and other devices, touch-screen interactive technology has become a norm in people’s daily lives, and advertisements that were once dominated by vision and hearing have added an interactive experience in the dimension of touch. Traditional advertising media screens can only complete simple information dissemination functions and cannot interact with users in a two-way manner. They can only receive information one-way and passively and lack interactivity. Touch-screen interactive advertising forms a good interaction with the target audience, thereby disseminating advertising information to achieve the purpose of promotion or brand image building. This paper designs a set of advertising media screen interaction systems based on smart sensors, including a gesture interaction module, a remote interaction module, and a touch interaction module. The gesture interaction module can recognize 5 static gestures and send gesture commands to control the advertising media screen. The remote interaction module can remotely control the advertising media screen, and the touch interaction module can control the advertising media screen through the touch screen. According to the functional requirements, the overall design of software and hardware is given, and the technical background of each module of the software is introduced. Next, the depth image-based gesture recognition method is studied. The number of fingers and the center distance feature are fused as feature vectors, and the weighted template matching method is used to classify and recognize gestures. Finally, the design and implementation of the interactive system are introduced.
Construction of an English Research Learning Model Based on Constructivism and Data Mining under a Cloud Computing Platform
Authors: Xu Dongyang
Published: March 2022

This paper attempts to explore and summarize the teaching activities of English research learning based on constructivism and data mining under the guidance of advanced teaching concepts and the support of cloud computing platforms and to explain the problems reflected in the practice of English research learning in the current environment. Constructing a teaching model based on constructivism and data mining on the cloud computing platform is a beneficial attempt to combine the new teaching design theory with teaching practice. Based on constructivist learning theory and data mining technology, combined with current English teaching practice, this paper discusses the integration of English research-based learning and data mining technology. Try to implement it in English teaching to improve English learners’ autonomous inquiry ability. The purpose is to promote students to form a positive learning attitude and good learning strategies and cultivate students’ innovative spirit and practical ability to adapt to the requirements of the times for talents. The combination of cloud computing technology and data mining has created a new English learning model, which can greatly improve the efficiency of English learning and provide a good reference for the English learning model.
Asymptotic Properties for Estimators in a Semiparametric EV Model with NA Errors and Missing Responses
Authors: Zhang Jing-jing , Liu Cheng-Liang
Published: March 2022

This article deals with the semiparametric errors‐in‐variables (EV) model yi = ξiβ + g(ti) + ϵi, xi = ξi + μi, where yi are the random missing response variables, (ξi, ti) are the design points, ξi are the potential variables observed with measurement errors μi, and random errors ϵi are negatively associated (NA) variables. In addition, we need to estimate the unknown slope parameter β and nonparametric component g(·). In order to solve the missing responses, we introduce three different approaches to get the estimators of β and g(·). Meanwhile, we study the asymptotic properties for all the estimators. The final results show that the strong consistent rates for all the estimators can achieve o(n−1/4). The asymptotic normality for all the estimators is considered. We compare the finite sample performance of the three estimators by simulation as well.