bluuebunny/crossref_metadata_2025 huggingface dataset:
Short term associations of ambient nitrogen dioxide with daily total, cardiovascular, and respiratory mortality: multilocation analysis in 398 cities
Authors: Meng Xia , Liu Cong , Chen Renjie , Sera Francesco , Vicedo-Cabrera Ana Maria , Milojevic Ai , Guo Yuming , Tong Shilu , Coelho Micheline de Sousa Zanotti Staglior , Saldiva Paulo Hilario Nascimento , Lavigne Eric , Correa Patricia Matus , Ortega Nicolas Valdes , Osorio Samuel , Garcia  , Kyselý Jan , Urban Aleš , Orru Hans , Maasikmets Marek , Jaakkola Jouni J K , Ryti Niilo , Huber Veronika , Schneider Alexandra , Katsouyanni Klea , Analitis Antonis , Hashizume Masahiro , Honda Yasushi , Ng Chris Fook Sheng , Nunes Baltazar , Teixeira João Paulo , Holobaca Iulian Horia , Fratianni Simona , Kim Ho , Tobias Aurelio , Íñiguez Carmen , Forsberg Bertil , Åström Christofer , Ragettli Martina S , Guo Yue-Liang Leon , Pan Shih-Chun , Li Shanshan , Bell Michelle L , Zanobetti Antonella , Schwartz Joel , Wu Tangchun , Gasparrini Antonio , Kan Haidong
Published: March 2021

Objective

To evaluate the short term associations between nitrogen dioxide (NO
2
) and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide, using a uniform analytical protocol.

Design

Two stage, time series approach, with overdispersed generalised linear models and multilevel meta-analysis.

Setting

398 cities in 22 low to high income countries/regions.

Main outcome measures

Daily deaths from total (62.8 million), cardiovascular (19.7 million), and respiratory (5.5 million) causes between 1973 and 2018.

Results

On average, a 10 μg/m
3
increase in NO
2
concentration on lag 1 day (previous day) was associated with 0.46% (95% confidence interval 0.36% to 0.57%), 0.37% (0.22% to 0.51%), and 0.47% (0.21% to 0.72%) increases in total, cardiovascular, and respiratory mortality, respectively. These associations remained robust after adjusting for co-pollutants (particulate matter with aerodynamic diameter ≤10 μm or ≤2.5 μm (PM
10
and PM
2.5
, respectively), ozone, sulfur dioxide, and carbon monoxide). The pooled concentration-response curves for all three causes were almost linear without discernible thresholds. The proportion of deaths attributable to NO
2
concentration above the counterfactual zero level was 1.23% (95% confidence interval 0.96% to 1.51%) across the 398 cities.

Conclusions

This multilocation study provides key evidence on the independent and linear associations between short term exposure to NO
2
and increased risk of total, cardiovascular, and respiratory mortality, suggesting that health benefits would be achieved by tightening the guidelines and regulatory limits of NO
2
.
Magmatic activity and hydrocarbon potential revealed by Paleozoic collapse structures in the Hangjinqi area, northern Ordos Basin, China
Authors: Ji Tianyu , Wang Donghui , Gui Pingjun , Pu Renhai , Wu Xiaochuan , Wu Xueqiong
Published: March 2021

Collapsed reflections of Lower Ordovician carbonates and upper Carboniferous – lower Permian coal-bearing strata occur below the middle Permian lower Shihezi Formation in the Hangjinqi area, northern Ordos Basin. This study takes advantage of three-dimensional seismic data, logging data, core data, and well-testing data to investigate the genesis of the collapsed reflections and their implications for hydrocarbon potential. These collapse structures have a subcircular appearance in map view. The columnar reflections in the basement and the volcanic tuff in the lower Shihezi Formation around collapse structures indicate that the formation of these structures are related to magmatic activity. Most of the collapse structures terminate upward in the H1 member of the lower Shihezi Formation, which explains its greater thickness and supports the hypothesis that magmatic activity occurred during the depositional stage of the lower Shihezi Formation in the early middle Permian. The collapse structures can increase the thickness and space of the reservoirs, and the collapse of magma conduit can also increase the thickness of the regional sedimentary cap rock above the collapse structures and improve the sealing capacity of the cap rock. These results provide insights into the magmatic activity and hydrocarbon potential of Paleozoic rocks in the Ordos Basin.
Knowledge Management Practices in the Indian Steel Industry (A Comprehensive Analysis of Public Sector Units)
Authors: Arora Rajesh Kumar , Date Hema
Published: March 2021

Knowledge is recognised as a strategic resource and companies have started managing organisational knowledge to gain sustainable competitive advantage. Considerable efforts and investments have been made by organisations on knowledge management (KM) initiatives to achieve business excellence. The objective of KM is to create, store, extract, disseminate and make the requisite knowledge available for intelligent business-related decision-making. Extensive literature promoting KM exists, which focuses on KM factors in isolation. Empirical studies showing the interconnection between KM factors and organisational outcomes are still rare. This paper is the result of industry-specific empirical research conducted in India. Public sector units are dominant in the Indian steel sector, led by the Steel Authority of India (SAIL), which operates five integrated steel plants, and Rashtriya Ispat Nigam Limited (RNIL) operating one plant. Respondents have been selected from the Bhilai Steel Plant, a unit of SAIL and Vizag Steel Plant, the only unit of RNIL. Both units are almost contemporary in introducing KM initiatives in their organisations, circa 2002. The paper proposes a research model of KM comprising of different KM factors (enablers, processes, practices and organisational outcomes) identified from the extant literature. These are hypothesised to impact organisational performance and creativity of the firm. Hypotheses have then been tested with structural equation modelling (SEM) by using a survey. Findings of this study reveal that some KM factors have a significant impact on organisational performance and organisational creativity.
Parabolic Equation Modeling of Scholte Waves and Other Effects Along Sloping Fluid-Solid Interfaces
Authors: Collins Michael D. , Ramamurti Adith
Published: March 2021

Several methods for handling sloping fluid–solid interfaces with the elastic parabolic equation are tested. A single-scattering approach that is modified for the fluid–solid case is accurate for some problems but breaks down when the contrast across the interface is sufficiently large and when there is a Scholte wave. An approximate condition for conserving energy breaks down when a Scholte wave propagates along a sloping interface but otherwise performs well for a large class of problems involving gradual slopes, a wide range of sediment parameters, and ice cover. An approach based on treating part of the fluid layer as a solid with low shear speed is developed and found to handle Scholte waves and a wide range of sediment parameters accurately, but this approach needs further development. The variable rotated parabolic equation is not effective for problems involving frequent or continuous changes in slope, but it provides a high level of accuracy for most of the test cases, which have regions of constant slope. Approaches based on a coordinate mapping and on using a film of solid material with low shear speed on the rises of the stair steps that approximate a sloping interface are also tested and found to produce accurate results for some cases.
Herlyn Werner Wunderlich Syndrome with Vagino-umbillical Fistula: A Most Unique Presentation
Authors: Valera Pamela Grace Vidal , Domingo Madonna Victoria Calderon
Published: March 2021

The Herlyn–Werner–Wunderlich (HWW) syndrome is an uncommon Mullerian duct anomaly composed of a triad of obstructed hemivagina, renal agenesis, uterine didelphys with a prevalence of [Formula: see text] females. Aside from its usual presentation of cyclic hypogastric pain and abdominal mass, there has been no other reported case in literature of the syndrome presenting with a vagino-umbilical fistula. Presented here is a unique case of a 35-year-old woman presenting with purulent, foul-smelling discharge extruding from a fistula on her umbilicus and her vagina associated with a tender hypogastric mass. Three-dimensional transvaginal ultrasonography aided the diagnosis of HWW syndrome with a concomitant vagino-umbilical fistula. Excision of the vaginal septum together with antibiotic coverage resolved her symptoms. The syndrome’s embryopathogenesis, classification, diagnostics, definitive surgical management and other issues during follow up are discussed.
Siloxane Deposition on the Ni-YSZ Solid Oxide Fuel Cell Anode Exposed to Bio-Syngas
Authors: Tian Jiashen , Milcarek Ryan J.
Published: March 2021

Siloxane, a common contaminant present in biogas, is known for adverse effects on cogeneration prime movers. In this study, the siloxane deposition products and mechanism in the solid oxide fuel cell nickel-yttria stabilized zirconia (Ni-YSZ) anode are investigated analytically and experimentally. An SOFC with Ni-YSZ anode and pure Ni/YSZ pellets were exposed to a simulated biogas-reformate fuel with octamethylcyclotetrasiloxane (D4) contamination at 750 °C. The electrochemical characterization results show that the SOFCs performance degradation caused by D4 contamination is irreversible. Morphology and XRD results illustrate that silicon and carbon deposition can both be detected in the anode and pellets. Graphite, SiC and SiO2 are all possible products based on the results of XRD test. According to the formation of graphite and SiC, the new mechanism suggests that carbon is also an essential factor in siloxane contamination of Ni-YSZ anodes besides silicon, which can be explained by the catalytic and electrochemical analysis.
Reducing Zinc Redistribution and Extending Cycle Life Via Electrochemical Synthesis of Zinc/Zinc Oxide Anodes in Rechargeable Alkaline Batteries
Authors: Kolhekar Snehal , Nyce Michael , Banerjee Sanjoy
Published: March 2021

Redistribution of zinc over the electrode surface, also known as shape change, is a major problem and a cause of failure in alkaline zinc anode batteries. To mitigate this phenomenon, we propose a scalable approach based on an in situ formed, highly porous electrochemically synthesized ZnO matrix with uniformly electrodeposited zinc particles. This results in ∼70% improvement in cycle life performance at a rate of 10 mA cm−2 compared to control Zn anodes, which have not gone through the formation process. A quantitative electrolyte analysis revealed under-saturated zincate ion concentration in the electrochemically synthesized ZnO/Zn cells indicating reduced zincate movement. Post mortem analysis of the anodes indicated higher retention of both Zn and ZnO on the electrochemically synthesized ZnO anodes signifying reduced redistribution of active material. Image analysis of the cycled anodes revealed a narrower Zn particle size distribution (62−79 μm) in contrast to a wider particle size distribution of 51–96 μm observed in the control anodes. The formation approach results in electrochemically synthesized ZnO/Zn anodes providing a stable ZnO matrix in which Zn particles retain their localized distribution on cycling better than control electrodes conventionally made by pasting zinc particles together with a binder.
Examining the benefits of cold exposure as a therapeutic strategy for obesity and type 2 diabetes
Authors: Ivanova Yoanna M. , Blondin Denis P.
Published: March 2021

The pathogenesis of metabolic diseases such as obesity and type 2 diabetes are characterized by a progressive dysregulation in energy partitioning, often leading to end-organ complications. One emerging approach proposed to target this metabolic dysregulation is the application of mild cold exposure. In healthy individuals, cold exposure can increase energy expenditure and whole body glucose and fatty acid utilization. Repeated exposures can lower fasting glucose and insulin levels and improve dietary fatty acid handling, even in healthy individuals. Despite its apparent therapeutic potential, little is known regarding the effects of cold exposure in populations for which this stimulation could benefit the most. The few studies available have shown that both acute and repeated exposures to the cold can improve insulin sensitivity and reduce fasting glycemia in individuals with type 2 diabetes. However, critical gaps remain in understanding the prolonged effects of repeated cold exposures on glucose regulation and whole body insulin sensitivity in individuals with metabolic syndrome. Much of the metabolic benefits appear to be attributable to the recruitment of shivering skeletal muscles. However, further work is required to determine whether the broader recruitment of skeletal muscles observed during cold exposure can confer metabolic benefits that surpass what has been historically observed from endurance exercise. In addition, although cold exposure offers unique cardiovascular responses for a physiological stimulus that increases energy expenditure, further work is required to determine how acute and repeated cold exposure can impact cardiovascular responses and myocardial function across a broader scope of individuals.
Icing after eccentric contraction-induced muscle damage perturbs the disappearance of necrotic muscle fibers and phenotypic dynamics of macrophages in mice
Authors: Kawashima Masato , Kawanishi Noriaki , Tominaga Takaki , Suzuki Katsuhiko , Miyazaki Anna , Nagata Itsuki , Miyoshi Makoto , Miyakawa Motoi , Sakuraya Tohma , Sonomura Takahiro , Arakawa Takamitsu
Published: March 2021

Icing blunted the muscle regeneration by perturbing the infiltration of polynuclear and mononuclear cells into necrotic myofibers and the phenotypic dynamics of macrophages rather than affecting the myogenic regulatory factors. Because of icing, the disappearance of necrotic muscle debris was retarded, coinciding with the delayed emergence and sustained accumulation of Pax7+ cells within the regenerating area. The expression patterns of TNF-α and IL-10 were altered by icing consistent with the perturbation of the macrophage phenotype.
PPI‐GA: A Novel Clustering Algorithm to Identify Protein Complexes within Protein‐Protein Interaction Networks Using Genetic Algorithm
Authors: Shirmohammady Naeem , Izadkhah Habib , Isazadeh Ayaz
Published: March 2021

Comprehensive analysis of proteins to evaluate their genetic diversity, study their differences, and respond to the tensions is the main subject of an interdisciplinary field of study called proteomics. The main objective of the proteomics is to detect and quantify proteins and study their post‐translational modifications and interactions using protein chemistry, bioinformatics, and biology. Any disturbance in proteins interactive network can act as a source for biological disorders and various diseases such as Alzheimer and cancer. Most current computational methods for discovering protein complexes are usually based on specific topological characteristics of protein‐protein networks (PPI). To identify the protein complexes, in this paper, we, first, present a new encoding method to represent solutions; we then propose a new clustering algorithm based on the genetic algorithm, named PPI‐GA, employing a new multiobjective quality function. The proposed algorithm is evaluated on two gold standard and real‐world datasets. The result achieved demonstrates that the proposed algorithm can detect important protein complexes, and it provides more accurate results compared with state‐of‐the‐art protein complex identification algorithms.
Effect of 3D Metal on Electrochemical Properties of Sodium Intercalation Cathode P2-NaxMe1/3Mn2/3O2 (M = Co, Ni, or Fe)
Authors: Phuong Le Nam Pham , Huynh Nguyen Le Thanh , Le Bao Phan An , Ngoc Nguyen Dieu Thi , Thu Nguyen Trang Thi , Nguyen Hoang Van , Cui Xujian , Garg Akhil , Le Phung My Loan , Tran Man Van
Published: March 2021

This research aims to evaluate the influence of different 3D metals (Fe, Co, and Ni) substituted to Mn on the electrochemical performance of P2-NaxMe1/3Mn2/3O2 material, which was synthesized by the coprecipitation process followed by calcination at high temperature. X-ray diffraction (XRD) results revealed that the synthesized Mn-rich materials possessed a P2-type structure with a negligible amount of oxide impurities. The materials possessed their typical cyclic voltammogram and charge-discharge profiles; indeed, a high reversible redox reaction was obtained by NaxCo1/3Mn2/3O2 sample. Both NaxCo1/3Mn2/3O2 and NaxFe1/3Mn2/3O2 provided a high specific capacity of above 140 mAh·g−1; however, the former showed better cycling performance with 83% capacity retention after 50 cycles at C/10 and high rate capability. Meanwhile, the Ni-sub NaxNi1/3Mn2/3O2 exhibited excellent cycling stability but a low specific capacity of 110 mAh·g−1 and inferior rate capability. The diffusion coefficient of Na+ ions into the structure tended to decrease with a depth of discharge; those values were in the range of 10−10–10−9 cm2·s−1 and 10−11–10−10 cm2·s−1 in the solid solution region and biphasic region, respectively.
A Technical Nuance to Avoid Lumbar Five Radiculopathy with Anterior Lumbar Fusion and Posterior Instrumentation
Authors: Neal Matthew T. , Kalani Maziyar A. , Lyons Mark K.
Published: March 2021

The anterior lumbar interbody fusion (ALIF) is a well-established procedure used to treat a multitude of spinal pathologies. When performed at the L5-S1 level, the ALIF is often supplemented with posterior pedicle screw and rod fixation. Because the interbody device can restore disk and foraminal height, one benefit of the ALIF procedure is indirect neural decompression in the spinal canal and neural foramina. If the contour of the posterior rod is not matched to the exact position of the tulip heads on the pedicle screws, spondylolisthesis can be introduced, leading to foraminal stenosis and nerve compression. This concern is particularly germane when the posterior instrumentation is placed percutaneously without any direct foraminal decompression. In this report, we describe a patient who had an L4-S1 ALIF, resulting in new L5-S1 retrolisthesis and worsening L5 radiculopathy. Technical nuances and avoidance strategies are discussed.
Hadoop-Based Medical Image Storage and Access Method for Examination Series
Authors: Huang Xin , Yi Wenlong , Wang Jiwei , Xu Zhijian
Published: March 2021

Under the background of electronic medical data, doctors use electronic images to replace the traditional film for diagnosis, and patients can view examination images at any time through various electronic means. The storage and frequent reading of massive data bring new challenges. Given the characteristics of the size and quantity of image files generated by different examination types, different merging strategies are proposed to improve the storage performance of the files; according to the characteristics of medical data with examination as the basic unit, a two-level model combined with medical imaging information is proposed. The indexing mechanism solves the problem that SEQ files cannot be read randomly without an index; given the time characteristics of data access, an improved 2Q algorithm is proposed to cache the prefetched files and the read files in different cache queues, which improves the efficiency of file reading. In the experimental comparison, the proposed algorithm surpasses the baseline method in storage and access performance.
Application of Multitask Joint Sparse Representation Algorithm in Chinese Painting Image Classification
Authors: Yang Dongyu , Ye Xinchen , Guo Baolong
Published: March 2021

This paper presents an in‐depth study and analysis of Chinese painting image classification by a multitask joint sparse representation algorithm for texture feature extraction of Chinese painting images and proposes a method to extract texture features directly for the original images. It simplifies the process of image grayscale conversion and preserves the information contained in the original Chinese painting images to the greatest extent. The algorithm uses the ideas of multicolor domain analysis and multiscale analysis, combined with the traditional grayscale coeval matrix to extract texture features. Experiments show that the multiscale grayscale cooccurrence matrix algorithm outperforms the traditional grayscale cooccurrence matrix algorithm and the color grayscale cooccurrence matrix algorithm. The discriminative ability of multiple features for target recognition is integrated by multitask learning, thus improving the robustness and generalization ability of the algorithm; meanwhile, the recognition accuracy is improved by using a two‐level multitask learning mode to exclude the interference of a large number of irrelevant dictionary atoms. The experimental results show that the algorithm has higher recognition accuracy and better robustness than the existing sparse representation SAR target recognition algorithm. Configuration recognition experiments are conducted on different configurations of target data, and the experimental results show that the algorithm achieves better configuration recognition accuracy than existing algorithms.
An Optimality‐Theoretic Analysis of the Acquisition of English Sentence Stress Based on Acoustic Data
Authors: Ji Wen , Liu Yun
Published: March 2021

The present study adopts both empirical and theoretical methods for the analysis of the acquisition of English sentence stress based on Optimality Theory, aiming to overcome mispronunciation of English sentence stress. Optimality Theory has a dramatic impact on most areas in linguistics besides phonology. The acoustic software Praat is chosen to collect and label data as the basis of the empirical method. Then, through analyzing the four major principles of distribution of sentence stress (content words stressed principle, rightmost words stressed principle, leftmost words stressed principle, and new information priority principle) and based on the analysis of Optimality Theory, the software Praat, and SPSS, the researcher can present the following findings: firstly, the constraint hierarchical ranking of nonnative speakers is DEP‐IO >> NEW‐IP >> ALIGN‐IP‐LEFT >> ALIGN‐IP‐RIGHT. Secondly, the native speakers also undergo the demotion of constraint hierarchical ranking: NEW‐IP >> DEP‐IO >> ALIGN‐IP‐RIGHT >> ALIGN‐IP‐LEFT. Thirdly, the constraint in each demotion of constraint hierarchical ranking during different stages is as follows: NEW‐IP constraint moves from the undominated position to the dominated position in the hierarchy; ALIGN‐IP‐RIGHT and ALIGN‐IP‐LEFT constraints move from the dominated position to the lower position in the hierarchy. Through the specific analysis, the researcher draws a conclusion that the varied reasons affect the nonnative speakers to master the distribution of sentence stress due to their incorrect position in the demotion of constraint hierarchical ranking.
[Retracted] Prediction of Fish Migration Caused by Ocean Warming Based on SARIMA Model
Authors: Xu Feng , Du Yu-Ang , Chen Hong , Zhu Jia-Ming
Published: March 2021

Herring and mackerel are two of the most important pillars of Scottish fisheries. In recent years, global warming has caused a gradual rise in ocean temperatures. In order to survive and reproduce, herring and mackerel populations will migrate. This will have a huge impact on Scotland’s fisheries. Therefore, we need to predict the relocation of fish stocks in advance, make timely adjustments to the fishing range, and minimize the loss of the fishing industry. In this article, we subdivide the research target sea area into 39 regions, establish the optimal SARIMA model for each region based on the collected seawater temperature time series data, and take region 13 and region 15 as examples to fit the ARIMA (3, 3, 1) (1, 2, 1) and ARIMA (2, 3, 1) (0, 2, 1) models with a period of 12. The results show that the SARIMA model fits well in all regions and predicts the temperature changes in the studied sea area from 2021 to 2050. Finally, according to the predicted sea temperature in different periods, the migration position of the fish school is predicted.
An Innovative Elastoplastic Analysis for Soft Surrounding Rock considering Supporting Opportunity Based on Drucker‐Prager Strength Criterion
Authors: Wang Rui , Liu Xu-dong , Bai Jian-biao , Yan Shuai , Xu Jun
Published: March 2021

In order to study the mechanism of excavation and supporting process of equivalent circular roadway, the model of soft roadway was established firstly. The elastoplastic solutions in excavation process were deduced based on Drucker‐Prager strength criterion. Then, the elastoplastic solution under supporting condition was obtained based on homogenization method under the condition of rockbolts and liner supporting. Lastly, an example was analyzed to study the effect of different factors such as “space effect,” supporting opportunity, stresses, surrounding displacement, and the radius of plastic zone. Based on theoretical research case, the change rules of considering the “space effect” and the supporting opportunity when calculating the subarea of the roadway were discussed, the control of interval distance of rockbolts on the displacement of surrounding rock mainly reflecting in the plastic residual zone and the “space effect” in excavation, and the supporting time to control the displacement of surrounding rock not being ignored are revealed. The results can provide an important theoretical basis for the stability evaluation and quantitative support design of roadway surrounding rock. Therefore, the “space effect” and the supporting time to control the displacement and stresses of surrounding rock can not being ignored in underground engineering.
Isolated Handwritten Pashto Character Recognition Using a K‐NN Classification Tool based on Zoning and HOG Feature Extraction Techniques
Authors: Huang Juanjuan , Haq Ihtisham Ul , Dai Chaolan , Khan Sulaiman , Nazir Shah , Imtiaz Muhammad
Published: March 2021

Handwritten text recognition is considered as the most challenging task for the research community due to slight change in different characters’ shape in handwritten documents. The unavailability of a standard dataset makes it vaguer in nature for the researchers to work on. To address these problems, this paper presents an optical character recognition system for the recognition of offline Pashto characters. The problem of the unavailability of a standard handwritten Pashto characters database is addressed by developing a medium‐sized database of offline Pashto characters. This database consists of 11352 character images (258 samples for each 44 characters in a Pashto script). Enriched feature extraction techniques of histogram of oriented gradients and zoning‐based density features are used for feature extraction of carved Pashto characters. K‐nearest neighbors is considered as a classification tool for the proposed algorithm based on the proposed feature sets. A resultant accuracy of 80.34% is calculated for the histogram of oriented gradients, while for zoning‐based density features, 76.42% is achieved using 10‐fold cross validation.
Thermal Analysis and Structural Optimization of High‐Efficiency Fuel Submersible Hot Water Machine
Authors: Zhu Zhaozhe , Wang Youmin , Zhang Yingshuai
Published: March 2021

Based on the oil quality of diesel oil, the thermal efficiency and fuel consumption of the fuel‐burning submersible hot water machine were calculated. The structure of the fuel‐burning submersible hot water machine was designed. The heat transfer calculation of the flame tube and convection surface of the high‐efficiency fuel submersible hot water machine was carried out, and the overall heat balance of the system was checked. ANSYS was used to analyze and study the mechanical and thermodynamic properties of the fuel‐based submersible hot water machine, and the simulation results were compared with the theoretical calculation results. The thermal field of the flame tube and the threaded tube was simulated, and the influence of the temperature field on the flame tube was analyzed. The changes in the total deformation and strength of the flame tube under the thermal structure coupling were studied. The thermal efficiency of oil‐fired submersible hot water machine was studied, and the relevant factors affecting the thermal efficiency of oil‐fired submersible hot water machine were put forward. The main factors affecting thermal efficiency were analyzed and mathematically modeled. The air supply model and the convective heat transfer model of the threaded tube were established. The main parameters that affected the thermal efficiency of the threaded tube were optimized. In the end, the design scheme of a high‐efficiency fuel‐type submersible hot water machine was obtained.
Degraded Image Enhancement Using Dual-Domain-Adaptive Wavelet and Improved Fuzzy Transform
Authors: Fan Weiqiang , Huo Yuehua , Li Xiaoyu
Published: March 2021

A novel enhancement algorithm for degraded image using dual-domain-adaptive wavelet and improved fuzzy transform is proposed, aiming at the problem of surveillance videos degradation caused by the complex lighting conditions underground coal mine. Firstly, the dual-domain filtering (DDF) is used to decompose the image into base image and detail image, and the contrast limited adaptive histogram enhancement (CLAHE) is adopted to adjust the overall brightness and contrast of the base image. Then, the discrete wavelet transform (DWT) is utilized to obtain the low frequency sub-band (LFS) and high frequency sub-band (HFS). Next, the wavelet shrinkage threshold is applied to calculate the wavelet threshold corresponding to the HFS at different scales. Meanwhile, a new Garrate threshold function that introduces adjustment factor and enhancement coefficient is designed to adaptively de-noise and enhance the HFS coefficients, and the Gamma function is employed to correct the LFS coefficients. Finally, the PAL fuzzy enhancement operator is improved and used to perform contrast enhancement and highlight area suppression on the reconstructed image to obtain an enhanced image. Experimental results show that the proposed algorithm can not only significantly improve the overall brightness and contrast of the degraded image but also suppresses the noise of dust and spray and enhances the image details. Compared with the similar algorithms of STFE, GTFE, CLAHE, SSR, MSR, DGR, and MSWT algorithms, the indicator values of comprehensive performance of the proposed algorithm are increased by 205%, 195%, 200%, 185%, 185%, 85%, 140%, and 215%, respectively. Moreover, compared with the other seven algorithms, the proposed algorithm has strong robustness and is more suitable for image enhancement in different mine environments.
Occurrence of Citropsis articulata in Tropical Forests in Uganda: Implication for Ex Situ Conservation
Authors: Wangalwa Rapheal , Olet Eunice Apio , Kagoro-Rugunda Grace , Tolo Casim Umba , Ogwang Patrick E. , Barasa Bernard
Published: March 2021

Citropsis articulata is a medicinal plant that is increasingly threatened by unsustainable methods of harvesting and habitat degradation. Owing to the fact that this plant species is highly utilized for herbal medicine and is currently restricted to a few forest reserves in Uganda, this has significant implications for ex situ conservation. Therefore, the aim of this study was to assess how physiographical factors influence the occurrence and distribution of C. articulata in the three forest reserves in Uganda, namely, Budongo, Mabira, and Kibale National Park. The study was carried out in 15 compartmental sites in each of the three forests. In each compartmental site, 4 plots of 60 m × 60 m were systematically established, and within each plot, 4 subplots each of size 20 m × 20 m were randomly setup. A total of 240 subplots were assessed for occurrence of Citropsis articulata in each forest. The results indicated a significant (p<0.05) variation in the density of C. articulata with the highest recorded in Kibale National Park. Citropsis articulata generally occurred at moderate altitudinal landscapes (overall elevation = 1200.0 ± 20.73 m) with soils that are moderately acidic (overall pH = 5.7 ± 0.10), low in salinity (overall salinity = 84.0 ± 3.84 mg/l), and moderate levels of macro- and micronutrients. Citropsis articulata was generally associated with plant communities dominated by canopy tree species of genera such as Chryosphyllum, Celtis, Markhamia, Cynometra, Lasiodiscus, Trilepisium, Funtumia, and Diospyros, thus suggesting that C. articulata is a shade-tolerant species. Establishing the ecological requirements of this plant species among other things informs the potential for ex situ production of this plant. This will not only provide alternative sources of plant harvest but also go a long way in relieving the current harvest pressures exerted on the conserved wild populations of this plant species.
Micro and Macro Structural Investigations on Welded Joints of Composite Truss Steel Concrete Beams
Authors: Caprili Silvia , Salvatore Walter , Valentini Renzo
Published: March 2021

The results of an experimental test campaign including micro and macro investigations on welded joints typically used in Composite Truss Steel‐Concrete beams are presented. The research was carried out with the aim of assessing the relevance of welding effects on the mechanical performance of different typologies of steel grades that can be used to realize the internal truss steel system, connected to the bottom steel plate used with the double structural and formwork function. Two different steel typologies were adopted for the steel truss: the “traditional” structural micro‐alloyed steel, normally used for composite steel‐concrete elements, and the typical reinforcing steel with TempCore® structure, achieved through the application of two‐phase thermomechanical treatment of quenching and tempering. The interest in the possibility of adopting reinforcing steel for the internal truss arises from its potential economic benefit, finding its justification in the intermediate condition in which this structural typology lies, between composite steel‐concrete and ordinary reinforced concrete buildings. Welding has a strong impact on such reinforcing steel material, resulting in relevant drops of ductility and brittle failure usually taking place in correspondence of the heat‐affected zone. So, it is advisable to refrain from using such steel grade, especially in constructions in seismic‐prone areas, where ductility is a major influencing and design factor.
Noise Attenuation of Seismic Data via Deep Multiscale Fusion Network
Authors: Sang Yu , Sun Jinguang , Gao Dacheng , Wu Hao
Published: March 2021

Convolutional neural network‐ (CNN‐) based deep learning (DL) architectures have achieved great success in many fields such as remote sensing, medical image processing, and computer vision. Recently, CNN‐based models have also been attempted to solve geophysical problems. This paper presents a noise attenuation method of seismic data via a novel deep learning (DL) architecture, namely, deep multiscale fusion network (MSFN). Firstly, we integrate multiscale fusion (MSF) block to adaptively exploit local signal features at different scales from seismic data. And then, a series of stacked MSF blocks are formed into MSFN, which can restore the noisy seismic data effectively and preserve more useful signal information. Furthermore, a comparative study of our method and other leading edge ones is conducted by using synthetic seismic records and the SEG/EAGE salt and overthrust models. The results qualitatively and quantitatively show the capability of our method of achieving higher peak signal‐to‐noise ratios (PSNRs) while preserving much more useful information, comparing with other methods. Finally, our method is utilized in the real seismic data processing, obtaining satisfactory results.
Recognition of the Impulse of Love at First Sight Based on Electrocardiograph Signal
Authors: Zhang Jin , Yuan Guangjie , Lu Huan , Liu Guangyuan
Published: March 2021

The impulse of love at first sight (ILFS) is a well known but rarely studied phenomenon. Despite the privacy of these emotions, knowing how attractive one finds a partner may be beneficial for building a future relationship in an open society, where partners are accepting each other. Therefore, this study adopted the electrocardiograph (ECG) signal collection method, which has been widely used in wearable devices, to collect signals and conduct corresponding recognition analysis. First, we used photos to induce ILFS and obtained ECG signals from 46 healthy students (24 women and 22 men) in a laboratory. Second, we extracted the time‐ and frequency‐domain features of the ECG signals and performed a nonlinear analysis. We subsequently used a feature selection algorithm and a set of classifiers to classify the features. Combined with the sequence floating forward selection and random forest algorithms, the identification accuracy of the ILFS was 69.07%. The sensitivity, specificity, F1, and area under the curve of the other parameters were all greater than 0.6. The classification of ECG signals according to their characteristics demonstrated that the signals could be recognized. Through the information provided by the ECG signals, it can be determined whether the participant possesses the desire to fall in love, helping to determine the right partner in the fastest time; this is conducive to establishing a romantic relationship.
Insulin Resistance Indexes as Biomarkers of Lifetime Cardiovascular Risk among Adults from Peru
Authors: Rojas-Humpire Ricardo , Olarte-Durand Mely , Medina-Ramirez Sebastian , Gutierrez-Ajalcriña Rosmery , Canaza Josue F. , Huancahuire-Vega Salomon
Published: March 2021

Background. Cardiovascular disease (CVD) is the most prevalent cause of death from disease and disability in the world. Reliable markers are needed to assess and reduce cardiovascular risk. This study aimed to determine if insulin resistance indexes, triglycerides to HDL-cholesterol ratio (TG/HDL-C), and triglyceride glucose index (TyG) are biomarkers for lifetime cardiovascular risk (CVR). Methods. This analytical cross-sectional study was performed on health personnel from Huaycan Hospital in Peru. The QRISK model was used to measure lifetime CVR. The association and diagnostic accuracy for TyG calculated as Ln (TG (mg/dL) × glucose (mg/dL)/2) and TG/HDL-C ratio were determined using Poisson regression models and ROC curves with Youden index. Results. In total, 291 adults (207 women and 84 men) were analyzed. In the adjusted Poisson models, each unit of TG/HDL-C increased 1.22-fold and 1.16-fold the probability of high lifetime CVR in men and women, respectively. However, each unit of TyG increased 1.98-fold in men and 3.25-fold in women the probability of high lifetime CVR. The optimal cutoff values of TG/HDL-C were 2.64 (AUC: 0.77), 3.90 (AUC: 0.80), and 2.64 (AUC: 0.74) for the overall population, men, and women, respectively. Likewise, the optimal cutoff values of TyG were 9.04 (AUC: 0.80), 8.95 (AUC: 0.79), and 9.04 (AUC: 0.80) for the overall population, men, and women, respectively. Conclusion. TG/HDL-C and TyG presented a significant association with lifetime CVR. However, TyG presented a stronger association than TG/HDL-C. Both TG/HDL-C and TyG are shown to be reliable markers for CVR in adults.
Chronic Inhibition of FAAH Reduces Depressive-Like Behavior and Improves Dentate Gyrus Proliferation after Chronic Unpredictable Stress Exposure
Authors: Tejeda-Martínez A. R. , Viveros-Paredes J. M. , Hidalgo-Franco G. V. , Pardo-González E. , Chaparro-Huerta V. , González-Castañeda R. E. , Flores-Soto M. E.
Published: March 2021

Symptoms of depressive disorders such as anhedonia and despair can be a product of an aberrant adaptation to stress conditions. Chronic unpredictable stress model (CUS) can generate an increase in the activity of the hypothalamic-pituitary-adrenal axis (HPA) and induce a reduction of neurotrophin signaling and the proliferation of neural progenitors in the adult dentate gyrus, together with increased oxidative stress. Levels of the endocannabinoid anandamide (AEA) seem to affect these depression-by-stress-related features and could be modulated by fatty acid amide hydrolase (FAAH). We aimed to evaluate the effects of FAAH inhibitor, URB597, on depressive-like behavior and neural proliferation of mice subjected to a model of CUS. URB597 was administered intraperitoneally at a dose of 0.2 mg/kg for 14 days after CUS. Depressive-like behaviors, anhedonia, and despair were evaluated in the splash and forced swimming tests, respectively. Alterations at the HPA axis level were analyzed using the relative weight of adrenal glands and serum corticosterone levels. Oxidative stress and brain-derived neurotrophic factor (BDNF) were also evaluated. Fluorescence immunohistochemistry tests were performed for the immunoreactivity of BrdU and Sox2 colabeling for comparison of neural precursors. The administration of URB597 was able to reverse the depressive-like behavior generated in mice after the model. Likewise, other physiological responses associated with CUS were reduced in the treated group, among them, increase in the relative weight of the adrenal glands, increased oxidative stress, and decreased BDNF and number of neural precursors. Most of these auspicious responses to enzyme inhibitor administration were blocked by employing a cannabinoid receptor antagonist. In conclusion, the chronic inhibition of FAAH generated an antidepressant effect, promoting neural progenitor proliferation and BDNF expression, while reducing adrenal gland weight and oxidative stress in mice under the CUS model.
Machine Learning-Based Stealing Attack of the Temperature Monitoring System for the Energy Internet of Things
Authors: Li Qiong , Zhang Liqiang , Zhou Rui , Xia Yaowen , Gao Wenfeng , Tai Yonghang
Published: March 2021

With the development of the Energy Internet of Things (EIoT), it is of great practical significance to study the security strategy and intelligent control system for solar thermal utilization system to optimize the operation efficiency and carry out intelligent dynamic adjustment. For buildings integrated with solar water heating systems, computational fluid dynamics simulation was used in analyzing the process of solar energy output. A method based on machine learning is proposed to predict energy conversion. Besides, the simulation and analysis are carried out in combination with the possible safety problems such as the vibration of the control system. This paper proposed a novel platform of EIoT for machine learning-based cybersecurity study and implemented the platform for the temperature monitoring system. After the evaluation of the machine learning-based cybersecurity study, the EIoT system demonstrated a high performance with the Extreme Gradient Boosting (XGBoost) training algorithm.
A Time Refinement Framework Based on iUML-B State Machine
Authors: Peng Han , Zhang Xiaoli , Cao Guozhen , Liu Zhouzhou , Jing Yuejuan , Rao Lei
Published: March 2021

Event-B is a formal modeling language that is very suitable for software engineering, but it lacks the ability of modeling time. Researchers have proposed some methods for modeling time constraints in Event-B. The limitations with existing methods are that, first of all, the existing research work lacks a systematic time refinement framework based on Event-B; secondly, the existing methods only model time in the Event-B framework and cannot be smoothly converted to automata-based models such as timed automata that facilitate the verification of time properties. These limitations make it more difficult to model and verify real-time systems with Event-B because it is very time-consuming to prove time properties in the Event-B framework. In this paper, we firstly proposed a systematic time refinement framework to express and refine time constraints in Event-B. Secondly, we also proposed various vertical refinement patterns and horizontal extension patterns to guide modelers to refine the Event-B real-time model step by step. Finally, we use a real-time system case to demonstrate the practicality of our method. The experimental results show that the proposed method can make the real-time system modeling in Event-B more convenient and the models are easier to convert to the timed automata model, thereby facilitating the verification of various time properties.
Network Security Technology of Intelligent Information Terminal Based on Mobile Internet of Things
Authors: Sun Ning , Li Tao , Song Gongfei , Xia Haoran
Published: March 2021

In the process of implementing the Internet of Things, the object itself has identity information and identification equipment and encounters difficulties in communication security during the process of entering the network communication. Just like the Internet and wireless sensor networks, there are security issues in information transmission. Therefore, it is of great significance to study the mobile Internet of Things network security technology depression to protect the communication information in the mobile Internet of Things. This paper mainly studies the network security technology of intelligent information terminal based on mobile Internet of Things. This article will analyze and compare the mainstream encryption algorithms of the current mobile Internet and choose a safer and more secure HASH algorithm. We study the flow of key management, key generation, key distribution, verification key distribution, key update, key storage, key backup, and key validity time setting for mobile Internet of Things, using an existing identity cryptosystem. Based on encryption, the design technology of key management and authentication in this paper is improved. Compared with other methods, the storage consumption of this method on GWN is relatively medium. In the initial stage, the storage is 32 bytes, then in registration stage 1, it reaches 84 bytes, in registration stage 2, it is 82 bytes, and then, in the login authentication phase, the number of bytes rose and reached 356 bytes in authentication phase 3. Experimental results show that this protocol has certain advantages in ensuring safety performance.
Investigation of Counterflow Microchannel Heat Exchanger with Hybrid Nanoparticles and PCM Suspension as a Coolant
Authors: Hasan Mushtaq I. , Khafeef Mohammad J. , Mohammadi Omid , Bhattacharyya Suvanjan , Issakhov Alibek
Published: March 2021

The effect of the hybrid suspension on the intrinsic characteristics of microencapsulated phase change material (MEPCM) slurry used as a coolant in counterflow microchannel heat exchanger (CFMCHE) with different velocities is investigated numerically. The working fluid used in this paper is a hybrid suspension consisting of nanoparticles and MEPCM particles, in which the particles are suspended in pure water as a base fluid. Two types of hybrid suspension are used (Al2O3 + MEPCM and Cu + MEPCM), and the hydrodynamic and thermal characteristics of these suspensions flowing in a CFMCHE are numerically investigated. The results indicated that using hybrid suspension with high flow velocities improves the performance of the microchannel heat exchanger while resulting in a noticeable increase in pressure drop. Thereupon, it causes a decrease in the performance index. Moreover, it was found that the increment of the nanoparticles’ concentration can rise the low thermal conductivity of the MEPCM slurry, but it also leads to a noticeable increase in pressure drop. Furthermore, it was found that as the thermal conductivity of Cu is higher than that for Al2O3, the enhancement in heat transfer is higher in case of adding Cu particles compared with Al2O3 particles. Therefore, the effectiveness of these materials depends strongly on the application at which CFMCHE is employed.