bluuebunny/crossref_metadata_2025 huggingface dataset:
The saturation class for linear combinations of Szász–Mirakjan operators
Authors: Xie Linsen , Wang Shuli , Zhao Kaifei
Published: May 2020

This paper investigates the regularity of a class of differential operators generated by Szász–Mirakjan operators. With the aid of the regularity, the relation between the uniform saturated approximation order of linear combinations of Szász–Mirakjan operators and the smoothness of the approximated functions is studied. The saturation class for linear combinations of Szász–Mirakjan operators is characterized.
Evaluation of Seismic Fragility Analysis of the Mega Sub-Controlled Structural System (MSCSS)
Authors: Abdulhadi Mustapha , Xun’an Zhang , Fan Buqiao , Moman Muhammad
Published: May 2020

The improved mega sub-controlled structure system (MSCSS) significantly reduced the building responses and improved the control effectiveness as compared to conventional mega substructure (MSS). However, since the MSCSS is designed to resist future earthquakes, the seismic risk assessment of the structure remains a significant concern. In this study, the seismic risk analysis of MSCSS is performed to probabilistically compare the building performance and its resistance to future earthquake damage at certain categories of limit states (LSs), which include category one (slight damage, moderate damage, and collapse damage LS) and category two (damage control and collapse prevention). The comparison is realized with the result of the traditional MSS. The probability of exceedance of the above damage LS for a particular ground motion (GM) intensity (i.e. Sa (T1,5%)) is evaluated to assess and compare the vulnerability of these buildings. The evaluation is done through developing fragility curves and relationships for MSCSS and MSS. The result showed that the improved MSCSS has strong seismic resistance ability and provides a better response from a nonlinear analysis result. Furthermore, the fragility curve of moderate and collapse damage LSs indicated that MSCSS requires higher GM intensity to reach a moderate and collapse damage LS than MSS. That means MSCSS is the most stable with a significant difference as compared to its counterpart. This is also true for the second category of LS, that is, damage control and collapse prevention. While at the slight damage LS, both the MSCSS and MSS require approximately the same GM intensity to reach a slight damage LS, as the difference is not significant.
Utility Mining across Multi-Sequences with Individualized Thresholds
Authors: Gan Wensheng , Lin Jerry Chun-Wei , Zhang Jiexiong , Yu Philip S.
Published: May 2020

Utility-oriented pattern mining is an emerging topic, since it can reveal high-utility patterns from different types of data, which provides more information than the traditional frequency/confidence-based pattern mining models. The utilities of various items/objects are not exactly equal in realistic situations; each item/object has its own utility or importance. In general, the user considers a uniform minimum utility (minutil) threshold to identify the set of high-utility sequential patterns (HUSPs). This is unable to find the interesting patterns while theminutilis set extremely high or low. We first design a new utility mining framework namely USPT for mining high-Utility Sequential Patterns across multi-sequences with individualized Thresholds. Each item in the designed framework has its own specified minimum utility threshold. Based on the lexicographic-sequential tree and the utility-array structure, the USPT framework is presented to efficiently discover the HUSPs. With the upper-bounds on utility, several pruning strategies are developed to prune the unpromising candidates early in the search space. Several experiments are conducted on both real-life and synthetic datasets to show the performance of the designed USPT algorithm, and the results show that USPT could achieve good effectiveness and efficiency for mining HUSPs with individualized minimum utility thresholds.
Mental Models of Mere Mortals with Explanations of Reinforcement Learning
Authors: Anderson Andrew , Dodge Jonathan , Sadarangani Amrita , Juozapaitis Zoe , Newman Evan , Irvine Jed , Chattopadhyay Souti , Olson Matthew , Fern Alan , Burnett Margaret
Published: May 2020

How should reinforcement learning (RL) agents explain themselves to humans not trained in AI? To gain insights into this question, we conducted a 124-participant, four-treatment experiment to compare participants’ mental models of an RL agent in the context of a simple Real-Time Strategy (RTS) game. The four treatments isolated two types of explanations vs. neither vs. both together. The two types of explanations were as follows: (1) saliency maps (an “Input Intelligibility Type” that explains the AI’s focus of attention) and (2) reward-decomposition bars (an “Output Intelligibility Type” that explains the AI’s predictions of future types of rewards). Our results show that a combined explanation that included saliency and reward bars was needed to achieve a statistically significant difference in participants’ mental model scores over the no-explanation treatment. However, this combined explanation was far from a panacea: It exacted disproportionately high cognitive loads from the participants who received the combined explanation. Further, in some situations, participants who saw both explanations predicted the agent’s next action
worse
than all other treatments’ participants.
Earthquake Simulation on Ancient Masonry Buildings
Authors: Fita Josep Lluis , Besuievsky Gonzalo , Patow Gustavo
Published: May 2020

Research on seismic simulations has focused mainly on methodologies specially tailored to civil engineering. However, we have detected a lack in the area of interactive cultural heritage applications, where speed and plausibility are the main requirements to satisfy. We designed a tool that allows setting up and recreating earthquakes in a simple way. We coupled our earthquake simulator with a structural simulator of physics, specifically tailored to masonry buildings, achieving a high degree of accuracy in the simulations. To validate our model, we performed a series of tests over a set of ancient masonry structures such as walls and churches. We show the feasibility of including earthquake simulations and structural vulnerability, a building property that limits the damage of this under seismic movements, into historical studies for helping professionals understand those events of the past where an earthquake took place.
Accurate Overlapping Method of Ultra-Long Interval Time-Lapse Images for World Heritage Site Investigation
Authors: Shishido Hidehiko , Kawasaki Emi , Kawamura Youhei , Matsui Toshiya , Kitahara Itaru
Published: May 2020

In this article, a method is proposed to accurately overlap multiple high-quality images with different shooting positions and intervals by combining corresponding point information between images and 3D shape information. In the proposed method, the correct feature matching of images obtained by rendering the 3D model of the subject is used. In this research, the subjects were the pillars of the Angkor Thom Bayon Temple and the epilithic microorganisms adhering to and eroding their surfaces. Synthetic transformation of a homography utilizing the correct matches is employed to overlap the target images. When overlapping different background images using the conventional method, estimation of the homography matrix becomes difficult owing to incorrect matches; thus, high-quality overlapping images cannot be obtained. The objective of this research was to realize the overlapping image process even under conditions that cause incorrect feature matches, such as differences in background and illumination. In this study, the damaged parts of the pillar surfaces were visualized using the proposed method. Based on the results of an experiment comparing the proposed method with an existing state-of-the-art method, the effectiveness and higher accuracy of the proposed method were verified. The findings of this research contribute to Angkor Thom Bayon Temple preservation, including a preservation project that the present authors are organizing for this culturally and historically valuable United Nations Educational, Scientific and Cultural Organization World Heritage site.
Discovery of Spatio-Temporal Patterns in Multivariate Spatial Time Series
Authors: Wu Gene P. K. , Chan Keith C. C.
Published: May 2020

With the advancement of the computing technology and its wide range of applications, collecting large sets of multivariate time series in multiple geographical locations introduces a problem of identifying interesting spatio-temporal patterns. We consider a new spatial structure of the data in the pattern discovery process due to the dependent nature of the data. This article presents an information-theoretic approach to detect the temporal patterns from the multivariate time series in multiple locations. Based on their occurrences of discovered temporal patterns, we propose a method to identify interesting spatio-temporal patterns by a statistical significance test. Furthermore, the identified spatio-temporal patterns can be used for clustering and classification. For evaluating the performance, a simulated dataset is tested to validate the quality of the identified patterns and compare with other approaches. The result indicates the approach can effectively identify useful patterns to characterize the dataset for further analysis in achieving good clustering quality. Furthermore, experiments on real-world datasets and case studies have been conducted to illustrate the applicability and the practicability of the proposed approach.
A Data-driven Approach for Architectural History Knowledge. Capturing Buildings’ Construction Events for Historical Research Collaboration
Authors: Ferreira-Lopes Prof. Patricia
Published: May 2020

The increase of multidisciplinary research in the field of architectural history has led to the need to set up new experiences and solutions for the handling and integration of the information extracted from historical documents. These solutions seek to support diverse users of the research community with the aim of solving challenges directly related with the digitalisation, structuring, standardisation, and management of historical information. These challenges include, for example, the creation of a digital support that enables a collaborative growth and management of information, the normalisation of terms and vocabularies to make its analysis efficient, the elaborating of a conceptual model, and the development of a metadata support that allows its more expanded dissemination and reuse.

This article describes a case study project in which the documents of archives, of research, and of projects previously carried out by the Late Gothic Network (Red Tardogótica) are the raw material for the proposal of an event-oriented historical database (e-database). This e-database means to record and systematise the information about the artistic transfers related with the architectural production in the transition of the Modern Age, a period also known as the Late Gothic. The e-database's design has considered the possibility of its use for the analysis of social networks (abstract-relational model, a Graph model) and the spatiotemporal analysis of the events (geo-temporal model, GIS). The main section of this article describes the architecture of the database, with a view to addressing the questions of the relations between the datasets and the matter of implementing thethesauriandcontrolled vocabulariesthat must be respected for the standardisation, recording, and later analysis of the data. Next, we contribute quantitative and qualitative analyses to evaluate the database's important gaps of information. This proposal initially covers the geographical framework of the western Andalusian territory, but it can be expanded to other areas and adapted to other case studies. Finally, the article summarises the learning achieved in this first phase of the case study project and describes the perspectives to broaden its use in the community of architectural history researchers.
Improving Accessibility to Intangible Cultural Heritage Preservation Using Virtual Reality
Authors: Selmanović Elmedin , Rizvic Selma , Harvey Carlo , Boskovic Dusanka , Hulusic Vedad , Chahin Malek , Sljivo Sanda
Published: May 2020

Presentations of virtual cultural heritage artifacts are often communicated via the medium of interactive digital storytelling. The synergy of a storied narrative embedded within a 3D virtual reconstruction context has high consumer appeal and edutainment value. We investigate if 360° videos presented through virtual reality further contribute to user immersion for the application of preserving intangible cultural heritage. A case study then analyzes whether conventional desktop media is significantly different from virtual reality as a medium for immersion in intangible heritage contexts. The case study describes bridge diving at Stari Most, the old bridge in Mostar Bosnia. This application aims to present and preserve the bridge diving tradition at this site. The project describes the site and history along with cultural connections, and a series of quiz questions are presented after viewing all of the materials. Successful completion of the quiz allows a user to participate in a virtual bridge dive. The subjective evaluation provided evidence to suggest that our method is successful in preserving intangible heritage and communicating ideas in key areas of concern for this heritage that can be used to develop a preservation framework in the future. It was also possible to conclude that experience within the virtual reality framework did not affect effort expectancy for the web application, but the same experience significantly influenced the performance expectancy construct.
SILK+ Preventing Latency Spikes in Log-Structured Merge Key-Value Stores Running Heterogeneous Workloads
Authors: Balmau Oana , Dinu Florin , Zwaenepoel Willy , Gupta Karan , Chandhiramoorthi Ravishankar , Didona Diego
Published: May 2020

Log-Structured Merge Key-Value stores (LSM KVs) are designed to offer good write performance, by capturing client writes in memory, and only later flushing them to storage. Writes are later compacted into a tree-like data structure on disk to improve read performance and to reduce storage space use. It has been widely documented that compactions severely hamper throughput. Various optimizations have successfully dealt with this problem. These techniques include, among others, rate-limiting flushes and compactions, selecting among compactions for maximum effect, and limiting compactions to the highest level by so-called fragmented LSMs.

In this article, we focus on latencies rather than throughput. We first document the fact that LSM KVs exhibit high tail latencies. The techniques that have been proposed for optimizing throughput do not address this issue, and, in fact, in some cases, exacerbate it. The root cause of these high tail latencies is interference between client writes, flushes, and compactions. Another major cause for tail latency is the heterogeneous nature of the workloads in terms of operation mix and item sizes whereby a few more computationally heavy requests slow down the vast majority of smaller requests.

We introduce the notion of an Input/Output (I/O) bandwidth scheduler for an LSM-based KV store to reduce tail latency caused by interference of flushing and compactions and by workload heterogeneity. We explore three techniques as part of this I/O scheduler: (1) opportunistically allocating more bandwidth to internal operations during periods of low load, (2) prioritizing flushes and compactions at the lower levels of the tree, and (3) separating client requests by size and by data access path. SILK+ is a new open-source LSM KV that incorporates this notion of an I/O scheduler.
Asterisk
Authors: Nashaat Mona , Ghosh Aindrila , Miller James , Quader Shaikh
Published: May 2020

Labeling datasets is one of the most expensive bottlenecks in data preprocessing tasks in machine learning. Therefore, organizations, in many domains, are applying weak supervision to produce noisy labels. However, since weak supervision relies on cheaper sources, the quality of the generated labels is problematic. Therefore, in this article, we present
Asterisk
, an end-to-end framework to generate high-quality, large-scale labeled datasets. The system, first, automatically generates heuristics to assign initial labels. Then, the framework applies a novel data-driven active learning process to enhance the labeling quality. We present an algorithm that learns the selection policy by accommodating the modeled accuracies of the heuristics, along with the outcome of the generative model. Finally, the system employs the output of the active learning process to enhance the quality of the labels. To evaluate the proposed system, we report its performance against four state-of-the-art techniques. In collaboration with our industrial partner, IBM, we test the framework within a wide range of real-world applications. The experiments include 10 datasets of varying sizes with a maximum size of 11 million records. The results illustrate the effectiveness of the framework in producing high-quality labels and achieving high classification accuracy with minimal annotation efforts.
Automatic Detection of Usability Problem Encounters in Think-aloud Sessions
Authors: Fan Mingming , Li Yue , Truong Khai N.
Published: May 2020

Think-aloud protocols are a highly valued usability testing method for identifying usability problems. Despite the value of conducting think-aloud usability test sessions, analyzing think-aloud sessions is often time-consuming and labor-intensive. Consequently, previous research has urged the community to develop techniques to support fast-paced analysis. In this work, we took the first step to design and evaluate machine learning (ML) models to automatically detect usability problem encounters based on users’ verbalization and speech features in think-aloud sessions. Inspired by recent research that shows subtle patterns in users’ verbalizations and speech features tend to occur when they encounter problems, we examined whether these patterns can be utilized to improve the automatic detection of usability problems. We first conducted and recorded think-aloud sessions and then examined the effect of different input features, ML models, test products, and users on usability problem encounters detection. Our work uncovers several technical and user interface design challenges and sets a baseline for automating usability problem detection and integrating such automation into UX practitioners’ workflow.
A Retargetable System-level DBT Hypervisor
Authors: Spink Tom , Wagstaff Harry , Franke Björn
Published: May 2020

System-level Dynamic Binary Translation (DBT) provides the capability to boot an Operating System (OS) and execute programs compiled for an Instruction Set Architecture (ISA) different from that of the host machine. Due to their performance-critical nature, system-level DBT frameworks are typically hand-coded and heavily optimized, both for their guest and host architectures. While this results in good performance of the DBT system, engineering costs for supporting a new architecture or extending an existing architecture are high. In this article, we develop a novel, retargetable DBT hypervisor, which includes guest-specific modules generated from high-level guest machine specifications. Our system simplifies retargeting of the DBT, but it also delivers performance levels in excess of existing manually created DBT solutions. We achieve this by combining offline and online optimizations and exploiting the freedom of a Just-in-time (JIT) compiler operating in a bare-metal environment provided by a Virtual Machine (VM) hypervisor. We evaluate our DBT using both targeted micro-benchmarks as well as standard application benchmarks, and we demonstrate its ability to outperform the de facto standard Q
EMU
DBT system. Our system delivers an average speedup of 2.21× over Q
EMU
across SPEC CPU2006 integer benchmarks running in a full-system Linux OS environment, compiled for the 64-bit ARMv8-A ISA and hosted on an x86-64 platform. For floating-point applications the speedup is even higher, reaching 6.49× on average. We demonstrate that our system-level DBT system significantly reduces the effort required to support a new ISA while delivering outstanding performance.
Model-based Design of Hardware SC Polar Decoders for FPGAs
Authors: Delomier Yann , Gal Bertrand Le , Crenne Jerémie , Jego Christophe
Published: May 2020

Polar codes are a new error correction code family that should be benchmarked and evaluated in comparison to LDPC and turbo-codes. Indeed, recent advances in the 5G digital communication standard recommended the use of polar codes in EMBB control channels. However, in many cases, the implementation of efficient FEC hardware decoders is challenging. Specialised knowledge is required to enable and facilitate testing, rapid design iterations, and fast prototyping. In this article, a model-based design methodology to generate efficient hardware SC polar code decoders is presented. With HLS design process and tools, we demonstrate how FPGA system designers can quickly develop complex hardware systems with good performances. The favourable impact of design space exploration is underlined on achievable performances when a relevant computation model is used. The flexibility of the abstraction layers is evaluated. Hardware decoder generation efficiency is assessed and compared to competing approaches. It is shown that the fine-tuning of computation parallelism, bit length, pruning level, and working frequency help to design high-throughput decoders with moderate hardware complexities. Decoding throughputs higher than 300 Mbps are achieved on an Xilinx Virtex-7 device and on an Altera Stratix IV device.
Scene Grammars, Factor Graphs, and Belief Propagation
Authors: Chua Jeroen , Felzenszwalb Pedro F.
Published: May 2020

We describe a general framework for probabilistic modeling of complex scenes and for inference from ambiguous observations. The approach is motivated by applications in image analysis and is based on the use of priors defined by stochastic grammars. We define a class of grammars that capture relationships between the objects in a scene and provide important contextual cues for statistical inference. The distribution over scenes defined by a probabilistic scene grammar can be represented by a graphical model, and this construction can be used for efficient inference with loopy belief propagation.

We show experimental results with two applications. One application involves the reconstruction of binary contour maps. Another application involves detecting and localizing faces in images. In both applications, the same framework leads to robust inference algorithms that can effectively combine local information to reason about a scene.
Differential Expression and Prognostic Value of Cytoplasmic and Nuclear Cyclin D1 in Prostate Cancer
Authors: Cao Zhi , Chen Xi , Xu Yalong , Guo Fei , Ji Jin , Xu Huan , He Jingyi , Sun Yinghao , Wang Fubo
Published: May 2020

Cyclin D1 (CCND1) has been revealed as a key regulating protein in cell cycle (G1 phase) and plays a critical role in promoting tumor development. The purpose of our study was to investigate the associations between CCND1 and biochemical recurrence of prostate cancer (PCa). We performed immunostaining of CCND1 on a tissue microarray and evaluated the CCND1 expression levels based on the intensity and extent of staining. The clinical data was collected, and the follow‐up data was received by searching our follow‐up database called “PC‐follow”. We revealed that CCND1 expression patterns were different between cytoplasm and nucleus in this study, and the expression of CCND1 in adjacent normal tissues was higher than that in PCa tissues (P < 0.001), while nuclear CCND1 showed the opposite distribution characteristic (P < 0.001). The cytoplasmic CCND1 also showed correlation with several clinical factors, e.g., tumor T stage (P < 0.001), Gleason score (P = 0.028), positive surgical margin (P = 0.037), and capsule invasion (P = 0.04). We also revealed that cytoplasmic CCND1 is a protective prognostic factor in the biochemical recurrence (BCR) free time analysis (P = 0.002). However, the nuclear CCND1 showed no correlation with clinical factors or prognostic value in this study. This study found that cytoplasmic and nuclear CCND1 have significant different expression patterns in PCa tissues, and cytoplasmic CCND1 has a certain prognostic value in the BCR analysis.
L-Fuzzy Semiprime Ideals of a Poset
Authors: Alaba Berhanu Assaye , Engidaw Derso Abeje
Published: May 2020

In this paper, we introduce the concept ofL-fuzzy semiprime ideal in a general poset. Characterizations ofL-fuzzy semiprime ideals in posets as well as characterizations of anL-fuzzy semiprime ideal to beL-fuzzy prime ideal are obtained. Also,L-fuzzy prime ideals in a poset are characterized.
Protein Level and Infantile Diarrhea in a Postweaning Piglet Model
Authors: Gao Jing , Yin Jie , Xu Kang , Han Hui , Liu ZeMin , Wang ChenYu , Li TieJun , Yin YuLong
Published: May 2020

Infantile diarrhea is a serious public health problem around worldwide and results in millions of deaths each year. The levels and sources of dietary protein are potential sources of diarrhea, but the relationship between the pathogenesis causes of infantile diarrhea and protein intake remains poorly understood. Many studies have indicated that the key to understanding the relationship between the protein in the diet and the postweaning diarrhea of piglets is to explore the influences of protein sources and levels on the mammalian digestion system. The current study was designed to control diarrhea control by choosing different protein levels in the diet and aimed at providing efficient regulatory measures for infantile diarrhea by controlling the protein levels in diets using a postweaning piglets model. To avoid influences from other protein sources, casein was used as the only protein source in this study. Fourteen piglets (7.98±0.14 kg, weaned at 28 d) were randomly allotted to two dietary treatments: a control group (Cont, containing 17% casein) and a high protein group (HP, containing 30% casein). The experiment lasted for two weeks and all animals were free to eat and drink water ad libitum. The diarrhea score (1=normal; 3=watery diarrhea) and growth performance were recorded daily. The results showed that the piglets in HP group had persistent diarrhea during the whole study, while no diarrhea was noticed in the control groups. Also, the feed intake and body weights were reduced in the HP groups compared with the other group (P<0.05). The diarrhea-related mRNA abundances were analyzed by real-time PCR; the results showed that HP treatment markedly decreased the expression of aquaporin (AQP, P<0.05) and the tight junction protein (P<0.05), but increased inflammatory cytokines (P<0.01) than those in control group. In addition, the Adenosine 5′-monophosphate (AMP)-activated protein kinase (AMPK) signaling pathway (P<0.01) was inhibited in the HP group. Intestinal microbiota was tested by 16S sequencing, and we found that the HP group had a low diversity compared the other group. In conclusion, despite being highly digestible, a high casein diet induced postweaning diarrhea and reduced the growth performance of the postweaning piglets. Meanwhile, AQP, tight junction protein, and intestinal immune were compromised. Thus, the mechanism of how a highly digestible protein diet induces diarrhea might be associated with the AMPK signaling pathway and intestinal microbiome.
A Coordination Mechanism of Supply Chain with a Retailer and Two Competitive Suppliers
Authors: Liu Zhi-yang , Liu Yong , Li Hui
Published: May 2020

To deal with coordination problem of a supply chain consisting of two competitive suppliers and a dominant retailer, considering these factors such as cooperation effort degrees and competition on the supply chain members, we establish a two-stage model considering cooperation effort degrees and competition of the suppliers from the perspectives of decentralized decision and centralized decision and exploit it to discuss the optional decisions and explore the impact of cooperation effort degrees on the profits of supply chain members. Then, we use a group negotiation model to establish a coordination mechanism. The results reveal that the decision variables and overall profit of the supply chain of suppliers and retailers under centralized decisions are better than those under the decentralized decisions. Besides, the degree of competition and price sensitivity have positive and negative effects on the efforts of suppliers and retailers, respectively. Meanwhile, the degree of cooperation between suppliers and retailers affects the profits of supply chain members and the whole supply chain in different degrees. Finally, the proposed value-added profit distribution mechanism can effectively deal with conflict problem and guarantee supply chain members and supply chain to maximize their profits and adopt the centralized decision.
Abundant Symmetry-Breaking Solutions of the Nonlocal Alice–Bob Benjamin–Ono System
Authors: Shen Wang , Ma Zheng-Yi , Fei Jin-Xi , Zhu Quan-Yong , Chen Jun-Chao
Published: May 2020

The Benjamin–Ono equation is a useful model to describe the long internal gravity waves in deep stratified fluids. In this paper, the nonlocal Alice–Bob Benjamin–Ono system is induced via the parity and time-reversal symmetry reduction. By introducing an extended Bäcklund transformation, the symmetry-breaking soliton, breather, and lump solutions for this system are obtained through the derived Hirota bilinear form. By taking suitable constants in the involved ansatz functions, abundant fascinating symmetry-breaking structures of the related explicit solutions are shown.
Potential Effects of Antioxidant and Serum Cholesterol‐Lowering Effects of Gynura bicolor Water Extracts in Syrian Hamster
Authors: Hsieh Shu-Ling , Tsai Pi-Jen , Liu Ya-Ching , Wu Chih-Chung
Published: May 2020

Gynura bicolor (Roxb. and Willd.) DC (G. bicolor) is a dietary vegetable in the Far East. The aims of the present study were to investigate the antioxidant effects of the G. bicolor water extract (GBWE) and its ability to regulate the blood lipid and lipoprotein profiles. In this study, the pigment composition and antioxidant ability of the GBWE were analyzed. Syrian hamsters were fed a high‐fat diet (HFD) and the GBWE for 12 weeks, and the blood lipid levels, lipoprotein profiles, and cholesterol metabolism‐related enzyme levels were then examined. The results showed that the GBWE exhibited excellent 2,2‐diphenyl‐1‐picrylhydrazyl (DPPH) radical‐scavenging activity and ferrous‐ion‐chelating ability. The hepatic glutathione levels in the hamsters were increased after the administration of low (0.4 g/kg BW, GBWE‐L) or high (0.8 g/kg BW, GBWE‐H) levels of the GBWE. The GBWE‐H‐treated hamsters exhibited significantly decreased serum levels of total cholesterols (TC) and low‐density lipoprotein‐cholesterol (LDL‐C) and significantly increased levels of lectin‐cholesterol acetyltransferase (LCAT). These results showed that GBWE‐H can reduce the total cholesterol and LDL‐C levels in HFD‐fed hamsters, and this reduction might be involved in the regulation of LCAT expression.
Public Knowledge and Attitudes towards Vitiligo: A Survey in Mekelle City, Northern Ethiopia
Authors: Tsadik Afewerki Gebremeskel , Teklemedhin Mezgebe Zeru , Mehari Atey Tesfay , Gidey Meles Tekie , Desta Desilu Mahari
Published: May 2020

Background. The overall well-being, sense of stigmatization, and treatment outcome of persons with vitiligo are largely dependent on their social acceptance and this is linked with perception and attitude of this disease in a given population. Therefore, this study assessed the knowledge and attitude of the public towards vitiligo.Methods. A cross-sectional survey was carried out using a self-reported questionnaire distributed to adults living in Mekelle city, Northern Ethiopia from August to November 2019. Individuals who were 18 to 65 years of age and not suffering from vitiligo were included in the study. A self-administered questionnaire that contains a demographic, knowledge, and attitudes parts was used to collect data. Data were entered using Epi Data® version 3.1 and analyzed using SPSS® version 21.Results. Of the total 368 subjects, 300 completed the questionnaires giving 81.5% response rate. The mean age was 30 ± 8.3 years and the male-to-female ratio was 1.14 : 1. Friends or families were reported as the most common source of information (70%) about vitiligo. The overall vitiligo knowledge was sufficient in 68.3% of the participants. Higher vitiligo-related knowledge scores were recorded by people older than 30 and below 50, those of secondary school graduated or more, urban-dwellers, persons who had heard about vitiligo, and persons having families or friends affected by vitiligo. Attitudes towards vitiligo were positive in 43.3% of participants. This was more prevalent among employed persons, those of secondary school graduated or more, and persons having families or friends affected by vitiligo. Moreover, sufficient knowledge was significantly related to positive attitudes towards the disease (p<0.0001).Conclusion. Even though the majority of the respondents had sufficient knowledge, we still found misconceptions and negative attitudes towards vitiligo. Therefore, it is still crucial to educate the public about vitiligo to ultimately improve the well-being of patients with vitiligo.
Immunohistochemical Studies of Age-Related Changes in Cell Proliferation and Angiogenesis during the Healing of Acetic Acid-Induced Gastric Ulcers in Rats
Authors: Ajayi A. Folorunsho , Olaleye S. Babafemi
Published: May 2020

Cell proliferation and angiogenesis are of utmost importance for healing to take place. The KI67 and EGFR proteins are markers of cell proliferation, while CD31 and factor VIII are markers of angiogenesis. To elucidate the mechanism responsible for delayed healing of the gastric injury in old age, we analyzed the expression of these markers in rats of different months during the healing of an acetic acid-induced gastric ulcer. Male Wistar rats (aged 3, 6, 12, and 18 months) divided into four groups, according to their ages, formed the experimental animals. Stomach tissue samples were collected on days 3, 7, 14, and 21 after induction for assessment of ulcer healing. The area of gastric mucosa healed was inversely proportional to age. The expression of markers of proliferation (KI67 and EGFR) and angiogenesis (factor VIII and CD31) decreased significantly (p<0.05) in older rats when compared with younger ones (3 months > six months > 12 months > 18 months) on days 7, 14, and 21 after induction of gastric ulcer. This study revealed that the slower gastric ulcer healing rate in older rats might be due to reduced epithelial cell proliferation and angiogenic activities.
A Characterization of Central BMO Space via the Commutator of Fractional Hardy Operator
Authors: Zhang Lei , Shi Shaoguang
Published: May 2020

This paper is devoted in characterizing the central BMO ℝn space via the commutator of the fractional Hardy operator with rough kernel. Precisely, by a more explicit decomposition of the operator and the kernel function, we will show that if the symbol function belongs to the central BMO ℝn space, then the commutator are bounded on Lebesgue space. Conversely, the boundedness of the commutator implies that the symbol function belongs to the central BMO ℝn space by exploiting the center symmetry of the Hardy operator deeply.
The Association between Leukocyte and Its Subtypes and Benign Breast Disease: The TCLSIH Cohort Study
Authors: Song Yanqi , Wang Xuena , Huang Liyan , Gu Yeqing , Cao Xingqi , Fu Jingzhu , Wu Hongmei , Li Xiaojiang , Kong Fanming , Sun Binxu , Sun Ruitian , Zhang Qing , Liu Li , Meng Ge , Zhang Shunming , Jia Yingjie , Niu Kaijun
Published: May 2020

Inflammation plays a crucial role in the formation of benign breast disease. Given the limited study to explore the association between leukocyte as an indicator of immune system and benign breast disease, we used data from a large cross-sectional study to investigate association between leukocyte and its subtypes and benign breast disease among women in the general population. The data were derived from baseline data of the Tianjin chronic low-grade systemic inflammation and health (TCLSIH) cohort study during 2014 and 2016. Breast thickness and nodules status were assessed by using ultrasonography. Leukocyte and its subtype counts were carried out using the automated hematology analyzer. Multiple logistic regression analysis was used to examine the association between leukocyte and its subtypes and prevalence of benign breast disease. In the present study, the prevalence of benign breast disease was 20.9%. After adjustments for potentially confounding factors, the odds ratios (95% confidence interval) for benign breast disease across lymphocyte quintiles were as follows: 1.00 (reference), 0.99 (0.82, 1.2), 0.85 (0.69, 1.04), 0.84 (0.68, 1.02), and 0.75 (0.61, 0.92) (P for trend = 0.002). An inverse association between lymphocyte counts and benign breast disease was found, but leukocyte and other subtypes have nothing to do with benign breast disease. Further prospective studies are needed to determine the findings.
Dynamic Repair and Robust Optimization of Complex Networks
Authors: Zhang Pengtao , Bai Peng , Fu Chaoqi , Li Shanshan
Published: May 2020

Network repair is indispensable for maintaining network security. Conventional static repair is relatively inefficient. In this study, by considering the energy transfer between nodes, a dynamic repair model was established. The fundamental reason for the secondary failure of repaired nodes during the dynamic repair process is the coupling structure of failure networks. A dynamic repair strategy was proposed that can effectively prevent the secondary failure of repair nodes influenced by energy during repair and can cause the redundant capacity of repair nodes to be used reasonably. By turning off the energy transfer function of the link to control the excessive flow of energy into the repair node to avoid the occurrence of secondary failure; on the other hand, by sharing part of the load of the failure node, realize the rational use of the redundant capacity of the repair node to reduce the impact of the failure node on the overall function of the network. The proposed strategy mitigated the effect of failure nodes on network functions and substantially improved the recovery efficiency of network functions. Furthermore, redundant edges, behaving as energy redundant links in a network structure, can considerably improve the robustness of the network by optimizing the removal of redundant edges. Dynamic repair is not only an efficient repair method but also a highly flexible choice for network repair.
Global Synchronization of Reaction-Diffusion Fractional-Order Memristive Neural Networks with Time Delay and Unknown Parameters
Authors: Sun Wenjiao , Ren Guojian , Yu Yongguang , Hai Xudong
Published: May 2020

This paper investigated the global synchronization of fractional-order memristive neural networks (FMNNs). To deal with the effect of reaction-diffusion and time delay, fractional partial and comparison theorem are introduced. Based on the set value mapping theory and Filippov solution, the activation function is extended to discontinuous case. Adaptive controllers with a compensator are designed owing to the existence of unknown parameters, with the help of Gronwall–Bellman inequality. Numerical simulation examples demonstrate the availability of the theoretical results.
Predicting Soil-Water Characteristic Curves of Clayey Sand Soils Using Area Computation
Authors: Dafalla M. A. , Al-Mahbashi A. M. , Almajed A. , Al-Shamrani M.
Published: June 2020

The soil-water characteristic curves (SWCCs) for soils are important for geotechnical engineers in the prediction of clay behavior in case of partially saturated conditions. In the wastewater and waste containment industry, variable clay content is considered. It is not practical to run a time-consuming test several times to obtain the soil-water characteristic curves for every proportion. This study is aimed at introducing a practical procedure to predict the response of clay of known mineralogy and geological setting when clay content within a liner is variable. Fitting curves were performed using Fredlund and Xing’s (1994) equations. The general trends were established for selected clay of known high content of smectite minerals. Obtained curves were examined, and areas under the suction curve were integrated from the starting point to the inflection point for clay-sand material with 5%, 10%, 15%, 30%, 60%, and 100% clay content. This area can be used to estimate the profile of the SWCC for higher or lower clay content based on an area factor determined for a specific clay type or clay of known mineralogy. Other clay of similar nature, but not typical mineralogy, were compared in order to observe and validate the use of the area method in predicting the SWCC for similar soils.
Perceptions and Practice of Early Diagnosis of Sickle Cell Disease by Parents and Physicians in a Southwestern State of Nigeria
Authors: Olatunya Oladele Simeon , Babatola Adefunke Olarinre , Ogundare Ezra Olatunde , Olofinbiyi Babatunde Ajayi , Lawal Olubunmi Adeola , Awoleke Jacob Olumuyiwa , Aduloju Olusola Peter , Daramola Alaba Olanrewaju , Emmanuel Eyitayo Ebenezer , Olajuyin Oyebanji Anthony , Komolafe Akinwumi Kolawole , Olaleye Abiola Olukayode
Published: May 2020

Background. Early sickle cell disease (SCD) diagnosis has shown promise in combating SCD in many countries. The aim of this study was to assess the practice and perception of early SCD diagnosis among a group of parents and physicians in Nigeria. Patients and Methods. This was a cross-sectional descriptive study conducted to assess the opinions and practice of early diagnosis of SCD among 135 physicians caring for SCD patients and 164 mothers of children with SCD in a southwestern state of Nigeria. Results. Most physicians 132 (97.8%) were aware of prenatal SCD diagnosis, but only 51 (37.8%) would recommend it. Most physicians 129 (95.6%) routinely recommend premarital SCD genetic counseling and testing, and 89 (65.1%) were aware of the national government newborn screening program but lesser proportion 75 (55.6%) were willing to recommend it. Amongst the mothers, 154 (94%) and 158 (96%) had encountered genetic counseling for SCD and were willing to offer newborn screening to their children, respectively. On the contrary, fewer mothers 42 (25%) were aware of prenatal SCD diagnosis, 28 (17%) were willing to partake in it, and 44 (26%) were undecided. There were discrepancies in the willingness by physicians to practice early SCD diagnosis and its uptake by mothers (p<0.0001). The commonest reason given by both the physicians and mothers for not practicing SCD prenatal diagnosis was the high cost of the procedure. Conclusion. The perceptions and practice of early SCD diagnosis was suboptimal in the study locality. Scaling up awareness and universal coverage are required.
On the Eccentric Connectivity Polynomial ofℱ-Sum of Connected Graphs
Authors: Imran Muhammad , Akhter Shehnaz , Iqbal Zahid
Published: May 2020

The eccentric connectivity polynomial (ECP) of a connected graphG=VG,EGis described asξcG,y=∑a∈VGdegGayecGa, whereecGaanddegGarepresent the eccentricity and the degree of the vertexa, respectively. The eccentric connectivity index (ECI) can also be acquired fromξcG,yby taking its first derivatives aty=1. The ECI has been widely used for analyzing both the boiling point and melting point for chemical compounds and medicinal drugs in QSPR/QSAR studies. As the extension of ECI, the ECP also performs a pivotal role in pharmaceutical science and chemical engineering. Graph products conveniently play an important role in many combinatorial applications, graph decompositions, pure mathematics, and applied mathematics. In this article, we work out the ECP ofℱ-sum of graphs. Moreover, we derive the explicit expressions of ECP for well-known graph products such as generalized hierarchical, cluster, and corona products of graphs. We also apply these outcomes to deduce the ECP of some classes of chemical graphs.
Strong-LAMP Assay Based on a Strongyloides spp.-Derived Partial Sequence in the 18S rRNA as Potential Biomarker for Strongyloidiasis Diagnosis in Human Urine Samples
Authors: Fernández-Soto Pedro , Celis-Giraldo Carmen T. , Collar-Fernández Coralina , Gorgojo Óscar , Camargo Milena , Muñoz José , Salas-Coronas Joaquín , Patarroyo Manuel A. , Muro Antonio
Published: May 2020

Human strongyloidiasis a soil-transmitted infection caused by Strongyloides stercoralis is one of the most neglected amongst the so-called Neglected Tropical Diseases (NTDs). S. stercoralis is a nematode, which is distributed worldwide; it has been estimated that it could affect millions of people, mainly in tropical and subtropical endemic regions. The difficulties of diagnosis lead to infection rates being underreported. Asymptomatic patients have chronic infections that can lead to severe hyperinfection syndrome or disseminated strongyloidiasis in immunocompromised patients. Strongyloidiasis can easily be misdiagnosed because conventional faecal-based techniques lack of sensitivity for the morphological identification of infective larvae in faeces. None of the currently used molecular methods have used urine samples as an alternative to faecal samples for diagnosing strongyloidiasis. This study was thus aimed at comparing, for the first time, the use of a new loop-mediated isothermal amplification (LAMP) molecular assay (Strong-LAMP) to traditional methods on patients’ urine samples. Twenty-four urine samples were taken from patients included in a study involving two Spanish hospitals for strongyloidiasis screening using parasitological and serological tests. Strongyloides larvae were found in 11 patients’ faecal samples, thereby ascertaining that they had the disease. Other patients had high antibody titres but no larvae were found in their faeces. All urine samples were analysed by PCR and Strong-LAMP assay. No amplification occurred when using PCR. Strong-LAMP led to detecting S. stercoralis DNA in urine samples from patients having previously confirmed strongyloidiasis by parasitological tests and/or a suspicion of being infected by serological ones. The Strong-LAMP assay is a useful molecular tool for research regarding strongyloidiasis in human urine samples. After further validation, the Strong-LAMP assay could also be used for complementary and effective diagnosis of strongyloidiasis in a clinical setting.