bluuebunny/crossref_metadata_2025_split huggingface dataset:
Possible neuropathic pain in patients with osteoarthritis of the knee before and after total knee arthroplasty
Authors: Hasegawa Masahiro , Tone Shine , Naito Yohei , Sudo Akihiro 
Published: April 2021

Abstract
Background: Although osteoarthritis (OA) is traditionally considered to be nociceptive, our objective was to examine neuropathic pain in the knees of OA patients using the painDETECT questionnaire (PDQ).Methods: A total of 180 knees in 158 consecutive patients who underwent total knee arthroplasty (TKA) were enrolled. The prevalence of neuropathic pain, unclear pain and nociceptive pain was determined before and after TKA. Knee pain was evaluated using a numerical rating scale (NRS). All patients were evaluated preoperatively and 6 months postoperatively. Neuropathic pain and unclear pain were grouped together as possible neuropathic pain. The relationship between possible neuropathic pain and pain intensity was evaluated.Results: Before TKA, neuropathic pain and unclear pain were found in 10 and 30 knees, respectively. The remaining 140 knees were categorized as nociceptive pain. After TKA, the numbers of knees with neuropathic and unclear pain decreased to one and five, respectively. The prevalence of possible neuropathic pain decreased significantly from 22.2% to 3.3% (p < 0.001) after surgery. Among the six knees with possible neuropathic pain postoperatively, four had possible neuropathic pain preoperatively as well, while the remaining two patients had been classified as nociceptive pain preoperatively (p = 0.021). Knees with postoperative possible neuropathic pain had higher postoperative NRS scores than those with nociceptive pain (p = 0.011).Conclusions: The prevalence of possible neuropathic pain decreased significantly after TKA, however, preoperative possible neuropathic pain might affect the presence of persistent postoperative pain.
A Genetic Algorithm for Subcontractors Selection and Allocation in Multiple Building Projects
Authors: Afshar Mohammad Reza , Shahhosseini Vahid , Sebt Mohammad Hassan 
Published: April 2021

Abstract
In construction industry general contractors (GCs) need to manage and conduct numerous projects simultaneously. To this aim, they usually have subcontractors conduct available tasks and projects. So, subcontractor management is becoming a major challenge. To deal with this challenge, GCs aim to reduce total costs of projects including employment /subcontracting costs, indirect costs, tardiness penalties, and the money which must be paid for movement of workforce from one project to another. The aim of current research study is to propose a model for selecting subcontractors and assigning available tasks in the project to them in order to reduce the costs of the GC. Then, a genetic algorithm (GA) is proposed to solve a real problem. The proposed algorithm is innovative from three points of view: (1) generation of initial population; (2) subcontractor assignment approach and (3) the objective function. The problem was also solved by means of an exact method. Then, the results of proposed algorithm were compared to the outcomes of the exact method. This comparison shows that the proposed algorithm can efficiently help GCs select subcontractors and assign available tasks to each subcontractor when several projects must be carried out simultaneously.
SCLRP - Architecture for Secure Cross-Layer Routing Protocol for Underwater Acoustic Sensor Networks using Fuzzy Logic and Enhanced Algebra Homomorphic Encryption
Authors: jayaraman sathiamoorthy , M Usha , R Bhagavath Nishanth , R Ashween 
Published: April 2021

Abstract
The latest research in WSNs (Wireless Sensor Network) has been exploring Underwater Acoustic Sensor Networks (UASNs). As the name suggests, these networks aim at providing effective communication underwater by addressing the challenges prevalent in this network. Underwater communication has found a lot of applications in ocean monitoring and underwater contamination monitoring. The issue of routing underwater is a major concern as it has to address a lot of challenges. Creating an effective routing protocol has been a constant topic of research in UASNs. We have focused on a Secure Cross-Layer Routing Protocol (SCLRP) in UASNs using Fuzzy Logic and Enhanced Algebra Homomorphic Encryption. This protocol aims at providing secure data transmission using optimized nodes that are selected from the neighboring nodes of the source node. The optimal nodes are selected by applying fuzzy rules to the available input. The selected nodes will then forward the packets to the next hop till the packet reaches the destination. The proposed protocol is an Energy Efficient Secure Fuzzy Logic based Cross –Layer design routing protocol. Our proposed protocol ensures safe transmission of data, which is the main objective of a routing protocol used in a wireless network. The routing protocol will ensure better QoS, by using a reliable encryption technique to reinforce secure routing. The protocol incorporates an enhanced Algebra Homomorphic encryption technique to help with managing the security of the transmitted data. QoS is further improved by using a cross-layer design wherein, the proposed protocol will not be expected to adjust as the data travels the different layers of the network so the protocol will be free from the confines of the standards and protocols followed in each of the layer. This flexibility will help in making our protocol perform better than the existing techniques. The SCLRP protocol is analyzed with the performance of NADIR and EEMCCP schemes to analyze its performance.
Probabilistic Evaluation of CPT-based Seismic Soil Liquefaction Potential: Towards the Integration of Interpretive Structural Modeling and Bayesian Belief Network
Authors: Ahmad Mahmood , Tang Xiao-Wei , Ahmad Feezan , Pirhadi Nima , Wan Xusheng , Cheng Kuang 
Published: April 2021

Abstract
This paper proposes a probabilistic graphical model that integrates interpretive structural modeling (ISM) and Bayesian belief network (BBN) approaches to predict CPT-based soil liquefaction potential. In this study, an ISM approach was employed to identify relationships between influence factors, whereas BBN approach was used to describe the quantitative strength of their relationships using conditional and marginal probabilities. The proposed model combines major causes, such as soil, seismic and site conditions, of seismic soil liquefaction at once. To demonstrate the application of the propose framework, the paper elaborates on each phase of the BBN framework, which is then validated with historical empirical data. In context of the rate of successful prediction of liquefaction and non-liquefaction events, the proposed probabilistic graphical model is proven to be more effective, compared to logistic regression, support vector machine, random forest and naïve Bayes methods. This research also interprets sensitivity analysis and the most probable explanation of seismic soil liquefaction appertaining to engineering perspective.
Actinoplanes aureus sp. nov., a novel protease-producing actinobacterium isolated from soil
Authors: Sun Xiujun , Luo Xianxian , He Chuan , Huang Zhenzhen , Zhao Junwei , He Beiru , Du Xiaowen , Xiang Wensheng , Song Jia , Wang Xiangjing 
Published: April 2021

Abstract
A novel protease-producing actinobacterium, designated strain NEAU-A11T, was isolated from soil collected from Aohan banner, Chifeng, Inner Mongolia Autonomous Region, China, and characterised using a polyphasic approach. On the basis of 16S rRNA gene sequence analysis, strain NEAU-A11T was indicated to belong to the genus Actinoplanes and was most closely related to Actinoplanes rectilineatus JCM 3194T (98.9 %). Cell walls contained meso-diaminopimelic acid as the diagnostic diamino acid and the whole-cell sugars were arabinose, xylose and glucose. The phospholipid profile contained diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, phosphatidylinositol and two phosphatidylinositol mannosides. The predominant menaquinones were MK-9(H4), MK-9(H6) and MK-9(H8). The major fatty acids were C18:0, C16:0, C18:1 ω9c, C17:0 and C15:0. Genome sequencing revealed a genome size of 10,742,096 bp, a G + C content of 70.5 % and 9,514 protein-coding genes (CDSs), including 102 genes coding for protease. Genome mining analysis using antiSMASH 5.0 led to the identification of 20 putative gene clusters responsible for the production of diverse secondary metabolites. Phylogenetic analysis using the 16S rRNA gene sequences showed that the strain formed a stable clade with A. rectilineatus JCM 3194T in the genus Actinoplanes. However, whole-genome average nucleotide identity (ANI) value and the levels of digital DNA-DNA (dDDH) hybridization between strain NEAU- A11T and A. rectilineatus JCM 3194T was 81.1 % and 24.6 % (22.2–27.0 %), respectively. The values were well below the criteria for species delineation of 70% for dDDH and 95–96% for ANI, suggesting that the isolate differed genetically from its closely related type strain. In addition, evidences from phenotypic, chemotaxonomic and genotypic studies indicate that strain NEAU-A11T represents a novel species of the genus Actinoplanes, for which the name Actinoplanes aureus sp. nov. is proposed, with NEAU-A11T (= CCTCC AA 2019063T = JCM 33971T) as the type strain.
Adapting to the impact of the COVID-19 pandemic on a randomized controlled trial examining lifestyle behaviors on cognitive functioning in obese African American adults: Building Research in Diet and Cognition (BRIDGE)
Authors: Fitzgibbon Marian , Blumstein Lara , Schiffer Linda , Antonic Mirjana , McLeod Andrew , Dakers Roxanne , Restrepo Leo , Boots Elizabeth , Sanchez-Flack Jennifer , Tussing-Humphreys Lisa , Lamar Melissa 
Published: April 2021

Abstract
Background. The COVID-19 pandemic has significantly altered the research landscape for clinical trials, requiring thoughtful consideration regarding how to handle the risks and benefits of continuing them. Design. This brief report describes the experience of adapting the Building Research in Diet and Cognition (BRIDGE) study, a randomized clinical trial examining the effects of the Mediterranean Diet, with and without weight loss, on cognitive functioning in 185 older obese African American adults during the COVID-19 pandemic. Measurement. The University of Illinois at Chicago (UIC) developed an expedited amendment process for research shifting to remote data collection. For the Cohort 3, 14-month data collection period, we adapted our protocol to allow data collection via telephone and e-mail. We were unable to collect certain measures that required face-to face contact. Results. For measures that could be collected remotely, 14-month retention was similar for Cohort 3 and earlier cohorts: data were collected for 86.9% of cohort 3 (remote) and 87.9% of cohorts 1 and2 (face to face), p = .84. Conclusions. In order to preserve the integrity of our clinical trial and ensure the safety of our participants and staff during the COVID-19 pandemic, we had to carefully and efficiently adapt our data collection procedures. The procedures put in place allowed us to collect our primary outcomes and the majority of our secondary outcomes and will enable us to examine the role of dietary intake, with and without weight loss, on cognitive functioning in a vulnerable and high-risk population. ClinicalTrials.gov NCT03129048
The rooting ability of in-vitro shoot cultures established from a UK collection of the common ash (Fraxinus excelsior L.) and their ex-vitro survival
Authors: Fenning Trevor Malcolm , O’Donnell Margaret , Preedy Katharine , Bézanger Aurélia , Kenyon David , Lopez Gustavo 
Published: April 2021

Abstract
There is renewed in the tissue culture of the European ash in response to ash dieback disease. Shoot cultures were established for 135 clones from 13 ash mother trees from the UK’s national collection, on DKW medium with 3ppm of BAP. Most were generated from hypocotyl pieces excised from sterile germinating mature ash seeds. Another 24 clones were lost to bacterial contamination, which was identified as Bacillus megaterium or possibly a close relative. These cultures were disposed of as it was difficult to eliminate the bacterium from them. The ability of all of the cultures to produce rooted plants capable of normal growth under nursery conditions was tested by exposing excised shoots to DKW medium with 3ppm IBA for 2 weeks, followed by 4–6 weeks on hormone-free medium. Across all experiments 41.5% of uncontaminated plants and 11.6% of contaminated plants produced roots in-vitro. Although differences were observed in the rooting ability between clones, families and from trial to trial, the only significant effect was whether the shoots were contaminated or not. In addition, 92.6% of the uncontaminated plants survived the transfer to the nursery as opposed to 62.1% of the contaminated plants. We show here that a single methodology can be successfully used to produce large numbers of clonal ash plants on demand from a wide cross-section of the UK’s ash breeding population, although contamination issues will need to be closely monitored for this approach to be used as part of the strategy for combating overcoming ash dieback disease.
Improvement of the LbCas12a-crRNA system for efficient gene targeting in plants
Authors: Vu Tien Van , Doan Duong Thi Hai , Tran Mil Thi , Sung Yeon Woo , Song Young Jong , Kim Jae-Yean 
Published: April 2021

Abstract
Plant gene targeting (GT) can be utilized to precisely replace up to several kilobases of a plant genome. Recent studies using the powerful clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) nucleases significantly improved plant GT efficiency. However, GT for loci without associated selection markers is still inefficient. We previously utilized Lachnospiraceae bacterium Cas12a (LbCas12a) in combination with a replicon for tomato GT and obtained high GT efficiency with some selection markers. In this study, we optimize and advance our GT system by using a temperature-tolerant LbCas12a (ttLbCas12a) in combination with various crRNA forms and chemical treatments to suppress the canonical non-homologous end-joining pathway in tomato. Our work demonstrates the significance of the selection of gene scissors, the appropriate design and number of LbCas12a crRNAs, the use of chemical treatments, and the establishment of favorable experimental conditions for further enhancement of plant HDR to enable efficient GT in tomato.
Parkinson's Detection Based On Combined CNN And LSTM Using Enhanced Speech Signals With Variational Mode Decomposition
Authors: ER Mehmet Bilal , ISIK Esme , ISIK Ibrahim 
Published: April 2021

Abstract
The dysfunction of the cells in the brain that contain the substance known as dopamine, which enables brain cells to interact with each other, results in Parkinson's disease (PD). PD can cause many non-motor and motor symptoms such as speech and smell. One of the difficulties that Parkinson’s patients can experience is a change in speech or speaking difficulties. Therefore, the right diagnosis in the early period is important in reducing the possible effects of speech disorders caused by the disease. Speech signal of Parkinson patients shows major differences compared to normal people. In this study, a new approach based on pre-trained deep networks and Long short-term memory (LSTM) by using mel-spectrograms obtained from denoised speech signals with Variational Mode Decomposition (VMD) for detecting PD from speech sounds is proposed. The proposed model consists of four stages. In the first step, the noise is removed by applying VMD to the signals. In the second stage, Mel-spectrograms are extracted from the enhanced sound signals with VMD. In the third stage, pre-trained deep networks are preferred to extract deep features from the Mel-spectrograms. For this purpose, ResNet-18, ResNet-50 and ResNet-101 models are used as pre-trained deep network architecture. In the last step, the classification process is occured by giving these features as input to the LSTM model, which is designed to define sequential information from the extracted features. Experiments are performed with the PC-GITA dataset, which consists of two classes and is widely used in the literature. The results obtained from the proposed method are compared with the latest methods in the literature, it is seen that it has a better performance in terms of classification performance.
Factor Graph Weight Particles aided Distributed Underwater Cooperative Positioning Algorithm
Authors: zhang lingling , yu baoguo , Tang Chengkai , zhang yi , Song Houbing 
Published: April 2021

Abstract
The growing scale of marine exploration requires high-resolution underwater localization, which necessitates cooperation among underwater network nodes, considering the channel complexity and power efficiency. In this paper, we proposed factor graph weight particles aided distributed underwater nodes cooperative positioning algorithm (WP-DUCP). It capitalized on the factor graph and sum-product algorithm to decompose the global optimization to the product of several local optimization functions. Combined with the Gaussian parameters to construct the weighted particles and to realize the belief transfer, it shows low complexity and high efficiency, suitable to the energy-restricted and communication distance-limited underwater networks. In terms of convergence, localization resolution, and computation complexity, we conducted the simulation and real-test with comparison to the existing co-localization methods. The results verified a higher resolution of the proposed method with no extra computation burden.
Two determinantal inequalities for positive semidefinite matrices
Authors: Hong Yan , Qi Feng 
Published: April 2021

Abstract

Let A,B,C ∈ Cnxn be positive semidefinite matrices. In this paper, the authors prove two determinantal inequalities|A+B+C|+|C|≥|A+C|+|B+C|+(3n −2 n+1+1)|ABC|1/3and|A+B+C|+|A|+|B|+|C|≥|A+B|+|A+C|+|B+C|+3(3n−1−2n+1)|ABC|1/3.These two inequalities improve known ones.
Contribution of Soil and Litter Nutrient Characteristics to Plant Nutrients in a Natural Secondary Mixed Forest in the Qinling Mountains, China
Authors: Pang Yue , Tian Jing , Liu Lanxin , Han Lina , Wang Dexiang 
Published: April 2021

Abstract
Soil and litter play important roles in ecosystem nutrient stroage and cycling, which both affect plant growth and ecosystem productivity. However, the potential contributions of soil and litter nutrient characteristics to the nutrient characteristics of different plant functional groups (PFGs) remain unclear. In this study, we investigated the carbon (C), nitrogen (N) and phosphorus (P) concentrations of different organs of three PFGs (trees, shrubs and herbs), litter and soil in nine natural secondary mixed forests in the Qinling Mountains. The results showed that leaves had the highest N and P concentrations and N:P ratios at the organ level, whereas the C:N and C:P values were lowest in leaves. At the PFG level, the N and P concentrations of the same organs in herbaceous plants were significantly higher than those in woody species, while the N:P ratio was significantly lower in herb leaves than in tree and shrub leaves. Tree organs had significantly higher C concentrations and C:N and C:P ratios than shrub and herb organs. The leaf N:P ratios of all PFGs were less than 14, suggested that plant growth was limited by N in the study region. The nutrient contents and stoichiometric ratios in plant organs had different degrees of linkages with those in litter and soil. Soil nutrient characteristics were the main factors affecting the nutrient characteristics of the different PFGs, and litter nutrient characteristics also had important contributions to the nutrient characteristics of PFGs, showing the following order: herbs > trees > shrubs. Our results indicate that the functional difference in plant organs resulted in diverse nutrient concentrations; and varied nutrient connections exist among different ecosystem components. Furthermore, nutrient characteristics of litter and soil can together affect the nutrient characteristics of PFGs.
MacroH2A histone variants modulate enhancer activity to repress oncogenic programs and cellular reprogramming
Authors: Ismail Wazim Mohammed , Mazzone Amelia , Kaur Jagneet , Safgren Stephanie , Moore-Weiss John , Buciuc Marina , Shimp Lynzie , Duarte Luis , Nagi Chandandeep , Carcamo Saul , Chung Chi-Yeh , Hasson Dan , Dadgar Neda , Revzin Alexander , Zhong Jian , Lee Jeong-Heon , Ordog Tamas , Bernstein Emily , Gaspar-Maia Alexandre 
Published: April 2021

Abstract
Considerable efforts have been made to characterize active enhancer elements, which can be annotated by accessible chromatin and H3 lysine 27 acetylation (H3K27ac). However, apart from poised enhancers that are observed in early stages of development and putative silencers, the functional significance of cis-regulatory elements lacking H3K27ac is poorly understood. Here we show that macroH2A histone variants mark a subset of enhancers in normal and cancer cells, which we coined ‘macroH2A-Bound Enhancers’, that negatively modulate enhancer activity. We find macroH2A variants enriched at enhancer elements that are devoid of H3K27ac in a cell type-specific manner, indicating a role for macroH2A at inactive enhancers to maintain cell identity. In following, reactivation of macro-bound enhancers is associated with oncogenic programs in breast cancer and its repressive role is correlated with the activity of macroH2A2 as a negative regulator of BRD4 chromatin occupancy. Finally, through single cell epigenomic profiling, we show that the loss of macroH2A2 leads to increased cellular heterogeneity that may help to explain the role of macroH2A variants in defining oncogenic transcriptional dependencies.
Research on recognition of human lying posture based on Kinect sensor
Authors: Wang Qi , Meng Xianyu , Li Cong , Liu Hongsheng , Yu Xiquan 
Published: April 2021

Abstract
As a high-tech intelligent product, the intelligent nursing bed largely meets the needs of the disabled for self-care, and saves a lot of manpower and material resources. In order to improve the safety and reliability of the intelligent nursing bed and ensure the safety of the user, this paper adds the recognition of the human body's lying posture as a part of the movement signal of the nursing bed. The Kinect sensor is used to track human bones, record human bone data, and preprocess human bone data. Use the pattern recognition toolbox in Matlab to classify the processed data to realize the recognition of the human body's lying posture. The average recognition rate of the five postures is 98.1%. The results show that the model used in this experiment has a high degree of recognition and can greatly improve the safety and reliability of the intelligent nursing bed.