bluuebunny/crossref_metadata_2025_split huggingface dataset:
1,2-benzenedicarboxylic acid, bis (2-methyl propyl) ester isolated from Onosma bracteata Wall. inhibits MG-63 cells proliferation via Akt-p53-cyclin pathway
Authors: Kumar Ajay , Kaur Sandeep , Dhiman Sukhvinder , Singh Prithvi Pal , Thakur Sharad , Sharma Upendra , Kumar Subodh , Kaur Satwinderjeet 
Published: June 2021

Abstract
Onosma bracteata Wall. (Boraginaceae family) is one of the important constituents of Ayurvedic drugs which enhance immunity. Among all the fractions isolated from O. bracteata, ethyl acetate fraction (Obea) showed good antioxidant activity in Superoxide radical scavenging assay and Lipid peroxidation assay with EC50 value of 95.12 and 80.67 µg/ml, respectively. Silica gel column chromatography of Obea yielded ObD1 fraction which was characterized as Di-isobutyl phthalate (DIBP) using NMR, FTIR and HRMS spectroscopic techniques. DIBP showed antiproliferative activity in human osteosarcoma MG-63, human neuroblastoma IMR-32 and A549 cell lines with GI50 value of 37.53, 56.05 and 47.12 µM, respectively, in MTT assay. In Flow cytometric studies, DIBP has shown disruption of mitochondrial membrane potential (MMP) and enhancement of ROS, indicating the apoptosis induction. The cells were found to be delayed at G0/G1 phase which might be due to the downregulation of Cyclin E and CDK2 as shown in RT-PCR studies. Western blotting analysis revealed an increased expression of p53, caspase 3 and caspase 9 and downregulation of p-NF-kB, p-Akt and Bcl-xl. Molecular docking studies also displayed the interaction of DIBP with p53 (− 151.13 kcal/mol) and CDK1 (− 133.96 kcal/mol). Thus, DIBP has exhibited great potential as chemopreventive/chemotherapeutic agent against osteosarcoma.
Action Recognition for the Robotics and Manufacturing Automation Using 3-D Binary Micro-block Difference
Authors: Voronin Viacheslav , Zhdanova Marina , Semenishchev Evgenii , Zelenskii Aleksander , Cen Yigang , Agaian Sos 
Published: June 2021

Abstract
Vision-based control systems play an important role in modern robotics systems. An important task in implementing such a system is the development of an effective algorithm for recognizing human actions and the working environment and the design of intuitive gesture commands. This paper proposes an action recognition algorithm for robotics and manufacturing automation. The key contributions are (1) fusion of multimodal information obtained by depth sensors and cameras of the visible range, (2) modified Gabor-based and 3-D binary-based descriptor using micro-block difference, (3) efficient skeleton-based descriptor, and (4) recognition algorithm using the combined descriptor. The proposed binary micro-block difference representation of 3-D patches from video with a complex background in several scales and orientations leads to an informative description of the scene action. The experimental results showed the effectiveness of the proposed algorithm on data sets.
Maturing autophagosomes are transported towards the cell periphery
Authors: Hilverling Anna , Szegö Eva M. , Dinter Elisabeth , Cozma Diana , Saridaki Theodora , Falkenburger Björn H. 
Published: June 2021

Abstract
Autophagosome maturation comprises fusion with lysosomes and acidification. It is a critical step in the degradation of cytosolic protein aggregates that characterize many neurodegenerative diseases. In order to better understand this process, we studied intracellular trafficking of autophagosomes and aggregates of α-synuclein, which characterize Parkinson’s disease and other synucleinopathies.
The autophagosomal marker LC3 and the aggregation prone A53T mutant of α-synuclein were tagged by fluorescent proteins and expressed in HEK293T cells and primary astrocytes. The subcellular distribution and movement of these vesicle populations were analyzed by (time-lapse) microscopy. Fusion with lysosomes was assayed using the lysosomal marker LAMP1; vesicles with neutral and acidic luminal pH were discriminated using the RFP-GFP “tandem fluorescence” tag.
With respect to vesicle pH, we observed that neutral autophagosomes, marked by LC3 or synuclein, were located more frequently in the cell center, and acidic autophagosomes were observed more frequently in the cell periphery. Acidic autophagosomes were transported towards the cell periphery more often, indicating that acidification occurs in the cell center before transport to the periphery. With respect to autolysosomal fusion, we found that lysosomes preferentially moved towards the cell center whereas autolysosomes moved towards the cell periphery, suggesting a cycle where lysosomes are generated in the periphery and fuse to autophagosomes in the cell center. Unexpectedly, many acidic autophagosomes were negative for LAMP1, indicating that acidification does not require fusion to lysosomes. Moreover, we found both neutral and acidic vesicles positive for LAMP1, consistent with delayed acidification of the autolysosome lumen.
Individual steps of aggregate clearance thus occur in dedicated cellular regions. During aggregate clearance, autophagosomes and autolysosomes form in the center and are transported towards the periphery during maturation. In this process, luminal pH could regulate the direction of vesicle transport.
Virtual Cleaning of Works of Art Using Deep Convolutional Neural Networks
Authors: Amiri Morteza Maali , Messinger David W 
Published: June 2021

Abstract
Virtual cleaning of art is a key process that conservators apply to see the likely appearance of the work of art they have aimed to clean, before the process of cleaning. It is also of public interest, allowing people to see their favorite work of art without the yellow tint of the varnish which has covered the work. There have been many different approaches to virtually clean artwork, all of which need to physically clean the work in at least a few spots, an impediment in some cases. Another issue regarding the methods devised until now is that some of them need samples of pure white or black paint on the painting which might be, again, an obstacle as there are certainly works without any pure black and white paint. To overcome these shortcomings, a Convolutional Neural Network is trained on representative RGB images; the images are first artificially yellowed using a physics based model and the network is trained to go from the yellowed images to the original colored images. The results show improvement over a proposed method using a physical model to remove the impacts of age. The CNN is then applied to images of the Mona Lisa and The Virgin and Child with Saint Anne, both painted by Leonardo da Vinci, and works for which we have images from both before and after physical cleaning. Results show both a qualitative and quantitative improvement in the color quality of the resulting image. The novelty of the work proposed herein lies in two premises. First is the accuracy of the method, which is demonstrated through comparing the method with the only physical approach derived until now. Second is the generalizability of the method which is shown through blindly applying the method to two famous works of art for which no information but an RGB image of the uncleaned artwork is known.
Feasibility for SARS-CoV-2 Tests in the Hospital: An Exposure Analysis of Critical Control Points Approach
Authors: Feng Tingting , Leptihn Sebastian , Li Mingyue , Guo Mingquan , Gao Jing , Li Qingtian , Zeng lingbing , Zhou Yuhua , Wei Yanxia , Guo Xiaokui , Temperton Nigel , Cui Zelin 
Published: June 2021

Abstract
This work aims to assess the feasibility of performing COVID-19 RNA tests in hospitals and communities experiencing SARS-CoV-2 virus outbreaks, to ultimately provide recommendations for hospitals with so-called fever clinics. In China, these specialized clinics within a hospital specifically receive outpatients with fever symptoms. A team with expertise in the Exposure Analysis and Critical Control Points (EACCP) framework identified potential infection routes during the testing for SARS-CoV-2, then constructed and tested flow diagrams, which were confirmed under actual conditions, demonstrating the feasibility to carry out in hospitals with fever clinics. The team determined critical control points to mitigate the exposure risks at each control point. The sampling and inactivation steps of clinical samples in fever clinics appeared to be associated with particularly high-risk levels of exposure to SARS-CoV-2. Moderate exposure levels were associated with storage and transportation of samples for inactivation; Low-risk levels associated with the transportation, storage, and detection steps after inactivation. To minimize infection risks for personnel, we proposed optimized processes to carry out SARS-CoV-2 RNA tests in hospitals with fever clinics in China. The high risk of SARS-CoV-2 exposure during procedures preceding testing is the sampling and biological inactivation; Simultaneously, full personal protective equipment and BSL2 laboratories in fever clinics or mobile BSL2 laboratories could reduce the risk. Implementing the EACCP framework could facilitate rapid responses to outbreaks of emerging infectious diseases.
Transfer Modeling for 1T1R Crossbar Arrays with Line Resistances
Authors: Zhang Xin , Zeng Ying 
Published: June 2021

Abstract
Progress of neuromorphic computing and next-generation information storage technologies hinges on the development of emerging nonvolatile memory (eNVM) devices, which are typically organized employing the crossbar array architecture. To facilitate quantitative performance analysis of eNVM crossbar array architecture, this paper proposes a way to study the one-transistor-one-resistor (1T1R, R: eNVM devices) crossbar arrays based on matrix algebra method. The comparative analysis of 1T1R crossbar array modeling based on matrix algebra method and compact-model SPICE simulations verifies the accuracy of the proposed method, which can be directly used for static quantitative analysis and evaluation of 1T1R crossbar array performance. With the proposed method, the optimization of array operation schemes and current backflow issue are discussed. Our analysis indicates that the proposed method is capable of flexibly adjusting array parameters and consider the influence of line resistance on array operation, and can provide guidance for improving the sensing margin of the array through multi-parameter co-simulation. The proposed matrix algebra-based 1T1R crossbar array modeling method can bridge the gap between the accuracy and flexibility of the available methods.
Silage Quality, Aerobic Stability, Gas Production and in vitro Digestibility of Pumpkin Waste Silages
Authors: Konca Yusuf , Beyzi Selma Büyükkılıç , Kaplan Mahmut , Boga Mustafa , Kaliber Mahmut 
Published: June 2021

Abstract
This experiment was carried out to determine the silage quality of pumpkin waste with wheat straw (S) and alfalfa hay (A). The treatment groups as follows: 1) 100% pumpkin waste (PR), 2) 80%PR and 20% A (PW80+A20), 3) 80%PW and 20%S (PW80+S20), 4) 60%PW and 40%A (PW60+A40), 5) 60%PW and 40%S (PW60+S40), 6) 80%PW+10%A+10%S (PW80+A10+S10) and 7) 60%PW + 20%A + 20%S (PW40+A20+S20). The lowest dry matter content was observed in PW group (39.0 g/kg). The crude protein ratio in the alfalfa groups were higher than those of S and PW groups. The crude cellulose was lower and NDF higher in the PW group than those of other groups and ADF was highest in the 40%S group. Water soluble carbohydrate ratio in PW and PW60+A20+S20 groups were higher than those of other groups. In the PW group, the lactic acid ratio was higher than PW80+S10+A10 group. In the PW80+S20 group the highest gas production was observed at 48th, 72nd and 96th hours. The energy values of PW group were higher than those of other groups. The aerobic stability of pumpkin silage was improved with hay addition especially alfalfa addition in 400 g/kg concentration.
Preparing for a Community-Based Agriculture-to-Nutrition Trial in Rural Malawi: Formative Research to Assess Feasibility and Inform Design and Implementation Decisions
Authors: Chiutsi-Phiri Gabriella , Kalimbira Alexander , Banda Leonard , Nalivata Patson , Sanuka Marion , Kalumikiza Zione , Matandika Limbanazo , Mfutso-Bengo Joseph , Allen Elizabeth , Ferguson Elaine , Sturgess Joanna , Broadley Martin , Langley-Evans Simon , Millar Kate , Gashu Dawd , Joy Edward 
Published: June 2021

Abstract
Background This study reports findings from formative research conducted to assess the feasibility and inform the design and implementation of the Addressing Hidden Hunger with Agronomy (AHHA) trial. The AHHA trial was a randomised, controlled trial conducted in rural Malawi, in which participants were given maize flour biofortified with selenium or control flour not biofortified with selenium for a period of 12 weeks, after which blood samples were taken to measure selenium status. Methods Formative research was conducted in villages near to the AHHA trial study site one year before the planned intervention. A short questionnaire with adult women (n=50), Focus Group Discussions with male (n groups=3) and female (n groups=3) community members, and in-depth Key Informant Interviews (KIIs; n=7) were conducted to understand community practices and perceptions. Findings Meals were typically cooked and eaten at home in this community, while participants reported that maize flour would be less readily sold than maize grain – important considerations for the design of the trial. Regarding intervention delivery, we identified potential concerns around effects on fertility, links between blood sampling and witchcraft, and the potential for social stigma if community members considered participants lazy for receiving free flour. Participants reported that involvement of the Malawi government partners including health extension workers would increase trust. Interpretation Following the formative research, the AHHA trial appeared feasible. However, community sensitisation would be essential to address potential fears and concerns; effective sensitisation would support recruitment and treatment adherence, and would protect the safety and wellbeing of participants and researchers. People in positions of authority and trust including village headmen, religious leaders, health and agriculture extension workers, and community care groups should be involved in community sensitisation.
Automatic road sign detection and recognition based on neural network
Authors: Lahmyed Redouan , Ansari Mohamed El , Kerkaou Zakaria 
Published: June 2021

Abstract
Road sign detection and recognition is an integral part of intelligent transportation sys-tems (ITS). It increases protection by reminding the driver of the current condition of the route, such as notices, bans, limitations and other valuable driving information. This paper describes a novel system for automatic detection and recognition of road signs, which is achieved in two main steps. First, the initial image is pre-processed using DBSCAN clustering algorithm. The clustering is performed based on color information, and the generated clusters are segmented using Artiﬁcial neural networks (ANN) classiﬁer. The resulting ROIs are then carried out based on their aspect ratio and size to retain only signiﬁcant ones. Then, a shape-based classiﬁcation is performed using ANN as classiﬁer and HDSO as feature to detect the circular, rectangular and triangular shapes. Second, a hybrid feature is deﬁned to recognize the ROIs detected from the ﬁrst step. It involves a combination of the so-called GLBP-Color which is an extension of the classical gradient local binary patterns (GLPB) feature to the RGB color space and the local self-similarity (LSS) feature. ANN, Adaboost and support vector machine (SVM) have been tested with the introduced hybrid feature and the ﬁrst one is selected as it outperforms the other two. The proposed method has been tested in outdoor scenes, using a collection of common databasets, well known in the traﬃc sign community (GTSRB, GTSDB and STS). The results demonstrate the eﬀectiveness of our method when compared to recent state-of-the-art methods.
Multi-Objective Spider Monkey Optimization for Energy Efficient clustering and Routing in wireless sensor networks
Authors: Samiayya Duraimurugan , Ramalingam Avudaiammal 
Published: June 2021

Abstract
In wireless sensor network (WSN), the gateways far away from the base station (BS) uses the gateways nearer to the BS to forward the data. It causes heavy traffic to the gateways in proximity with the BS. They need to manage this heavy traffic load but it leads to additional energy consumption and reduction in network lifetime. In order to overcome these issues, loads around the gateways need to be balanced. In this paper, multi objective based spider monkey optimization (MOSMO) has been presented to balance the load and to improve the network lifetime through energy efficient routing and clustering. The objective functions such as routing fitness and clustering fitness have been considered for optimal routing and clustering. The routing fitness function is found by incorporating both the minimum distance traversed by the gateways and minimum number of the gateway hops. The clustering fitness function is the minimum fitness function of gateways. The fitness function of each gateway is computed based on both the mean load of gateways as well as the distance between gateways and BS. The performance of the proposed MOSMO based routing and clustering scheme is compared with the existing Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) based routing and clustering scheme. The QoS features such as delay, energy consumption, delivery ratio, throughput and network lifetime with various node density are analyzed. The proposed work is simulated using MATLAB. The results show that, the reduction in delay and energy consumption is about 18% and 17% respectively whereas improvement in delivery ratio, throughput and network life time is about 15%, 24% and 19% respectively when compared to the existing PSO and GWO methods.
Use of Cone Beam Computed Tomography in the Differential Diagnosis of Jaw Bone Lesions
Authors: Carneiro Mailon Cury , Tolentino Elen de Souza , Aquaroni Lorena Borgononi , Huayhua Milenka Gabriela Quenta , Orcina Bernardo da Fonseca , Reia Verônica Caroline Brito , Rubira-Bullen Izabel Regina Fischer 
Published: June 2021

Abstract
Background/Objective: This study aims to describe in detail the characteristics of the different jaw bone lesions seen in cone beam computed tomography examinations, from a retrospective analysis. Methods: All the preoperative examinations of cone beam computed tomography of intraosseous lesions of the jaws were retrospectively reviewed from patients treated at the Department of Stomatology of a Brazilian University, from 2008 to 2017. The following data were collected: sex, age, location, density and size of the lesion, relation to an unerupted tooth, margins, cortical and/or perforation, tooth displacement, root resorption, presence of calcifications, and proximity to anatomical structures. Fisher's exact test was used to verify associations between the variables. Results: We identified 28 lesions, all of which were benign: 14 odontogenic keratocysts, 5 odontomas, 3 dentigerous cysts, 2 ameloblastomas, 1 ameloblastic fibro-odontoma, 1 cementoblastoma, 1 adenomatoid odontogenic tumour, and 1 calcifying epithelial odontogenic cyst. Of these lesions, 23 affected the mandible, and 5 the maxilla. The lesions were subdivided into aggressive and non-aggressive, and when compared, there was a difference only for the cortical cone perforation variable (p <0.05), which was more prevalent in aggressive lesions, suggesting that this characteristic is an important indicator of pathological behaviour. Conclusions: An accurate identification of the characteristics of bone lesions of the buccomaxillofacial complex, using cone beam computed tomography, can guide diagnostic hypotheses, in addition to guiding the management, thus, providing a more appropriate treatment for each individualized case.
Accumulation of Potentially Toxic Trace Elements (PTEs) by Native Plant Species Growing in a Typical Gold Mining Area Located in the Northeast of Qinghai-Tibet Plateau
Authors: Wang Lei , Xie Xiaorong , Li Qifeng , Yu Zhifeng , Hu Guangde , Wang Xixi , Liu Jinrong 
Published: June 2021

Abstract
Though gold mines provide significant economic benefits to local governments, mining causes soil pollution by potentially toxic trace elements (PTEs) in mining areas, especially in the Qinghai-Tibet Plateau. Screening of native plant species from mining areas is now an effective, inexpensive, and eco-friendly method for the remediation of PTEs in situ. In the present study, we conducted experiments to assess the accumulation of As, Cd, Pb, and Zn in 12 native plant species growing on a typical gold mining area in Qinghai-Tibet Plateau. Our results showed that rhizosphere soils have high soil organic matter content, high levels of As, and moderate levels of Cd. G. pylzowianum accumulated relatively higher As in its shoots and exhibited TF higher than 1 for As (4.65), Cd (1.87), and Pb (1.36). P. saundersiana had BCF-S higher than 1 for Cd (4.52) and Pb (1.70), whereas its TF was higher than 1 for As, Cd, Pb, and Zn. These plant species also exhibit strong tolerance to these PTEs. Furthermore, E. nutans accumulated low levels of As, Cd, Pb, and Zn in their shoots and exhibited TF values lower than 1 for the four PTEs. Therefore, G. pylzowianum could be used for the in situ phytoextraction of As, and P. saundersiana can be used as an effective plant for Cd and Pb phytoextraction. E. nutans is better suited for the phytostabilisation of multiple PTEs. Our study is of significant importance for introducing native plant species to remediate PTE-contaminated soils, particularly As and Cd, and has a good potential for developing PTE phytoremediation strategies at mining sites.
Digital footprints´ wrangling – Are analytics used for better or worse?: Evidence of Danish data governance practices on tech-based services
Authors: Abrantes Bruno F. , Ostergaard Klaus 
Published: June 2021

Abstract
Incumbents face nowadays one of their great data governance challenges, regarding the balancing of Big Data´s utilization and the imperative of uplifting the consumer´s sentiment. In the context of the European Union (EU), the prior is especially applicable as a growing opposition against the allegedly hazardous commercial exploitation of digital footprints is ascribed to distort information bundles to the consumer and gradually bias their individual capacity to take informed free choices, configuring a phenomenon of concealed “data autocracy”. Yet, this occurs despite the introduction on May-18 of the General Data Protection Regulation (GDPR).Hence, we have conducted a multi-methods enquire with foci on the Danish market covering the footprint´s awareness and undertaking´s rationale targeting equidistantly the data-owners and data-brokers. This was fashioned with a descriptive-exploratory research purpose to enlighten both the sentiment (perceptions) and the behaviour (actions) and determine the extent of (un)willingness surrounding the dataveillance over personal lives (and firm´s quotidian) and their coherence with regard to self-protection. A dyad of triangulation procedures were applied then for validation purposes and extending our findings.The results of the empirical testing confirmed the most marked disruption of Big Data at individual-level as to the range of benefits and drawbacks. A gap (perception versus action) acknowledged on the two parties uncovered a (paradoxical) laissez-faire of data-owners and institutional isomorphism of data-brokers, and the need for capability building and for the government authorities´ intervention, re-conceptualizing scope and boundaries of collection securitization for building a far more efficient model against citizen´s rights usurpation.JEL: M15; M31; M38.