bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a robust real-time synchronized data transmission technique from a Magnetic Observatory to an INTERMAGNET GIN
Authors: Potharaju Sai Vijay Kumar , Nelapatla Phani Chandrasekhar 
Published: June 2022

AbstractThis paper presents the step-by-step development and implementation of real-time data transmission from a distant Observatory. Using Python programming language, we have developed an algorithm for automated data transmission of high resolution real-time magnetic data from Choutuppal (CPL) and Hyderabad (HYB), India to INTERMAGNET Edinburgh GIN, with minimal internet services. We have designed a system to transfer the data in a secured and encrypted pattern with SSH keys and save the same dataset in the local server at CSIR-NGRI. Both the Observatories data are transmitted to GIN in real-time with a time frame of less than 300 s. After successfully transmitting real-time 1 min geomagnetic data from CPL and HYB Observatories to Edinburgh GIN, CPL's 1 s real-time data is also initiated and is one of the first Indian observatories to transmit real-time 1 s data to GIN. The details of algorithm development, function libraries and the challenges faced for 1 s and 1 min data transmission at both the Observatories are discussed.
Nanoscale defect evaluation framework combining real-time transmission electron microscopy and integrated machine learning-particle filter estimation
Authors: Sasaki K. , Muramatsu M. , Hirayama K. , Endo K. , Murayama M. 
Published: June 2022

AbstractObservation of dynamic processes by transmission electron microscopy (TEM) is an attractive technique to experimentally analyze materials’ nanoscale phenomena and understand the microstructure-properties relationships in nanoscale. Even if spatial and temporal resolutions of real-time TEM increase significantly, it is still difficult to say that the researchers quantitatively evaluate the dynamic behavior of defects. Images in TEM video are a two-dimensional projection of three-dimensional space phenomena, thus missing information must be existed that makes image’s uniquely accurate interpretation challenging. Therefore, even though they are still a clustering high-dimensional data and can be compressed to two-dimensional, conventional statistical methods for analyzing images may not be powerful enough to track nanoscale behavior by removing various artifacts associated with experiment; and automated and unbiased processing tools for such big-data are becoming mission-critical to discover knowledge about unforeseen behavior. We have developed a method to quantitative image analysis framework to resolve these problems, in which machine learning and particle filter estimation are uniquely combined. The quantitative and automated measurement of the dislocation velocity in an Fe-31Mn-3Al-3Si autunitic steel subjected to the tensile deformation was performed to validate the framework, and an intermittent motion of the dislocations was quantitatively analyzed. The framework is successfully classifying, identifying and tracking nanoscale objects; these are not able to be accurately implemented by the conventional mean-path based analysis.
Machine learning methods to predict attrition in a population-based cohort of very preterm infants
Authors: Teixeira Raquel , Rodrigues Carina , Moreira Carla , Barros Henrique , Camacho Rui 
Published: June 2022

AbstractThe timely identification of cohort participants at higher risk for attrition is important to earlier interventions and efficient use of research resources. Machine learning may have advantages over the conventional approaches to improve discrimination by analysing complex interactions among predictors. We developed predictive models of attrition applying a conventional regression model and different machine learning methods. A total of 542 very preterm (< 32 gestational weeks) infants born in Portugal as part of the European Effective Perinatal Intensive Care in Europe (EPICE) cohort were included. We tested a model with a fixed number of predictors (Baseline) and a second with a dynamic number of variables added from each follow-up (Incremental). Eight classification methods were applied: AdaBoost, Artificial Neural Networks, Functional Trees, J48, J48Consolidated, K-Nearest Neighbours, Random Forest and Logistic Regression. Performance was compared using AUC- PR (Area Under the Curve—Precision Recall), Accuracy, Sensitivity and F-measure. Attrition at the four follow-ups were, respectively: 16%, 25%, 13% and 17%. Both models demonstrated good predictive performance, AUC-PR ranging between 69 and 94.1 in Baseline and from 72.5 to 97.1 in Incremental model. Of the whole set of methods, Random Forest presented the best performance at all follow-ups [AUC-PR1: 94.1 (2.0); AUC-PR2: 91.2 (1.2); AUC-PR3: 97.1 (1.0); AUC-PR4: 96.5 (1.7)]. Logistic Regression performed well below Random Forest. The top-ranked predictors were common for both models in all follow-ups: birthweight, gestational age, maternal age, and length of hospital stay. Random Forest presented the highest capacity for prediction and provided interpretable predictors. Researchers involved in cohorts can benefit from our robust models to prepare for and prevent loss to follow-up by directing efforts toward individuals at higher risk.
Bespoke magnetic field design for a magnetically shielded cold atom interferometer
Authors: Hobson P. J. , Vovrosh J. , Stray B. , Packer M. , Winch J. , Holmes N. , Hayati F. , McGovern K. , Bowtell R. , Brookes M. J. , Bongs K. , Fromhold T. M. , Holynski M. 
Published: June 2022

AbstractQuantum sensors based on cold atoms are being developed which produce measurements of unprecedented accuracy. Due to shifts in atomic energy levels, quantum sensors often have stringent requirements on their internal magnetic field environment. Typically, background magnetic fields are attenuated using high permeability magnetic shielding, with the cancelling of residual and introduction of quantisation fields implemented with coils inside the shield. The high permeability shield, however, distorts all magnetic fields, including those generated inside the sensor. Here, we demonstrate a solution by designing multiple coils overlaid on a 3D-printed former to generate three uniform and three constant linear gradient magnetic fields inside the capped cylindrical magnetic shield of a cold atom interferometer. The fields are characterised in-situ and match their desired forms to high accuracy. For example, the uniform transverse field, Bx, deviates by less than 0.2% over more than 40% of the length of the shield. We also map the field directly using the cold atoms and investigate the potential of the coil system to reduce bias from the quadratic Zeeman effect. This coil design technology enables targeted field compensation over large spatial volumes and has the potential to reduce systematic shifts and noise in numerous cold atom systems.
Characterization of Stenotrophomonas maltophilia phage AXL1 as a member of the genus Pamexvirus encoding resistance to trimethoprim–sulfamethoxazole
Authors: McCutcheon Jaclyn G. , Lin Andrea , Dennis Jonathan J. 
Published: June 2022

AbstractStenotrophomonas maltophilia is a ubiquitous environmental bacterium capable of causing disease in humans. Antibiotics are largely ineffective against this pathogen due to numerous chromosomally encoded antibiotic resistance mechanisms. An alternative treatment option is phage therapy, the use of bacteriophages to selectively kill target bacteria that are causing infection. To this aim, we isolated the Siphoviridae bacteriophage AXL1 (vB_SmaS-AXL_1) from soil and herein describe its characterization. Host range analysis on a panel of 30 clinical S. maltophilia strains reveals a moderate tropism that includes cross-species infection of Xanthomonas, with AXL1 using the type IV pilus as its host surface receptor for infection. Complete genome sequencing and analysis revealed a 63,962 bp genome encoding 83 putative proteins. Comparative genomics place AXL1 in the genus Pamexvirus, along with seven other phages that infect one of Stenotrophomonas, Pseudomonas or Xanthomonas species. Functional genomic analyses identified an AXL1-encoded dihydrofolate reductase enzyme that provides additional resistance to the antibiotic combination trimethoprim–sulfamethoxazole, the current recommended treatment option for S. maltophilia infections. This research characterizes the sixth type IV pilus-binding phage of S. maltophilia and is an example of phage-encoded antibiotic resistance.
Reputation structure in indirect reciprocity under noisy and private assessment
Authors: Fujimoto Yuma , Ohtsuki Hisashi 
Published: June 2022

AbstractEvaluation relationships are pivotal for maintaining a cooperative society. A formation of the evaluation relationships has been discussed in terms of indirect reciprocity, by modeling dynamics of good or bad reputations among individuals. Recently, a situation that individuals independently evaluate others with errors (i.e., noisy and private reputation) is considered, where the reputation structure (from what proportion of individuals in the population each receives good reputations, defined as goodness here) becomes complex, and thus has been studied mainly with numerical simulations. The present study gives a theoretical analysis of such complex reputation structure. We formulate the time change of goodness of individuals caused by updates of reputations among individuals. By considering a large population, we derive dynamics of the frequency distribution of goodnesses. An equilibrium state of the dynamics is approximated by a summation of Gaussian functions. We demonstrate that the theoretical solution well fits the numerical calculation. From the theoretical solution, we obtain a new interpretation of the complex reputation structure. This study provides a novel mathematical basis for cutting-edge studies on indirect reciprocity.
Comparative genomic analysis of Streptomyces rapamycinicus NRRL 5491 and its mutant overproducing rapamycin
Authors: Jo Hee-Geun , Adidjaja Joshua Julio , Kim Do-Kyung , Park Bu-Soo , Lee Namil , Cho Byung-Kwan , Kim Hyun Uk , Oh Min-Kyu 
Published: June 2022

AbstractStreptomyces rapamycinicus NRRL 5491 is a well-known producer of rapamycin, a secondary metabolite with useful bioactivities, including antifungal, antitumor, and immunosuppressive functions. For the enhanced rapamycin production, a rapamycin-overproducing strain SRMK07 was previously obtained as a result of random mutagenesis. To identify genomic changes that allowed the SRMK07 strain’s enhanced rapamycin production, genomes of the NRRL 5491 and SRMK07 strains were newly sequenced in this study. The resulting genome sequences of the wild-type and SRMK07 strains showed the size of 12.47 Mbp and 9.56 Mbp, respectively. Large deletions were observed at both end regions of the SRMK07 strain’s genome, which cover 17 biosynthetic gene clusters (BGCs) encoding secondary metabolites. Also, genes in a genomic region containing the rapamycin BGC were shown to be duplicated. Finally, comparative metabolic network analysis using these two strains’ genome-scale metabolic models revealed biochemical reactions with different metabolic fluxes, which were all associated with NADPH generation. Taken together, the genomic and computational approaches undertaken in this study suggest biological clues for the enhanced rapamycin production of the SRMK07 strain. These clues can also serve as a basis for systematic engineering of a production host for further enhanced rapamycin production.
Determination of sequence and absolute configuration of peptide amino acids by HPLC–MS/CD-based detection of liberated N-terminus phenylthiohydantoin amino acids
Authors: Hahn Dongyup , Wang Weihong , Choi Hyukjae , Kang Heonjoong 
Published: June 2022

AbstractWe report a method for the simultaneous determination of the sequence and absolute configuration of peptide amino acids using a combination of Edman degradation and HPLC–MS/CD. Phenylthiohydantoin (PTH) derivatives of 20 pairs of standard d- and l-amino acids were synthesized by the Edman reaction. The CD spectra of the derivatives revealed that each pair of the PTH derivatives exhibited the absorption with opposite signs at around 270 nm. These standard PTH derivatives showed well-resolved resolution without interference from byproducts in the ion chromatogram and clear positive/negative CD absorptions when subjected on a reversed phase HPLC–MS system coupled with a CD-2095 HPLC detector. This method was applied for the detection of a synthetic pentapeptide and a natural depsipeptide (halicylindramide C). The sequence and configuration of the pentapeptide and up to eight residues of halicylindramide C were successfully analyzed by this method. The amino acid configuration of the pentapeptide was also determined successfully by subjecting its acid hydrolysates to the Edman reaction followed by HPLC–MS/CD.
A hybrid optimization with ensemble learning to ensure VANET network stability based on performance analysis
Authors: Marwah Gagan Preet Kour , Jain Anuj 
Published: June 2022

AbstractHigh vehicle mobility, changing vehicle density and dynamic inter-vehicle spacing are all important issues in the VANET environment. As a result, a better routing protocol improves VANET overall performance by permitting frequent service availability. Therefore, an ensemble-based machine-learning technique is used to forecast VANET mobility. Effective routing based on a hybrid metaheuristic algorithm combined with Ensemble Learning yields significantly improved results. Based on information collected from the Road Side Unit (RSU) or the Base Station, a hybrid metaheuristic (Seagull optimization and Artificial Fish Swarm Optimization) method is used to estimate (BS). The suggested approach incorporates an ensemble machine learning and hybrid metaheuristic method to reduce the latency. The current model's execution is calculated using a variety of Machine Learning techniques, including SVM, Nave Bayes, ANN, and Decision Tree. As a result, the performance of machine learning algorithms may be studied and used to achieve the best results. Comparative analysis between the proposed method (HFSA-VANET) and (CRSM-VANET was done on different performance parameters like throughput, delay, drop, network lifetime, and energy consumption to assess system performance on two factors Speed and Nodes. The HFSA-VANET method shows an overall drop in the delay of 33% and a decrease in the energy consumption of 81% and an increase of 8% in the throughput as compared with the CRSM-VANET method at 80 node. The proposed method that is HFSA-VANET has been implemented in the MATLAB and NS2 environment.
Green synthesis of gold nanoparticles in Gum Arabic using pulsed laser ablation for CT imaging
Authors: Mzwd Elham , Ahmed Naser M. , Suradi Nursakinah , Alsaee Saleh K. , Altowyan Abeer S. , Almessiere Munirah A. , Omar Ahmad Fairuz 
Published: June 2022

AbstractLaser ablation synthesis in liquid solution (PLAL) is a green technique that allows for the physical formation of nanomaterials. This study indicates the preparation of stable gold nanoparticles (AuNPs) in Gum Arabic (GA) solution via laser ablation as a CT contrast agent. The optical properties were achieved using the absorption spectroscopic technique whereas the morphology and size distribution were investigated by TEM and ImageJ software. TEM image shows greater stability and spherical shape of GA-AuNPs with smaller size at 1.85 ± 0.99 nm compared to AuNPs without GA. The absorption spectrum of pure AuNPs has a lower absorption peak height in the visible range at λ = 521 nm, while the spectrum of GA-AuNPs has a higher plasmon peak height at λ = 514 nm with a blue shift towards lower wavelengths. The concentration of GA that dissolved in 10 mL of DI water via laser ablation is set at 20 mg. Increasing the number of pulses has only a minor effect on particle size distribution, which remains tiny in the nanometer range (less than 3 nm). For energies greater than 200 mJ, there is a blue shift toward shorter wavelengths. As the concentration of GA-AuNPs increases, the CT number is also increased indicating good image contrast. It can be concluded that there is a positive and significant influence of GA as a reducing agent for AuNPs, and a contrast agent for CT imaging which highlights its superiority in future medical applications.
Fabrication of eco-friendly graphene-based superhydrophobic coating on steel substrate and its corrosion resistance, chemical and mechanical stability
Authors: Mohamed M. E. , Ezzat A. , Abdel-Gaber A. M. 
Published: June 2022

AbstractSuperhydrophobic coatings were successfully fabricated on steel substrates using potentiostatic electrodeposition of Ni and Ni-graphene, Ni-G, coatings followed by immersion in an ethanolic solution of stearic acid, SA. Rice straw, an environmentally friendly biomass resource, was used to synthesize high-quality graphene. The Raman spectra proved the high quality of the produced graphene. The Fourier transform infrared spectroscopy, FTIR, results showed that the Ni coating grafted with stearic acid, Ni-SA, and the Ni-G composite grafted with stearic acid, Ni-G-SA, were successfully deposited on the steel substrate. The scanning electron microscope, SEM, results showed that the prepared superhydrophobic coatings exhibit micro-nano structures. The wettability results revealed that the values of contact angles, CAs, for Ni-SA and Ni-G-SA coatings are 155.7° and 161.4°, while the values of sliding angles, SAs, for both coatings are 4.0° and 1.0°, respectively. The corrosion resistance, chemical stability, and mechanical abrasion resistance of the Ni-G-SA coating were found to be greater than those of the Ni-SA coating.
Polyphenols from persimmon fruit attenuate acetaldehyde-induced DNA double-strand breaks by scavenging acetaldehyde
Authors: Matsuzaki Kenichiro , Kumatoriya Kenji , Tando Mizuki , Kometani Takashi , Shinohara Miki 
Published: June 2022

AbstractAcetaldehyde, a metabolic product of ethanol, induces DNA damage and genome instability. Accumulation of acetaldehyde due to alcohol consumption or aldehyde dehydrogenase (ALDH2) deficiency increases the risks of various types of cancers, including esophageal cancer. Although acetaldehyde chemically induces DNA adducts, the repair process of the lesions remains unclear. To investigate the mechanism of repair of acetaldehyde-induced DNA damage, we determined the repair pathway using siRNA knockdown and immunofluorescence assays of repair factors. Herein, we report that acetaldehyde induces DNA double-strand breaks (DSBs) in human U2OS cells and that both DSB repair pathways, non-homologous end-joining (NHEJ) and homology-directed repair (HDR), are required for the repair of acetaldehyde-induced DNA damage. Our findings suggest that acetaldehyde-induced DNA adducts are converted into DSBs and repaired via NHEJ or HDR in human cells. To reduce the risk of acetaldehyde-associated carcinogenesis, we investigated potential strategies of reducing acetaldehyde-induced DNA damage. We report that polyphenols extracted from persimmon fruits and epigallocatechin, a major component of persimmon polyphenols, attenuate acetaldehyde-induced DNA damage without affecting the repair kinetics. The data suggest that persimmon polyphenols suppress DSB formation by scavenging acetaldehyde. Persimmon polyphenols can potentially inhibit carcinogenesis following alcohol consumption.
Biochemical characterization of Soxhlet-extracted pulp oil of Canarium schweinfurthii Engl. fruit in Nigeria
Authors: Omeje Kingsley O. , Ezema Benjamin O. , Ozioko Juliet N. , Omeje Henry C. , Ossai Emmanuel C. , Eze Sabinus O. O. , Okpala Charles Odilichukwu R. , Korzeniowska Małgorzata 
Published: June 2022

AbstractCharacterization and further development of underutilized/underexploited indigenous tropical seed oils are essential to supplement both nutritional and industrial needs of an ever-increasing African (and global) population. Before now and to our best knowledge, the previous research involved Canarium schweinfurthii Engl. fruit specific to Nigeria appear to have been more on the evaluation of seed, pulp, and essential oils (from the seed), but much less on the pulp oil. To supplement existing information, this current work has aimed to biochemically characterize the Soxhlet-extracted pulp oil of C. schweinfurthii fruit gathered from a community situated in the South-east of Nigeria. Specifically, the biochemical characterization comprised the determinations of proximate compositions, lipid peroxidation, fatty acid profile, as well as carotenoids, sterols, and tocopherols. Processing the fruit sample to pulp oil involved, among others, oven-drying, and grinding, prior to the Soxhlet extraction. Results of proximate components of C. schweinfurthii pulp oil showed the following trend: crude fat content (~ 49.32%) > carbohydrates (~ 37.93%) > moisture content (~ 8.62%) > ash content (~ 3.74%) > crude protein content (~ 0.39%) values. The lipid peroxidation attributes comprised acid (~ 23.60 mg KOH/g), peroxide (~ 33.91 mEq. O2/kg), iodine (~ 58.3 g/100 g), and saponification (~ 138.21 mg KOH/g) values. In addition to the free (~ 13.8%), saturated (~ 9.74%), and unsaturated (~ 90.26%) fatty acids, a total of fifteen (15) fatty acid methyl esters (FAMEs) spectral peaks were found, from caprylic acid (C8:0) to lignoceric acid (C24:0). Total tocopherol concentration amounted to ~ 73 mg/100 g, which comprised α, β, γ-tocopherol, and δ-tocotrienol, with fair concentrations of carotenoids and sterols. Overall, the C. schweinfurthii pulp oil—biochemically competitive with a high concentration of unsaturated fatty acid, tocopherol, and sterol, suggests strong industrial promise.
A transcriptomic signature for prostate cancer relapse prediction identified from the differentially expressed genes between TP53 mutant and wild-type tumors
Authors: Zhang Wensheng , Zhang Kun 
Published: June 2022

AbstractFor prostate cancer (PCa) patients, biochemical recurrence (BCR) is the first sign of disease relapse and the subsequent metastasis. TP53 mutations are relatively prevalent in advanced PCa forms. We aimed to utilize this knowledge to identify robust transcriptomic signatures for BCR prediction in patients with Gleason score ≥ 7 cancers, which cause most PCa deaths. Using the TCGA-PRAD dataset and the novel data-driven stochastic approach proposed in this study, we identified a 25-gene signature from the genes whose expression in tumors was associated with TP53 mutation statuses. The predictive strength of the signature was assessed by AUC and Fisher’s exact test p-value according to the output of support vector machine-based cross validation. For the TCGA-PRAD dataset, the AUC and p-value were 0.837 and 5 × 10–13, respectively. For five external datasets, the AUCs and p-values ranged from 0.632 to 0.794 and 6 × 10–2 to 5 × 10–5, respectively. The signature also performed well in predicting relapse-free survival (RFS). The signature-based transcriptomic risk scores (TRS) explained 28.2% of variation in RFS on average. The combination of TRS and clinicopathologic prognostic factors explained 23–72% of variation in RFS, with a median of 54.5%. Our method and findings are useful for developing new prognostic tools in PCa and other cancers.