bluuebunny/crossref_metadata_2025 huggingface dataset:
Upscaling HIV and hepatitis C testing in primary healthcare settings: stigma-sensitive practice
Authors: Lenton Emily , Johnson Jen , Brown Graham
Published: June 2021

Increasing testing for viral hepatitis and HIV is central to meeting World Health Organization and Australian targets to eliminate blood-borne viruses as public health priorities by 2030. In this paper we draw on findings and recommendations from a Victorian consultation with 40 health and community practitioners engaged with blood-borne virus testing. The consultation focused on identifying what constitutes best practice in pre- and post-testing discussion in the current era of highly effective treatments for HIV and hepatitis C. Overall, the consultation found that the pre- and post-test discussion remains an important feature of testing, but, given that stigma continues to impact the lives of people affected by these viruses, sensitivity to this issue needs to inform how these discussions take place. We describe how primary healthcare settings can support the goal of upscaling HIV and hepatitis C testing in a way that delivers safe and stigma-free testing encounters. We offer the notion of ‘stigma-sensitive practice’ as a term to describe this approach to pre- and post-test discussions.
Investigation of multi-layered graphene/silicon Schottky junction in oxidizing atmosphere
Authors: Ricciardella Filiberto , Nigro Maria Arcangela , Miscioscia Riccardo , Miglietta Maria Lucia , Polichetti Tiziana
Published: June 2021

In this study, we investigate a Schottky junction based on solution-processed multilayered graphene (MLG). We present a rectifying device obtained with a straightforward approach, that is drop-casting a few microliters of MLG solution simultaneously onto Si, Si–SiO2 and Si–SiO2–Cr/Au surface. Monitoring the modulation of Schottky barrier height while operating in reverse bias, we study the behavior of such prepared MLG-Si/junction (MLG-Si/J) when exposed to oxidizing atmosphere, especially to nitrogen oxide (NO2). We finally compare the sensing behavior of MLG-Si/J at 1 ppm of NO2 with that of a chemiresistor-based on similarly prepared solution-processed MLG. Our study thus opens the path towards low-cost highly sensitive graphene-based heterojunctions advantageously fabricated without any complexity in the technological process.
Detecting the relativistic bispectrum in 21cm intensity maps
Authors: Jolicoeur Sheean , Maartens Roy , De Weerd Eline M. , Umeh Obinna , Clarkson Chris , Camera Stefano
Published: June 2021

We investigate the detectability of leading-order relativistic effects in the bispectrum of future 21cm intensity mapping surveys. The relativistic signal arises from Doppler and other line-of-sight effects in redshift space. In the power spectrum of a single tracer, these effects are suppressed by a factor
ℋ2/k2. By contrast, in the bispectrum the relativistic signal couples to short-scale modes, leading to
an imaginary contribution that scales as
ℋ/k, thus increasing the possibility of detection.
Previous work has shown that this relativistic signal is detectable in a Stage IV Hα galaxy survey.
We show that the signal is also detectable by next-generation 21cm intensity maps, but typically with a lower signal-to-noise, due to foreground and telescope beam effects.
A study of beam ion and deuterium–deuterium fusion-born triton transports due to energetic particle-driven magnetohydrodynamic instability in the large helical device deuterium plasmas
Authors: Ogawa K. , Isobe M. , Nuga H. , Kamio S. , Fujiwara Y. , Kobayashi M.I. , Sangaroon S. , Takada E. , Seki R. , Yamaguchi H. , Murakami S. , Jo J. , Osakabe M.
Published: June 2021

Understanding energetic particle transport due to magnetohydrodynamic instabilities excited by energetic particles is essential to apprehend alpha particle confinement in a fusion burning plasma. In the large helical device (LHD), beam ion and deuterium–deuterium fusion-born triton transport due to resistive interchange mode destabilized by helically-trapped energetic ions (EIC) are studied employing comprehensive neutron diagnostics, such as the neutron flux monitor and a newly developed scintillating fiber detector characterized by high detection efficiency. Beam ion transport due to EIC is studied in deuterium plasmas with full deuterium or hydrogen/deuterium beam injections. The total neutron emission rate (S
n) measurement indicates that EIC induces about a 6% loss of passing transit beam ions and a 60% loss of helically-trapped ions. The loss rate of helically-trapped ions, which drive EIC, is larger than the loss rate of passing transit beam ions. Furthermore, the drop of S
n increasing linearly with the EIC amplitude shows that barely confined beam ions existing near the confinement-loss boundary are lost due to EIC. In full deuterium conditions, a study of deuterium–deuterium fusion-born triton transport due to EIC is performed by time-resolved measurement of total secondary deuterium–tritium neutron emission rate (S
n_DT). Drop of S
n_DT increases substantially with EIC amplitude to the third power and reaches up to 30%. The relation shows that not only tritons confined in confined-loss boundary, but also tritons confined in the inner region of a plasma, are substantially transported.
Based on “MOOC + SPOC” customized regional primary and secondary school teachers’ information technology application ability training strategy
Authors: Jiqiong Yang , Yue Qian
Published: June 2021

According to the research status of information technology application ability of regional primary and secondary school teachers, aiming at the subjective factors of regional primary and secondary school teachers, such as weak foundation, less free time, conflict between training time and working time, and the lack of close combination of existing training content and teaching practice, single training method and outdated content, can not meet the different needs of different teachers and other objective factors, put forward the “MOOC + SPOC” based on the regional primary and secondary school teachers’ information technology application ability training design, in order to use the fragment time to complete the preliminary knowledge learning and then through the flip classroom mixed mode to complete the knowledge internalization, effective training is realized through the path of evaluation and feedback to promote ability improvement.
‘Anomalies’ Visualized by Ten Years Tracking of Ph.D. Recruitment Data on JREC-IN in Japan
Authors: Hirayama Kota , Umemura Kazuo
Published: June 2021

We have accumulated retrieval data of PhD job recruitments using the JREC-IN website, which is the public jobs database in Japan. We focused on retrieval for natural science and engineering fields with five typical keywords such as ‘Chemistry’ and ‘Biology/Life science’. To continue the retrieval for ten years, a simple keyword search was demonstrated, although a more detailed analysis might be available for short-term searches. Our data revealed several anomalies. First, the ratios of non-permanent positions against permanent positions in ‘biology/life science’ fields and ’chemistry’ fields were much higher (195% and 153%) than other fields such as ‘physics’. Biologists and chemists may easily find non-permanent positions, but it is not easy to find a permanent position. Second, a clear anomaly of recruitments according to seasons in one year was observed based on the ten years’ historical data. Because the fiscal year in Japan starts in April, the number of recruitments of permanent positions was maximised in August in all fields. Then, the peak of recruitments of non-permanent positions appeared in November through February. Our work provided fundamental knowledge to understand and solve the PhD job problem in the natural science and engineering fields in Japan.
Application of the intra cluster, characteristic of k-means clustering method in English score analysis in Colleges
Authors: Wang Qin
Published: June 2021

As an important data mining method, clustering algorithm can find valuable information hidden in data objects through unsupervised classification method. It is widely used in data analysis, image segmentation, feature learning and other fields. It is one of the common methods in traditional machine learning algorithm. K-means clustering algorithm is a partition-based algorithm in clustering analysis, which is efficient and accurate, easy to implement, and is generally implemented in machine learning and other fields. In this paper, based on the characteristics of K-means clustering method, the scores of each part of 30 college students' English scores are used as the input data, and the cluster center is used as the influencing factor to participate in the clustering process. The clustering effect is evaluated under the average distance of the characteristics within the cluster after several iterations.
Refined range analysis of early warning and pre-control based on multi-element spatiotemporal clustering
Authors: Tu Min
Published: June 2021

There are three parts in public security big data analysis when early warning and pre-control oriented: refined analysis scope, visualization of temporal and spatial characteristics of analysis scope, and subspace emergency analysis model for early warning and controlling. These three parts are interrelated, and complete the early warning and pre-control analysis of emergency iteratively. The exploration method of refined analysis range is analysed in the paper, which is based on the calculation and comparison of multi-element spatiotemporal clustering results. This research adopts a grid division strategy to convert heterogeneous data into a normalized space-time grid, in order to improve the versatility of the framework. And the estimation of grid records without observed values using kernel density estimation method. The added clustering ensemble is to improve the stability of clustering results. It can avoid the influence of uncertain factors on the clustering results, as well as improving the real-time performance of clustering algorithm, by the optimization of clustering ensemble parameters, and the clustering ensemble deployed on Hadoop platform.
An optimal algorithm analysis of signal transitive random signal without noise feedback
Authors: Xiao Xiaonan
Published: June 2021

This article used the way of stochastic processes statistics to raise and study a kind of optimization of signal transitive stochasic system without noise feedback, and it did the optimum operation to permit coding function of the signal and solved the measuring question of the optimum coding and decoding of the signal. It could contributs an ideal way of mathematical.
Classification and analysis of literary works based on distribution weighted term frequency-inverse document frequency
Authors: Dai Wei
Published: June 2021

Term Frequency-Inverse Document Frequency (TF-IDF) is a commonly used data mining weighting technology for information retrieval. It can evaluate the importance of a word to a text and is widely used in Internet search engines. In order to improve the text analysis ability of different text types, a variety of weighting algorithms of TF-IDF have been developed. For the word analysis of literary works of various genres, this paper adopts Distribution Weighted Term Frequency-Inverse Document Frequency (TF-IDF-DW), which takes the distribution of feature items within and between classes into account, and can get better screening results. In the text classification part, via the comprehensive weight value obtained by TF-IDF-DW, and the classification results are obtained by class center vector algorithm and Bayesian algorithm. Finally, the classification performance of TF-IDF-DW algorithm is evaluated by comparison with the traditional TF-IDF method.
Application of panel data-generalized method of moments on the impact of urban output
Authors: Cong Dibei , Xia Gang , Xiang Wenjing
Published: June 2021

This article summarized the mechanism of the impact of real estate tax on city output path, on the basis of selecting the Chinese provincial panel data from 2005 to 2019, by using the PD - GMM method. The real estate tax was taken as the core explanation variable, and was added a lot of control variables to establish the impact of real estate tax on city output 7 panel data models. We estimated and analyzed the robustness through Eviews software. Research results showed that: (1) from the national level, the real estate industry tax would have a significant effect on urban output, and there is a "U" shaped relationship between the output and the real estate tax and cities. At the beginning of the urban development, the city real estate tax inhibited output, when the urban economy was in the period of high quality development. The real estate tax on urban output result, had obvious function. (2) At the regional level, the real estate tax in the eastern region had a negative inhibitory effect on the urban revenue, while the real estate tax in the western region had a significant promoting effect on the urban revenue, and the influence degree was shown as the eastern>western>middle. (3) The more real estate investment and human capital are tilted to the west, the more favorable the development of the western region, while the impact on the eastern and central regions was not significant.
Research on thermal imaging fault detection system based on weibull distributed electrical system
Authors: Pang Jiamao , Yu Zhimin , Chen Xiangguang
Published: June 2021

A fault prediction analysis is performed In order to use infrared thermal imaging technology to detect electrical system faults, based on Weibull distribution technology. First, the principle is explained, the key technologies and factors of infrared thermal imaging and the electrical fault monitoring system are analyzed, and the available technologies are summarized. The detection process and analysis research are established with the help of on-site inspection and analysis results for power system fault analysis and research. The research shows that the method is effective for fault detection and trend analysis, and provides a reference for power fault detection and prediction analysis.
Research on the influence of radius test based on hydraulic fracturing measures
Authors: Ma Shuyin
Published: June 2021

By analyzing the mechanism of hydraulic fracturing, and the special geological conditions of a certain mine, the relevant parameters of hydraulic fracturing and increasing permeability suitable for the mine are determined through on-site fracturing pump tests. After two sets of hydraulic fracturing tests in the test areas, and compared with the original drainage parameters, the average coal seam gas drainage concentration increased by an average of 3.55, 3.65 times, and the scalar drainage increased by 3.6, 3.1 times. The average water content of coal seams increased by 1.43 times and 1.65 times. Finally, after comprehensive analysis of the borehole gas drainage concentration, gas drainage scalar and coal seam water content measured in test area 1 and test area 2, it is concluded that the influence radius of fracturing and permeability is 25~30m. It provides an effective reference for the layout of hydraulic fracturing boreholes and increasing the effect of gas drainage.
Research on brand value based on analytic hierarchy process and fuzzy comprehensive evaluation
Authors: Chen Wei , Bu Xiaona
Published: June 2021

Based on the continuous deepening of brand strategy concepts in recent years, improving brand value has become a top priority. This article uses Xingtai wild jujube as an example to use the analytic hierarchy process to evaluate the brand value of Xingtai wild jujube from four aspects: product quality, brand support, product leadership, product profitability, and its subordinates 10 indicators; and use the fuzzy comprehensive evaluation method to calculate the evaluation score of Xingtai wild jujube, draw conclusions and make suggestions for the future development of Xingtai wild jujube.
Research on radar behavior recognition method under the condition of electronic jamming
Authors: Chu Zhenyong , Xiao Nan , Liang Jun
Published: June 2021

In the course of ECM, the attacker needs to grasp the working state of the target radar by identifying its behaviors, so as to adopt the best attack strategy. Based on the correlation characteristics between nodes of the networked combat system, the proposed method processes the electromagnetic radiation parameters of the target radar and its cooperative radar, uses the support vector machine multi-classifier algorithm to identify the target radar's behaviors, and determines the influence of jamming on the radar's working states. The simulation results show that the proposed method has higher accuracy than the traditional method which only considers the target radar radiation parameters, and the selection of kernel function and electromagnetic radiation parameters are closely related to the accuracy of behavior recognition.
Research on the causes of regional differences in urban residential land incremental value based on shapley value decomposition framework
Authors: Wu Zhenhua , Yu Qinping , Wang Yabei , Bai Qinguo
Published: June 2021

This paper studied the formation mechanism of the differences of land incremental value among various regions by using the Shapley value decomposition framework. It was the first time to introduce inequality indexes to measure the differences in land incremental value in various regions, then a semi-logarithmic regression equation were constructed to determine the influencing factors, and finally the contribution of each factor was measured through the Shapley value decomposition model. The results indicated that: the regional inherent differences between cities and the differences in the residential land price per land area have a stable and strong impact on the differences in urban residential land value increment; the differences in completion value of residential buildings have a certain contribution on the expansion of regional differences in urban residential land incremental value, but they fluctuate greatly; the contribution of the differences of housing investment demand to the differences of urban residential land incremental value has gradually increased.
Risk of spillovers between the Chinese and international crude oil futures’ markets: A dynamic Copula-CoES approach
Authors: Cao Jie , Lei Lianghai , Zhang Rong , Lei Qiran
Published: June 2021

To overcome the limitations of conditional value-at-risk (CoVaR), the upside conditional expected shortfall (CoES) is proposed and used as a measure of the extreme risk spillover effect between the Chinese and international crude oil futures markets. Then, the calculation formula of the upside CoES is given under the semiparametric dynamic Copula model, which does not need to set the specific evolution equation of the Copula parameters. The empirical results show that there is a strong positive correlation between Chinese and international crude oil futures, and the correlation gradually increases when oil prices rise. There is a significant two-way risk spillover effect for both of them, and the average risk spillover intensity between Chinese crude oil futures (INE) and West Texas intermediate crude oil futures (WTI) is the highest. Moreover, INE is not always the recipient of the price fluctuation risk. In particular, INE has played the role of risk spillover most of the time after 2019. This study provides new ideas for the measurement of risk spillovers.
Quality evaluation system based on 3D-indicators-perspective model
Authors: Wang Yanan , Wang Han
Published: June 2021

The quality evaluation system is based on the perspective of owners, which integrates various resources effectively and reasonably, and evaluates the results after arrangement, reflecting the satisfaction of owners to the results of resource utilization. This paper constructs a quality evaluation system from three dimensions of profitability, security and growth. The monthly transaction data from January 2010 to December 2018 and data from 2010 to 2018 are selected as data research samples. The conclusion is that good quality needs good profitability, safety and growth. The paper also puts forward some countermeasures and suggestions for sample companies with low quality score, in order to provide effective reference.
Research on real-time simulation modeling of hybrid electric vehicle power system
Authors: Miao Zheng , Zhang Ying
Published: June 2021

This article conducts simulation research on the power plant of hybrid electric vehicles. Through the strategy and logic control of the power system, the stable operation of the engine in the economic area is realized. The engine model can express the relationship between performance and operating point more clearly, and can better meet the real-time response requirements of the system. This paper establishes Simulink-Amesim joint simulation model and conducts simulation analysis. The results show that the curve of engine torque changing with speed basically conforms to the engine principle.
Establishment and analysis of quality art-evaluation model based on BP neural network
Authors: Cui Guoling
Published: June 2021

BP is a multi-layer feedforward neural network trained by error back propagation algorithm, which is designed to mimic the structure of biological neurons. The system could solve the problem of hidden layer connection weight learning in multi-layer neural network. Based on the influence degree of investment on art education in primary and secondary schools, four input layer neurons including the number of investment fields, the type of investment fields, the popularity rate and the utilization rate were selected to build a neural network model. The average relative error between the statistical value and the predicted value was 0.15%, which could prove that the model had a high prediction accuracy and can be applied in evaluating on primary and secondary school arts education.
BPS monopoles and dyons in generalized BPS Lagrangian method
Authors: Atmaja A N
Published: June 2021

We generalize BPS Lagrangian method and rederive BPS equations for monopoles and dyons from the Lagrangian of SU(2) Maxwell-Higgs model in four dimensional spacetime. We show that in the BPS Lagrangian method the Gausss’s law constraint does not necessary to be imposed beforehand. We find that the BPS Lagrangian has non-boundary terms which in turn gives us some constraint equations. These constraint equations can be reduced by taking the standard BPS equations for Monopoles and Dyons, which turns out to be the Gausss’s law constraint in the BPS limit.
Searching for a modification of a conformally flat metric in the five-dimensional braneworld model that localizes scalar and vector fields
Authors: Rohman Muhammad Taufiqur , Triyanta
Published: June 2021

A modification of the Randall-Sundrum metric model in the form of conformally flat metric was proposed some years ago. The proposed model shows better localization properties than the original Randall-Sundrum model. However, this new model still does not meet the expectation that all fundamental fields can be localized for one type of warp factor, e.g. for a decreasing warp factor. In this research we propose to add a factor f(r) in the extra coordinate part of the above modified Randall-Sundrum metric and derive conditions for localization for scalar and vector fields. r is the extra coordinate. We then look for some functions f(r) that fulfill the localization conditions for both scalar and vector fields. Examples of the function f(r) under investigation are e
Ar, e
−Ar−Br
2
, e
−A/r
, Ar, Ar + Br
2, and sinh(Ar). We found the expected function, that is e Ar
, which might be used as a further discussion in fields localization.
Density functional theory of Ni-doped (10, 0) single-walled carbon nanotubes for C 2H 2 and C 2H 4 sensing
Authors: Yusfi M , Jonuarti R , Wungu T D K , Suprijadi
Published: June 2021

The adsorption of C 2H 2 and C 2H 4 gas molecules on Ni-doped singe-wall carbon nanotubes (Ni-SWCNT (10,0)) was investigated using Density functional theory (DFT). To discover the highest interaction energy, three Ni-SWCNT configurations that are bridge, hollow, and top position of Ni on SWCNT were calculated. The Ni on the bridge configuration was the most stable configuration based on binding energy and Ni-C bond length analysis. With the addition of Ni to SWCNT, the energy gap energy of SWCNT becomes narrower from 0.879 eV to 0.289 eV. The C 2H 4 adsorption energy was acquired stronger than C 2H 2, which results in a smaller energy gap. Also, the geometry change of the gases/Ni-SWCNT was investigated in this research.
Neutronic Study of Fast Reactor with Modified CANDLE Burnup Scheme Using natural Pb, Pb(nat)-Bi Eutectic,208Pb, and208Pb-Bi Eutectic as Coolant
Authors: Widiawati N , Su’ud Z , Irwanto D , Andris D
Published: June 2021

About 96% of reactors in the world consume enriched uranium. However, enrichment technology is costly and a sensitive issue related to nuclear non-proliferation. Whereas, without the technology, it is difficult to obtain the optimal benefits from the nuclear reactor. The long-life reactor designs that can consume natural uranium and minimize initial fue l loading are needed. Therefore, the design study of long-life Pb(208)-Bi eutectic cooled reactor with modified CANDLE (Constant Axial shape of Neutron flux, nuclide densities, and power shape During Life of Energy Energy production) burn up scheme has performed. Modified CANDLE burnup scheme can use natural Uranium (without enrichment) as fuel and also can reprocess LWR (Light-Water Reactor) spent fuel. In Modified CANDLE scheme, a reactor core is divided into 10 regions in an axial direction which has the same volume. Region 1 is filled by fresh natural uranium and after 10 years burnup, it is then shifted to region 2. These mechanisms are applied to all the regions. Coolant for LFR (Lead-cooled Fast Reactors) have some requirements such as has low neutron absorption, low melting point, high boiling point and non-reactive with air and water. Pb(208)-Bi eutectic is a promising coolant for LFR due to its properties. The Neutronic calculation was performed by SRAC and FITB.ch1 using JENDL 4.0 as nuclear data library. The Important neutronic parameter such as k-eff is discussed in the present study. Initial k-eff of the reactor using Pb-natural, Pb-Bi, Pb(208), and Pb(208)-Bi as coolant are 0.99973, 1.0020, 1.0089, and 1.0059, respectively.
Fast Neutron Irradiation Influence Analysis in Thermal-Hydraulics Aspect of HTR-10 Reactor Using Modified PEBBLE Program
Authors: Bari Bilal El , Irwanto Dwi
Published: June 2021

Pebble Bed Reactor is a Gen-IV reactor that uses spherical fuel loaded into an active core. This reactor uses graphite that can be found on fuel and reflectors as a neutron moderator. The fast neutron can damage the atomic structure of fuel because the neutron with high energy can displace the graphite lattice. As its effect, the value of fuel thermal conductivity is influenced. PEBBLE is the program used for thermal-hydraulic calculation for pebble bed reactor type (PBR), and mPEBBLE was developed based on PEBBLE. The main difference between the two is that the mPEBBLE can take into account the fast neutron factor in the calculation. In this study, the thermal-hydraulics calculation for HTR-10 was performed using the mPEBBLE code. The result obtained is compared to the results from two different programs; THERMIX and WIMSTER. The comparison between the mPEBBLE and THERMIX has a temperature difference, which is relatively high at 63.3°C at the near-wall position. For the comparison between mPEBBLE and WISMTER, the noticeable difference happens in pebble center temperature, which is 65.3°C for the temperature difference.
Occupational exposure to incidental nanoparticles: a review on control banding
Authors: Sousa M , Arezes P , Silva F
Published: June 2021

As the integration of nanomaterials in our lives evolves, these materials become more noticeable and so do the concerns about the associated risks. Handling engineered nanomaterials (ENM) increases these concerns and has been leading to multiple studies about how to assess the risk of exposure to these materials. In the meanwhile, many workers are not conscious that they are exposed to nanomaterials, since some are unintentionally released in workplaces, during industrial activities, for example. The exact approach to be taken to study this exposure risk is far from being fully established and unanimously accepted. Choosing a quantitative approach can lead to more consistent results, but it requires expert’s knowledge and proper equipment. A qualitative methodology may be less expensive and time consuming. Control Banding (CB) is an example of a qualitative approach, frequently used to manage the risk of exposure to engineered nanomaterials. But while numerous authors and organizations are focused on risk management of ENM, is the exposure to incidental nanomaterials being neglected? If not, how is this being managed? The purpose of this work was to review different CB approaches for occupational risk management of nanomaterials and to highlight its application for the specific case of incidental nanoparticles. Using two databases for the literature review and after some data analysis, the results of this work allowed to clarify the tendency to apply CB methodologies to ENM risk management research and also the opportunity of applying such approach to incidental nanomaterials.
Digital Twins applied to the implementation of Safe-by-Design strategies in nano-processes for the reduction of airborne emission and occupational exposure to nano-forms
Authors: López De Ipiña Jesús M. , Aznar Gabriel , Lopez Alberto , Olite Jorge , Koivisto Joonas , Bartolini Gianni , Costa Anna
Published: June 2021

Digital Twins (DTs) are one of the most promising enabling technologies for the deployment of the factory of the future and the Industry 4.0 framework. DTs could be labelled as an inherently Safe-by-Design (SbD) strategy and can be applied at different stages in the life cycle of a process. The EU-funded project ASINA has the ambition to promote coherent, applicable and scientifically sound SbD nano-practices. In particular, in the field of nanomanufacturing, ASINA intends to deliver innovative SbD solutions applied to process (P-SbD). In this context, ASINA will investigate the use of DTs as a disruptive digital technology for the prevention, prediction and control of nano-forms airborne emission and worker exposure. This paper introduces the concept of DT in the field of nano-processes SbD and outlines the preliminary architecture of ASINA-DT, that will be developed and implemented by ASINA in one industrial scenario.
Test of low radioactive molecular sieves for radon filtration in SF6
gas-based rare-event physics experiments
Authors: Marcelo Gregorio R.R. , Spooner N.J.C. , Berry J. , Ezeribe A.C. , Miuchi K. , Ogawa H. , Scarff A.
Published: June 2021

Type 5 Å molecular sieves (MS) have been demonstrated to remove radon from SF6 gas. This is important for ultra-sensitive SF6 gas-based directional dark matter and related rare-event physics experiments, as radon can provide a source of unwanted background events. Unfortunately, commercially available sieves intrinsically emanate radon at levels not suitable for ultra-sensitive physics experiments. A method to produce a low radioactive MS has been developed in Nihon University (NU). In this work, we explore the feasibility of the NU-developed 5 Å type MS for use in such experiments. A comparison with a commercially available Sigma-Aldrich 5 Å type MS was made. The comparison was done by calculating a parameter indicating the amount of radon intrinsically emanated by the MS per unit radon captured from SF6 gas. The measurements were made using a specially adapted DURRIDGE RAD7 radon detector. The NU-developed 5 Å MS emanated radon up to 61 ± 9% less per radon captured (2.1 ± 0.1) × 10−3, compared to the commercial Sigma-Aldrich MS (5.4 ± 0.4) × 10−3, making it a better candidate for use in a radon filtration setup for future ultra-sensitive SF6 gas based experiments.
Air equivalence of some solid fluoropolymers in photon beams
Authors: Habrman P.
Published: June 2021

Two fluoropolymers polyvinylidene fluoride (PVDF) and ethylene tetrafluoroethylene (ETFE), which differ only in chemical structure and have the same atomic composition, were evaluated for use in air simulation for phantom measurements in photon beams. Photon interaction was modelled using US-NIST datasets. In order to mimic the radiation properties of air with another material, values of the following quantities were chosen for comparison: total mass attenuation coefficients, mass-energy absorption coefficients, total electron mass stopping powers, mass collision stopping powers, and mass scattering powers. The calculated ratios of the corresponding coefficients or stopping powers between the material and air were the values of interest. The results for fluoropolymers were compared with other polymers commonly used in the manufacture of phantoms. The results show that in the photon energy range from 150 keV to 1 GeV both fluoropolymers exhibit excellent dosimetric properties slightly better than air equivalent plastic C552. The effect of a carbon-based filler added to the fluoropolymer to ensure the electrical conductivity of the resulting composite was also investigated. It has been found that the increased carbon-based filler content (up to 20 wt% of carbon) added to the fluoropolymer has a very small effect on the radiation properties of the composite.
Effects of salinity and light conditions on the survival of brown seaweed Sargassum ilicifolium (Turner) C. Agardh during early development
Authors: De Cruz A R E , De Cruz A E , Evangelio J C , Montes H R
Published: June 2021

The present study was carried out to investigate the survival of Sargassum ilicifolium from zygote to germling under laboratory conditions. Zygotes were cultured at 3 different salinity conditions (30-35 PSU, 20-25 PSU, and 10-15 PSU) and under the illumination of 3 various light sources (natural, fluorescent, and LED lights) with varying intensities. Results showed that S. ilicifolium germlings have a relatively higher tolerance to lower salinities that ranged from 10 to 30 PSU, and optimal growth in salinity ranges from 30– 35 PSU. There was no significant effect of the light source on this species’ zygote survival and germination. Fluorescent lighting effectively obtained high survival and germination rates of zygotes and driving the development of morphologically normal germlings compared to LED lighting. This study also demonstrated the potential of using zygote-derived germlings as a source of nursery seedlings. Therefore, salinity and light conditions were important variables affecting the survival, germination, and growth of S. ilicifolium, which are valuable data in developing streamlined practices for aquaculture production and management.
3D Strata Visualization in Web Environment – Review
Authors: Hanafi Faraliyana Mohd , Hassan Muhammad Imzan
Published: June 2021

Nowadays, rapid population growth has caused a high demand of land and stratified property especially in urban areas (big city). In cadastral system, visualization is considered as a tool for reflecting the real world which is commonly drawn in 2-Dimensional (2D) based plan. However, it only works efficiently for land parcel but not in representing strata property (high rise building). The complexity and overlapping boundaries also need to be considered in portraying 3-Dimensional (3D) model which cannot be achieved using only 2D plan. On top of that, the need of providing a 3D visualization platform has been recognised by many researchers worldwide. There have been numbers of 3D Cadastral system prototype being developed for different country such as Australia, Russia and Indonesia. 3D visualization helps enhanced communication between users, improve decision making, and helps to manage and facilitate land information system. This paper therefore seeks to analyse the problems related to the visualisation for the application of strata and the current approach of 3D visualisation. It is carried out by investigating different techniques and methods used in visualising 3D objects. The outcome of this paper would be the solutions in finding suitable visualization tools to be developed via Web-based visualization applications which are common with end users and easily accessible due to advancements in technology.
Fault Diagnosis and Prediction of Rolling Bearings Based on Deep Learning
Authors: Li Xing
Published: June 2021

In this paper, the rolling bearing is taken as the research object, and the deep learning method is applied to the diagnosis, identification and prediction of bearing state. The main models of deep learning and its application in rolling bearing fault diagnosis are analyzed, and some challenges and feasible solutions of deep learning in rolling bearing fault diagnosis are pointed out. In this paper, a fault diagnosis algorithm based on convolutional neural network in deep learning is proposed, and the original vibration data is used as the input of the network model to train it to exert its powerful self-learning ability. Compared with the traditional fault diagnosis method, the multi-layer network structure of the proposed method ensures its higher diagnosis accuracy; compared with the general bearing fault diagnosis method based on multi-feature extraction, the proposed method is simpler and more effective in extracting the features that can represent the health status of rolling bearings.
Study on Effect of Rock Interface on Hydraulic Fracture in W9 Offshore Gas Field
Authors: Xiaojin Wan , Ruohan Hu , Siyu Xie , Hui Yuan , Qaingui Zhang , Jin Zhao
Published: June 2021

In-situ principal stresses in ZH formation of W9 offshore gas field are measured by Kaiser effect method, and the horizontal minimum stress profile is interpreted by logging information. Static Young’s modulus and Poisson’s ratio of rock are measured by tri-axial loading experimental system, and cohesion and internal friction angle of rock are calculated by empirical formula based on logging data. Failure mode discrimination equation of hydraulic fracture at the rock interface is established applying stress analysis of hydraulic fracture tips at rock interface combined with tensile failure criterion and shear failure criterion. In-situ stresses and strength parameters in ZH formation are used to calculate and analyze the control effect of interface on hydraulic fracture propagation. The calculation results show it is necessary to control fracture height growth in ZH formation of W9 offshore gas field, which is of great significance on guiding the optimization of fracturing parameters in this field.
Investigation on Catalytic N2O Conversion to NO for Potential Nitric Acid Production from Industrial Waste Gas
Authors: Zhang Yuanyang , Feng Yaoyu
Published: June 2021

It is well known that N2O has a very significant impact on the greenhouse effect. Although N2O is not the major contributor to the global warming, while it could stay in atmosphere for about 150 years, and its global warming potential (GWP) is about 2.5 and 310 times as that of CH4and CO2, respectively. The main source of N2O emission from chemical industries is originated from the process of adipic/nitric acid production. The emission of N2O due to adipic acid production in China is about 0.48∼0.72 million tons per year based on the mass ratio between N2O emission and adipic acid production, which is equivalent to 150∼250 million tons CO2emission. However, there are few reports on economically reusing N2O from flue gas by direct oxidation method. Therefore, a series of catalysts applied on catalytic N2O conversion to NO for potential production of nitric acid from flue gas have been prepared by co-precipitation method. The basic property of catalysts was characterized by BET, laser particle size analyzer, FT-IR, TG/DTA, and CO2-TPD, etc. The catalyst’s performance was evaluated in a fixed-bed reactor with mixture of 40%(v)N2O+40%(v)N2+20%(v)O2under 3000 h−1space velocity and 0.1MPa system pressure. Results showed that catalysts of Pt/Cu-Zn-O and Pt/Zr-Zn-O have good selectivity on NO production, which was about 10% and 15%, respectively, in the temperature range from 550°C to 650°C. The basic experimental results show that it is a promising method to be applied for N2O reuse in adipic acid production and nitric acid industries and also provide the basis for further relative theoretical and experimental studies.
Evaluation of Carrying Capacity on Water Resources Based on Improved Water Footprint Method
Authors: Kong Xiangming , Wang Donglin , Zhao Jing , Wang Chunxiao , Cheng Rong
Published: June 2021

A water footprint based principal component analysis method (WFPCA) has been proposed for evaluation of carrying capacity on water resources. The evaluation indexes can be defined based on the water footprint theory. Then the comprehensive evaluation value of water resources carrying capacity can be generated by the method of principal component analysis. The developed WFPCA method has been applied in the case study in Tongliao City, China. The results show that the indexes defined based on the water footprint theory can reflect the interactions between human being activities and water resources systems. The readjustment of water utilization structure affects the practical water use and the virtual water footprint in Tongliao City. The comparison of comprehensive evaluation values from 2010 to 2019 indicates that the water resources carrying capacity in Tongliao City continues to increase, which is benefited from the reasonable planning of water resources systems and the effective management of environment systems.
Direct and indirect effects of high temperatures on fledging in a cooperatively breeding bird
Authors: Bourne Amanda R , Ridley Amanda R , Spottiswoode Claire N , Cunningham Susan J
Published: June 2021

High temperatures and low rainfall consistently constrain reproduction in arid-zone bird species. Understanding the mechanisms underlying this pattern is critical for predicting how climate change will influence population persistence and to inform conservation and management. In this study, we analyzed Southern Pied Babbler Turdoides bicolor nestling survival, daily growth rate and adult investment behavior during the nestling period over three austral summer breeding seasons. High temperatures were associated with lower body mass, shorter tarsi, and reduced daily growth rates of nestlings. Our piecewise structural equation models suggested that direct impacts of temperature had the strongest influence on nestling size and daily growth rates for both 5-day-old and 11-day-old nestlings, followed by temperature-related adjustments to provisioning rates by adults. Rainfall and group size influenced the behavior of provisioning adults but did not influence nestling growth or survival. Adjustments to adult provisioning strategies did not compensate for direct negative effects of high air temperatures on nestling size or daily growth rates. Detailed mechanistic data like these allow us to model the pathways by which high temperature causes nest failure. In turn, this could allow us to design targeted conservation action to effectively mitigate climate effects.
In silico model for miRNA-mediated regulatory network in cancer
Authors: Ahmed Khandakar Tanvir , Sun Jiao , Chen William , Martinez Irene , Cheng Sze , Zhang Wencai , Yong Jeongsik , Zhang Wei
Published: June 2021

Deregulation of gene expression is associated with the pathogenesis of numerous human diseases including cancer. Current data analyses on gene expression are mostly focused on differential gene/transcript expression in big data-driven studies. However, a poor connection to the proteome changes is a widespread problem in current data analyses. This is partly due to the complexity of gene regulatory pathways at the post-transcriptional level. In this study, we overcome these limitations and introduce a graph-based learning model, PTNet, which simulates the microRNAs (miRNAs) that regulate gene expression post-transcriptionally in silico. Our model does not require large-scale proteomics studies to measure the protein expression and can successfully predict the protein levels by considering the miRNA–mRNA interaction network, the mRNA expression, and the miRNA expression. Large-scale experiments on simulations and real cancer high-throughput datasets using PTNet validated that (i) the miRNA-mediated interaction network affects the abundance of corresponding proteins and (ii) the predicted protein expression has a higher correlation with the proteomics data (ground-truth) than the mRNA expression data. The classification performance also shows that the predicted protein expression has an improved prediction power on cancer outcomes compared to the prediction done by the mRNA expression data only or considering both mRNA and miRNA. Availability: PTNet toolbox is available at http://github.com/CompbioLabUCF/PTNet
fastsimcoal2: demographic inference under complex evolutionary scenarios
Authors: Excoffier Laurent , Marchi Nina , Marques David Alexander , Matthey-Doret Remi , Gouy Alexandre , Sousa Vitor C
Published: June 2021

Motivation

fastsimcoal2 extends fastsimcoal, a continuous time coalescent-based genetic simulation program, by enabling the estimation of demographic parameters under very complex scenarios from the site frequency spectrum under a maximum-likelihood framework.

Results

Other improvements include multi-threading, handling of population inbreeding, extended input file syntax facilitating the description of complex demographic scenarios, and more efficient simulations of sparsely structured populations and of large chromosomes.

Availability and implementation

fastsimcoal2 is freely available on http://cmpg.unibe.ch/software/fastsimcoal2/. It includes console versions for Linux, Windows and MacOS, additional scripts for the analysis and visualization of simulated and estimated scenarios, as well as a detailed documentation and ready-to-use examples.
Poor Antibody Response After Two Doses of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Vaccine in Transplant Recipients
Authors: Mazzola Alessandra , Todesco Eve , Drouin Sarah , Hazan Fanny , Marot Stéphane , Thabut Dominique , Varnous Shaida , Soulié Cathia , Barrou Benoît , Marcelin Anne-Geneviève , Conti Filomena
Published: June 2021

A low anti-spike antibody response of 28.6% was observed 28 days after BNT162b2 vaccine second dose among 133 solid organ transplant recipients without previous coronavirus disease 2019 (COVID-19). No serious adverse events were recorded. Four severe COVID-19 cases were reported between or after the 2 doses. Our data suggest to change the vaccine strategy.