bluuebunny/crossref_metadata_2025 huggingface dataset:
A cluster-based hybrid sampling approach for imbalanced data classification
Authors: Feng Shou , Zhao Chunhui , Fu Ping
Published: May 2020

When processing instrumental data by using classification approaches, the imbalanced dataset problem is usually challenging. As the minority class instances could be overwhelmed by the majority class instances, training a typical classifier with such a dataset directly might get poor results in classifying the minority class. We propose a cluster-based hybrid sampling approach CUSS (Cluster-based Under-sampling and SMOTE) for imbalanced dataset classification, which belongs to the type of data-level methods and is different from previously proposed hybrid methods. A new cluster-based under-sampling method is designed for CUSS, and a new strategy to set the expected instance number according to data distribution in the original training dataset is also proposed in this paper. The proposed method is compared with five other popular resampling methods on 15 datasets with different instance numbers and different imbalance ratios. The experimental results show that the CUSS method has good performance and outperforms other state-of-the-art methods.
Future of the human climate niche
Authors: Xu Chi , Kohler Timothy A. , Lenton Timothy M. , Svenning Jens-Christian , Scheffer Marten
Published: May 2020

Significance

We show that for thousands of years, humans have concentrated in a surprisingly narrow subset of Earth’s available climates, characterized by mean annual temperatures around ∼13 °C. This distribution likely reflects a human temperature niche related to fundamental constraints. We demonstrate that depending on scenarios of population growth and warming, over the coming 50 y, 1 to 3 billion people are projected to be left outside the climate conditions that have served humanity well over the past 6,000 y. Absent climate mitigation or migration, a substantial part of humanity will be exposed to mean annual temperatures warmer than nearly anywhere today.
The protective benefits of tsunami mitigation parks and ramifications for their strategic design
Authors: Lunghino Brent , Santiago Tate Adrian F. , Mazereeuw Miho , Muhari Abdul , Giraldo Francis X. , Marras Simone , Suckale Jenny
Published: May 2020

Nature-based solutions are becoming an increasingly important component of sustainable coastal risk management. For particularly destructive hazards like tsunamis, natural elements like vegetation are often combined with designed elements like seawalls or dams to augment the protective benefits of each component. One example of this kind of hybrid approach is the so-called tsunami mitigation park, which combines a designed hillscape with vegetation. Despite the increasing popularity of tsunami mitigation parks, the protective benefits they provide are poorly understood and incompletely quantified. As a consequence of this lack of understanding, current designs might not maximize the protective benefits of tsunami mitigation parks. Here, we numerically model the interactions between a single row of hills with an incoming tsunami to identify the mechanisms through which the park protects the coast. We initialize the tsunami as an N wave that propagates to shore and impacts the coast directly. We find that partial reflection of the incoming wave is the most important mechanism by which hills reduce the kinetic energy that propagates onshore. The protective benefit of tsunami mitigation parks is thus comparable to that of a small wall, at least for tsunamis with amplitudes that are comparable to the hill height. We also show that hills could elevate potential damage in the immediate vicinity of the hills where flow speeds increase compared to a planar beach, suggesting the need to include a buffer zone behind the hills into a strategic park design.
Metabolic cost of rapid adaptation of single yeast cells
Authors: Woronoff Gabrielle , Nghe Philippe , Baudry Jean , Boitard Laurent , Braun Erez , Griffiths Andrew D. , Bibette Jérôme
Published: May 2020

Cells can rapidly adapt to changing environments through nongenetic processes; however, the metabolic cost of such adaptation has never been considered. Here we demonstrate metabolic coupling in a remarkable, rapid adaptation process (1 in 1,000 cells adapt per hour) by simultaneously measuring metabolism and division of thousands of individual
Saccharomyces cerevisiae
cells using a droplet microfluidic system: droplets containing single cells are immobilized in a two-dimensional (2D) array, with osmotically induced changes in droplet volume being used to measure cell metabolism, while simultaneously imaging the cells to measure division. Following a severe challenge, most cells, while not dividing, continue to metabolize, displaying a remarkably wide diversity of metabolic trajectories from which adaptation events can be anticipated. Adaptation requires a characteristic amount of energy, indicating that it is an active process. The demonstration that metabolic trajectories predict
a priori
adaptation events provides evidence of tight energetic coupling between metabolism and regulatory reorganization in adaptation. This process allows
S. cerevisiae
to adapt on a physiological timescale, but related phenomena may also be important in other processes, such as cellular differentiation, cellular reprogramming, and the emergence of drug resistance in cancer.
Essential role for autophagy protein ATG7 in the maintenance of intestinal stem cell integrity
Authors: Trentesaux Coralie , Fraudeau Marie , Pitasi Caterina Luana , Lemarchand Julie , Jacques Sébastien , Duche Angéline , Letourneur Franck , Naser Emmanuelle , Bailly Karine , Schmitt Alain , Perret Christine , Romagnolo Béatrice
Published: May 2020

The intestinal epithelium acts as a barrier between the organism and its microenvironment, including the gut microbiota. It is the most rapidly regenerating tissue in the human body thanks to a pool of intestinal stem cells (ISCs) expressing
Lgr5
. The intestinal epithelium has to cope with continuous stress linked to its digestive and barrier functions. Epithelial repair is crucial to maintain its integrity, and Lgr5-positive intestinal stem cell (Lgr5
+
ISC) resilience following cytotoxic stresses is central to this repair stage. We show here that autophagy, a pathway allowing the lysosomal degradation of intracellular components, plays a crucial role in the maintenance and genetic integrity of Lgr5
+
ISC under physiological and stress conditions. Using conditional mice models lacking the autophagy gene
Atg7
specifically in all intestinal epithelial cells or in Lgr5
+
ISC, we show that loss of Atg7 induces the p53-mediated apoptosis of Lgr5
+
ISC. Mechanistically, this is due to increasing oxidative stress, alterations to interactions with the microbiota, and defective DNA repair. Following irradiation, we show that Lgr5
+
ISC repair DNA damage more efficiently than their progenitors and that this protection is Atg7 dependent. Accordingly, we found that the stimulation of autophagy on fasting protects Lgr5
+
ISC against DNA damage and cell death mediated by oxaliplatin and doxorubicin treatments. Finally,
p53
deletion prevents the death of
Atg7
-deficient Lgr5
+
ISC but promotes genetic instability and tumor formation. Altogether, our findings provide insights into the mechanisms underlying maintenance and integrity of ISC and highlight the key functions of Atg7 and p53.
Darwin’s naturalization conundrum can be explained by spatial scale
Authors: Park Daniel S. , Feng Xiao , Maitner Brian S. , Ernst Kacey C. , Enquist Brian J.
Published: May 2020

Darwin proposed two seemingly contradictory hypotheses regarding factors influencing the outcome of biological invasions. He initially posited that nonnative species closely related to native species would be more likely to successfully establish, because they might share adaptations to the local environment (preadaptation hypothesis). However, based on observations that the majority of naturalized plant species in the United States belonged to nonnative genera, he concluded that the lack of competitive exclusion would facilitate the establishment of alien invaders phylogenetically distinct from the native flora (competition-relatedness hypothesis). To date, no consensus has been reached regarding these opposing hypotheses. Here, following Darwin, we use the flora of the United States to examine patterns of taxonomic and phylogenetic relatedness between native and nonnative taxa across thousands of nested locations ranging in size and extent, from local to regional scales. We find that the probability of observing the signature of environmental filtering over that of competition increases with spatial scale. Further, native and nonnative species tended to be less related in warm, humid environments. Our work provides an empirical assessment of the role of observation scale and climate in biological invasions and demonstrates that Darwin’s two opposing hypotheses need not be mutually exclusive.
Prodrugs of PKC modulators show enhanced HIV latency reversal and an expanded therapeutic window
Authors: Sloane Jack L. , Benner Nancy L. , Keenan Katherine N. , Zang Xiaoyu , Soliman Mohamed S. A. , Wu Xiaomeng , Dimapasoc Melanie , Chun Tae-Wook , Marsden Matthew D. , Zack Jerome A. , Wender Paul A.
Published: May 2020

Significance

Since the start of the HIV/AIDS epidemic, approximately 32 million people have died from the infection. Although antiretroviral therapy slows disease progression by preventing virus replication, it does not eliminate latently infected cells, which can resupply active virus, necessitating lifelong treatment. Latency-reversing agents (LRAs), such as protein kinase C (PKC) modulators, present a strategy to cure the disease by activating and enabling immunological clearance of latent viral reservoirs. A major challenge with the clinical use of LRAs is sustaining therapeutic levels of the active agent while minimizing side effects. To address this problem, we report prodrugs of PKC modulators for use in HIV eradication. Relative to the parent, select prodrugs show delayed activation and significantly better efficacy and tolerability.
The origin and diversification of a novel protein family in venomous snakes
Authors: Giorgianni Matt W. , Dowell Noah L. , Griffin Sam , Kassner Victoria A. , Selegue Jane E. , Carroll Sean B.
Published: May 2020

The genetic origins of novelty are a central interest of evolutionary biology. Most new proteins evolve from preexisting proteins but the evolutionary path from ancestral gene to novel protein is challenging to trace, and therefore the requirements for and order of coding sequence changes, expression changes, or gene duplication are not clear. Snake venoms are important novel traits that are comprised of toxins derived from several distinct protein families, but the genomic and evolutionary origins of most venom components are not understood. Here, we have traced the origin and diversification of one prominent family, the snake venom metalloproteinases (SVMPs) that play key roles in subduing prey in many vipers. Genomic analyses of several rattlesnake (
Crotalus
) species revealed the SVMP family massively expanded from a single, deeply conserved
adam28
disintegrin and metalloproteinase gene, to as many as 31 tandem genes in the Western Diamondback rattlesnake (
Crotalus atrox
) through a number of single gene and multigene duplication events. Furthermore, we identified a series of stepwise intragenic deletions that occurred at different times in the course of gene family expansion and gave rise to the three major classes of secreted SVMP toxins by sequential removal of a membrane-tethering domain, the cysteine-rich domain, and a disintegrin domain, respectively. Finally, we show that gene deletion has further shaped the SVMP complex within rattlesnakes, creating both fusion genes and substantially reduced gene complexes. These results indicate that gene duplication and intragenic deletion played essential roles in the origin and diversification of these novel biochemical weapons.
Neutron crystallography of copper amine oxidase reveals keto/enolate interconversion of the quinone cofactor and unusual proton sharing
Authors: Murakawa Takeshi , Kurihara Kazuo , Shoji Mitsuo , Shibazaki Chie , Sunami Tomoko , Tamada Taro , Yano Naomine , Yamada Taro , Kusaka Katsuhiro , Suzuki Mamoru , Shigeta Yasuteru , Kuroki Ryota , Hayashi Hideyuki , Yano Takato , Tanizawa Katsuyuki , Adachi Motoyasu , Okajima Toshihide
Published: May 2020

Recent advances in neutron crystallographic studies have provided structural bases for quantum behaviors of protons observed in enzymatic reactions. Thus, we resolved the neutron crystal structure of a bacterial copper (Cu) amine oxidase (CAO), which contains a prosthetic Cu ion and a protein-derived redox cofactor, topa quinone (TPQ). We solved hitherto unknown structures of the active site, including a keto/enolate equilibrium of the cofactor with a nonplanar quinone ring, unusual proton sharing between the cofactor and the catalytic base, and metal-induced deprotonation of a histidine residue that coordinates to the Cu. Our findings show a refined active-site structure that gives detailed information on the protonation state of dissociable groups, such as the quinone cofactor, which are critical for catalytic reactions.
Stentian structural plasticity in the developing visual system
Authors: Rahman Tasnia N. , Munz Martin , Kutsarova Elena , Bilash Olesia M. , Ruthazer Edward S.
Published: May 2020

In a small fraction of
Xenopus
tadpoles, a single retinal ganglion cell (RGC) axon misprojects to the ipsilateral optic tectum. Presenting flashes of light to the ipsilateral eye causes that ipsilateral axon to fire, whereas stimulating the contralateral eye excites all other RGC inputs to the tectum. We performed time-lapse imaging of individual ipsilaterally projecting axons while stimulating either the ipsilateral or contralateral eye. Stimulating either eye alone reduced axon elaboration by increasing branch loss. New branch additions in the ipsi axon were exclusively increased by contralateral eye stimulation, which was enhanced by expressing tetanus neurotoxin (TeNT) in the ipsilateral axon, to prevent Hebbian stabilization. Together, our results reveal the existence of a non−cell-autonomous “Stentian” signal, engaged by activation of neighboring RGCs, that promotes exploratory axon branching in response to noncorrelated firing.
There is no privileged link between kinds and essences early in development
Authors: Noyes Alexander , Keil Frank C.
Published: May 2020

According to the dominant view of category representation, people preferentially infer that kinds (richly structured categories) reflect essences. Generic language (“Boys like blue”) often occupies the central role in accounts of the formation of essentialist interpretations—especially in the context of social categories. In a preregistered study (n= 240 American children, ages 4 to 9 y), we tested whether children assume essences in the presence of generic language or whether they flexibly assume diverse causal structures. Children learned about a novel social category described with generic statements containing either biological properties or cultural properties. Although generic language always led children to believe that properties were nonaccidental, young children (4 or 5 y) in this sample inferred the nonaccidental structure was socialization. Older children (6 to 9 y) flexibly interpreted the category as essential or socialized depending on the type of properties that generalized. We uncovered early-emerging flexibility and no privileged link between kinds and essences.
Evidence from internet search data shows information-seeking responses to news of local COVID-19 cases
Authors: Bento Ana I. , Nguyen Thuy , Wing Coady , Lozano-Rojas Felipe , Ahn Yong-Yeol , Simon Kosali
Published: May 2020

The COVID-19 outbreak is a global pandemic with community circulation in many countries, including the United States, with confirmed cases in all states. The course of this pandemic will be shaped by how governments enact timely policies and disseminate information and by how the public reacts to policies and information. Here, we examine information-seeking responses to the first COVID-19 case public announcement in a state. Using an event study framework for all US states, we show that such news increases collective attention to the crisis right away. However, the elevated level of attention is short-lived, even though the initial announcements are followed by increasingly strong policy measures. Specifically, searches for “coronavirus” increased by about 36% (95% CI: 27 to 44%) on the day immediately after the first case announcement but decreased back to the baseline level in less than a week or two. We find that people respond to the first report of COVID-19 in their state by immediately seeking information about COVID-19, as measured by searches for coronavirus, coronavirus symptoms, and hand sanitizer. On the other hand, searches for information regarding community-level policies (e.g., quarantine, school closures, testing) or personal health strategies (e.g., masks, grocery delivery, over-the-counter medications) do not appear to be immediately triggered by first reports. These results are representative of the study period being relatively early in the epidemic, and more-elaborate policy responses were not yet part of the public discourse. Further analysis should track evolving patterns of responses to subsequent flows of public information.
Key comparison BIPM.RI(I)-K7 of the air-kerma standards of the NRC, Canada and the BIPM in mammography x-rays
Authors: Kessler C , Burns D T , Mainegra-Hing E , Shen H , McEwen M R
Published: May 2020

A key comparison has been made between the air-kerma standards of the NRC and the BIPM in mammography x ray beams. The results show the standards to be in agreement at the level of the combined standard uncertainty of 3.2 parts in 103. The results are analysed and presented in terms of degrees of equivalence, suitable for entry in the BIPM key comparison database.

Main text

To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/.

The final report has been peer-reviewed and approved for publication by the CCRI, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Length-dependence of light-induced currents in graphene
Authors: Boolakee Tobias , Heide Christian , Wagner Fabian , Ott Christian , Schlecht Maria , Ristein Jürgen , Weber Heiko B , Hommelhoff Peter
Published: May 2020

We investigate the transport of optically injected currents in graphene, a (semi-) metal with exceptional optical and electronic properties. We have recently shown that ultrashort laser pulses with low temporal symmetry drive coupled intraband motion and interband (Landau–Zener) transitions resulting in residual ballistic currents in graphene. Here we show experimentally how this current scales as a function of the distance between the light-induced current injection region and the adjacent metal contact electrodes and propose an approach to model the results based on diffusive and field driven charge transport. We expect this study to contribute to ongoing discussions on the propagation of light-field-controlled currents, a requirement for future lightwave electronics, operating at petahertz clock rates.
Detail study of application of the relativistic mean-field effective NN forces for heavy-ion fusion within a dynamical model
Authors: Chushnyakova M V , Gontchar I I , Khmyrova N A
Published: May 2020

In the analysis of the heavy-ion above-barrier fusion cross-sections of complex nuclei, the relativistic effects are usually ignored. In the present work, we undertake a step toward accounting for these effects. Namely, the nucleus–nucleus interaction potential is obtained using the double-folding model with six different effective nucleon–nucleon (NN) forces coming from the relativistic mean field (RMF) theory. We also compare our present results with the ones obtained with the non-relativistic M3Y NN-forces. In all calculations, the nuclear densities resulting from the Hartree–Fock approach with the SKX-Skyrme forces accounting for the tensor part are used. Our calculations show that four sets of the considered RMF forces cannot be used for describing heavy ion fusion. Of the remaining two sets, one results in the barriers which are too high not leaving any room for the dissipative effects. Only the potentials calculated using the NL2 NN-forces allow us to reproduce the experimental cross-sections within the framework of the fluctuation–dissipation trajectory model with surface friction with a typical accuracy of 3%–5%. The values of the variable parameter of the model which defines the friction strength resulting from the present calculations are systematically lower than those obtained earlier with the M3Y NN-forces.
Magnetoelastic coupling associated with vacancy ordering and ferrimagnetism in natural pyrrhotite, Fe7S8
Authors: Haines C R S , Lampronti G I , Carpenter M A
Published: May 2020

Magnetoelastic coupling associated with the hexagonal—monoclinic transition in a natural sample of the mineral pyrrhotite, Fe7S8, has been analysed in terms of separate coupling of spontaneous strains with two discrete order parameters, q
v for Fe/vacancy ordering and q
m for magnetic ordering. Coupling of the two order parameters separately with strain gives rise to two terms for coupling between them, λ

q

m

2

q

v

2

and λ

q

m

2

q

v

8

, and a pattern of evolution in which q
v varies continuously and q
m discontinuously through a single transition point. The transition is ferrimagnetic and ferroelastic but the relatively slow relaxation rate for Fe/vacancy ordering, in comparison with magnetic ordering, results in elastic and anelastic properties which are quite different from those observed in other ferroic or multiferroic materials with two instabilities. Instead of classical elastic softening, there is stiffening of the elastic constants which scales with

q

m

2

and

q

v

2

. Instead of the normal pattern of acoustic loss associated with the mobility and subsequent freezing for ferroelastic twin walls, the loss is consistently low throughout the temperature range 300 K–875 K.
Influence of Deposited Material Energy on Superconducting Properties of the WSi Films
Authors: Vasilev D D , Malevannaya E I , Moiseev K M , Zolotov P I , Antipov A V , Vakhtomin Y B , Smirnov K V
Published: May 2020

WSi thin films have the advantages for creating SNSPDs with a large active area or array of detectors on a single substrate due to the amorphous structure. The superconducting properties of ultrathin WSi films substantially depends on their structure and thickness as the NbN films. Scientific groups investigating WSi films mainly focused only on changes of their thickness and the ratio of the components on the substrate at room temperature. This paper presents experiments to determine the effect of the bias potential on the substrate, the temperature of the substrate, and the peak power of pulsed magnetron sputtering, which is the equivalent of ionization, a tungsten target, on the surface resistance and superconducting properties of the WSi ultrathin films. The negative effect of the substrate temperature and the positive effect of the bias potential and the ionization coefficient (peak current) allow one to choose the best WSi films formation mode for SNSPD: substrate temperature 297 K, bias potential -60 V, and peak current 3.5 A.
Features of Au(80)Sn(20) thin film solder manufacturing technology
Authors: Filonenko E M , Fomin A V , Ivanov V V
Published: May 2020

This work provides the results of manufacturing technology development for Au(80)Sn(20) thin film solders produced with electron-beam evaporation coating of alternating gold and tin layers. The phase formation mechanism in the produced solders was studied to work out an evaporation procedure which enables to make a solder with the properties meeting the requirements to soldering of a laser diode onto a heatsink base surface.
Investigation of MoS2ultrathin films formed by physical vapor deposition in vacuum
Authors: Belikov A I , Phyo Kyaw Zin , Syomochkin A I
Published: May 2020

The article presents the optical spectroscopy results of molybdenum disulfide ultrathin films deposited on Si substrates by the methods of direct current (DCMS) and pulsed (PMS) magnetron sputtering MoS2target in vacuum, and also at flow deposition under the influence of external magnetic field on the substrate. Furthermore, the article revues the results of optical bandgap calculation for all samples of MoS2thin films.
Ultrathin film deposition for nanoelectronic device manucturing
Authors: Panfilov Y V , Rodionov I A , Ryzhikov I A , Baburin A S , Moskalev D O , Lotkov E S
Published: May 2020

Study results of thin film with thickness less than 50 nm deposition by means of electron beam evaporation on special vacuum coaters were represented. Calculation results of energy and mass carry magnitude for ITO, Ag and Al thin films deposition with preset of structure and composition homogeneity and roughness were shown.
Development of microfluidic chip manufacturing technology for human sweat analysis
Authors: Sevryugina E A , Sidorova S V
Published: May 2020

A technology for manufacturing a microfluidic chip for analyzing the composition of human sweat is proposed. Microfluidic chips can be made of various materials, and, depending on this, can be made by various methods. The analysis of the materials of the constituent components of the product. Equipment was selected for each operation, modes were selected.
Coupling relationship between transportation and tourism systems—a case study in the Huizhou City, China
Authors: Zeng Jingni , Rong Qiangqiang , Yue Wencong , Dai Xuejun , Su Meirong
Published: May 2020

Coupling relationship between transportation and tourism systems is significant to the sustainable development of regional economy, society and environment. Based on the coupling coordination degree model and scenario analysis method, the coupling relationship between transportation and tourism systems in the Huizhou City was studied in this research. The results showed that during 2014 and 2015, the coupling coordination degree between the two systems in the Huizhou City was at a moderate imbalance level. In terms of the districts and counties in the city, Huicheng District was at a moderate imbalance level, while Huiyang District, Longmen, Boluo and Huidong Counties were at a slight imbalance level. Results from the scenario analysis indicated that in order to improve the coordination between the transportation and tourism systems, decision makers in Huicheng and Huiyang Districts are supposed to increase effort to develop tourism while those in Longmen, Boluo and Huidong Counties are expected to pay more attention to transportation development. This research will help provide a decision-making basis for the urban planning in the Huizhou City. It will also provide a theoretical and methodological support for the other areas with similar concerns.
Mathematical model and simulated power performance of a novel O-type engine
Authors: Chen Guanyu , Zhang Zhengqing
Published: May 2020

Reciprocating engines such as V-type, L-type and W-type engines are used widely in our daily life. However, there is still some room for the improvement of power performance if the configuration of the cylinder and connecting rod system is changed. In this paper, a novel O-type engine is put forward firstly. The structural features of the O-type cylinder sets are described briefly, and then the relevant mathematical model with hypotheses is established to conduct the performance analysis. Secondly, the O-type engine is compared with the general range of power performance of gasoline engine to demonstrate its merits. Then, the power performance indicators, namely the mean indicated pressure (PMI), space occupation efficiency (SOE) and heat efficiency (HE) of the novel engine are analysed and discussed in detail through MATLAB with the verification and validation which are conducted to ensure the reliability of results. And the results show that the power performance of the O-type engine is better than most of gasoline engines; the power performance indicators in the research are not monotonous at different volumes with the bore stroke ratio increasing; the proper range of the volume and the bore stroke ratio is obtained to make the engine achieve a high power performance. All in all, the research is helpful for the development and application of the O-type engine.
The development of artificial intelligence and the response of labor policy
Authors: Pan Xiaodie , Zhong Hongsen
Published: May 2020

With the emergence of big data, information technology, digital technology and artificial intelligence, our society is making great strides towards an artificial intelligence society, and the foundation of economic society has undergone profound changes. Today’s labor policy must not only adapt to the needs of marketization, but also need to respond legally due to the development of science and technology. It should reasonably anticipate the changes in labor relations caused by artificial intelligence, including the norms of digital labor and the status of labor policy of intelligent robots. And the protection of social rights after the replacement of traditional labor. In the era of high-tech being widely used, the rapid development of modern artificial intelligence is gradually spreading from the field of science and technology to the life of the general public. This will have a subversive impact on labor relations. This is also the future of labor The amendment of the Law is an important factor that cannot be ignored.
Application of Markov Chains
Authors: Luo Qianfan
Published: May 2020

This paper introduces the theory of Markov Chains and illustrates the deduction of its transition probability matrix. A mathematical model for the growth of a bacteria colony and a mathematical model of the artificial intelligence in the venous transfusion are built. They are based on Markov chains and accord with the properties of transition matrix. The limitation of the model is discussed. The material is cited from authoritative websites, research done by academic institutions, and scientific essays.
Study on Dissolved Oxygen, Ammonia-nitrogen and Permanganate Index in Water of Lake Dianchi
Authors: Li Lucen
Published: May 2020

The water environment of Lake Dianchi in Yunnan province is threatened by eutrophication, which leads to the decrease of dissolved oxygen in water. Meanwhile, as the index reflecting the pollution of organic and inorganic oxidizable substances in water, permanganate index is also affected. China has been developing the automatic monitoring system for a series of water quality factors, such as dissolved oxygen and permanganate index. Additionally, the monitoring and prediction of ammonia-nitrogen, one of the water eutrophication sources, are also important. This study analyzed the water quality factor data in Lake Dianchi from 2015 to 2018 and implemented the prediction based on the Long Short-Term Memory neural network algorithm. It is found that the water quality of Lake Dianchi will be in a relatively ideal state in the future, but it cannot be improved further by itself. The Kunming government should implement more targeted improvement measures according to the characteristics of water quality factors, such as the seasonality of Lake Dianchi. Those measures will improve the ecological service quality of Lake Dianchi effectively, ensure the daily water safety of people in Kunming, and bring more economic values to the city.
A Non-line-of-Sight Propagation Identification Algorithm in Wireless Sensor Network
Authors: Chu H , Ji P , Lian S , Yang H , Wu R
Published: May 2020

With the rapid developing of communication technology, Wireless Sensor Network(WSN) has been applied in many fields. The accuracy of localization is the vital key to all these applications. In order to mitigate the non-line of-sight(NLOS) influence, we propose a propagation identification algorithm based on Anderson-Darling(AD) test. Firstly, the status of signal is determined by the AD testing. Secondly, the particle swarm optimization algorithm is adopted to estimate the mobile node based on the identification results. Finally, the effectiveness of the algorithm is verified by simulation experiments.
Based on PPI Network and Deep Learning Predicte Protein Function Module Algorithm
Authors: Huo Sicong , Lu Tao
Published: May 2020

The existing Protein protein interaction(PPI) based prediction algorithm for protein functional modules has the disadvantages of low accuracy and less number of functional modules. This paper presents an algorithm based on PPI network and in-depth learning and prediction of protein function module. In this method, three important attributes (node location, PPI network structure and core nodes) are integrated to improve the prediction accuracy and increase the number of protein functional modules. In this paper, First use the Local Density-Based Methods (LDBM) improved density clustering algorithm for clustering analysis. After clustering, use the improved to isometric mapping dimension reduction algorithm for principal component analysis (PPIPCA); then use Multi Layer Perceptron (MLP) for training and function module selection. Last Based on PPI network and deep learning based prediction protein function module algorithm (LPMM) compared with other algorithms. On the basis of yeast dip data set, the accuracy, F value, dimensionality reduction rate and functional module of recognition protein of LPMM algorithm and acc-fmd, MCL and mcode algorithm based on PPI network were compared. Experimental results show that LPMM algorithm is superior to other algorithmsin accuracy, F value, dimensionality reduction rate, number of recognition modules and so on.
The Hotspots of Smart Education in China: Base on the Bibliometric Analysis and Knowledge Mapping
Authors: Wang HaiBin , Chen Qian , Hong Aoyuan , Wang Xiaoyan , Hou Ziyi , Cheng Lin
Published: May 2020

To explore the hotspots in the area of Smart education in China, 245 related articles form the China National Knowledge Infrastructure (CKNI) were analyzed by the visualization software of CiteSpace. The results show that: (1) the studies of smart education began in 2003 while there were sporadic papers published in the next ten years. There was an increasing trend year by year from 2013 to 2017 and the number of articles reached the historical peak in 2017 with 52 articles. Xianming Yang, Jiangsu Normal University and E-Education Research topped the lists of contributing authors, organizations and publications respectively. (2) “smart education”, “educational informationization”, “intelligent education” and “smart campus” were the top four largest clusters in the domain of smart education in China.
Exploring the cross-disciplinary collaboration: a scientometric analysis of social science research related to Artificial Intelligence and Big Data application
Authors: Liao Han-Teng , Wang Zijia , Liu Yu
Published: May 2020

Given the significant impacts of Big Data and Artificial Intelligence (AI) on the planet and people, it is important for researchers from all disciplines to pay attention to the social, economic and policy needs and challenges with its applications. With the aim to provide a systematic review of social science literatures on the topic, this article has summarized the annual trends since 1962, main research disciplines and publication outlets based on a scientometric analysis of 10,229 articles collected from the WoS database. The research findings show that disciplines/areas such as management and psychology have been constantly engaging the Big Data and AI, whereas new emerging disciplines/areas such as interdisciplinary social sciences and geography have experienced exponential growth in recent years. Both the application and critiques of Big Data and AI have been published in various new journals such as Big Data & Society, Value in Health, etc. The article therefore provides essential groundwork for understanding and contextualizing the Big Data and AI applications, so that researchers, funding bodies, policy-makers and industry professionals can enhance cross-disciplinary collaboration.
Analysing Gender Bias in IMDB Films Based on Social Networks
Authors: Chen Jiayuan , Cui Minglu
Published: May 2020

The film industry has a major impact on society. This paper focuses on the gender bias in films. First, the social network analysis (SNA) method is used to construct a movie social network from the online movie dataset IMDb. By analysing these social network data, natural language processing methods are used to analyse movie titles, movie subtitles and casts. Then, this paper constructs a film gender bias classifier. Because the online movie data set IMDb lacks large-scale manual annotation data, and the classifier using traditional deep learning is prone to over-fitting, so this paper proposes a movie gender based on dual learning. The bias feature extractor and classifier enable training of the deep learning model from a small amount of annotated data and classify the bias. Finally, we find that women’s roles in the film have improved in all aspects, including the central role of female characters.
Review on Application of Binocular Vision Technology in Field Obstacle Detection
Authors: Wang Qiao , Meng Zhijun , Liu Hui
Published: May 2020

Obstacles within the field are the main external source of safety hazard in field operation of agricultural machineries. Autonomous obstacle avoidance is a critical technology to be solved for the robotization of field operation by agricultural machineries. For this technology, a critical premise is to timely and accurately perceive static and dynamic information of field obstacles. Firstly, this paper describes main detection parameters of field obstacles. Whereafter, by compared with other detection technologies, applicability of binocular vision-based detection technology in field obstacle detection is analyzed. Afterwards, this paper summarizes the whole process of binocular vision-based obstacle detection into three steps. For step one, main detecting methods for locating obstacles in images, main principles of these methods and their applicability in field operation scene are discussed. For step two, main existing methods for detecting spatial position parameters of obstacles based on detection results of step one and their application status in field operation scene are summarized. For step three, typical target tracking methods for obtaining the motion state of obstacles are compared and summarized, and their reference value for future research is pointed out. At last, the main challenges of detecting obstacles in field scene based on binocular vision are summarized.
A Novel Fuzzy Evaluation Method on Teaching Quality of College English based on Preference Selection Index
Authors: Liu Guojiaozi , Cai Qing , Ren Haiping
Published: May 2020

The evaluation of teaching quality is an important part of the quality management of teaching in colleges and universities. Many evaluation systems exist shortcomings, which are not suitable for the evaluation of English class. Because English subject has its own characteristics, in which the evaluation subject taken on students is more suitable than on teachers. This paper will propose a college English evaluation index system on the basis of students as the evaluation subject. Since the evaluation indicators are mainly qualitative indicators, which makes the evaluation value fuzzy, this paper proposes a new evaluation method of college English classroom teaching evaluation based on linguistic terms, triangular fuzzy numbers and preference selection index method. Finally, an algorithm case is analyzed to illustrate the effectiveness and feasibility of the proposed method.
Towards the eco-design of Artificial Intelligence and Big Data applications: a bibliometric analysis of related research
Authors: Wang Zijia , Liao Han-Teng
Published: May 2020

Given the impacts of information and communications technologies on the planet and people, researchers from all disciplines need to pay attention to the environmental footprints and sustainable opportunities associated with the Artificial Intelligence (AI) and Big Data applications. In order to provide a preliminary discussion on the eco-design of AI and Big Data applications, the paper aims to map out the sources and topics to explore (1) the intersections of eco-design with AI and Big Data, and (2) the sustainable and eco-friendly design. Based on a bibliometric analysis of 236 articles gathered from the Web of Science (WoS) database, the paper has identified main research topics, publication outlets, research fronts, and intellectual bases and explored their inter-relationship and grouping. The leading application disciplines include construction & building technology, automation & control system, computer & information science, and business & economics. Multi-disciplinary and inter-disciplinary journals such as Sustainability, Journal of Cleaner Production, and Sustainable Cities and Society have been proven to be more receptive to such eco-design research outputs. As the notion of eco-design of AI and Big Data applications is expected to be pertinent and relevant for designing greener strategies, products and services for green digital transformation, we argue that more concerted efforts must be made to advance both the theoretical and empirical research on the nascent topic among researchers, funding bodies, policy-makers and industry professionals.
Analysis on the Economic Development and Innovation Path of Tourism Cultural and Creative Industry Based on Big Data Statistics
Authors: Wu Ke
Published: May 2020

As Computer Internet improves by leaps and bounds, human beings have been in an era full of data and information. Various efficient and advanced management software has filled every aspect of human life, and the rapid growth of it is more and more suitable for people’s travel and lifestyle. As an information-intensive industry, tourism cultural and creative industry is naturally integrated with information technology. Therefore, the use of big data on the Internet has triggered two revolutions as the core. All of this have profoundly changed the mode of running, management and operation, and play a vital role in the development of such enterprises.
Applications and challenges of arc welding methods in dissimilar metal joining
Authors: Chaudhari R , Loharkar P K , Ingle A
Published: May 2020

Dissimilar metal welding is a significant metal joining process with an extensive application in industrial domain. The quality of the welded joint is of critical importance in these applications and quite an issue since the base metals are different primarily due to different physical, chemical and mechanical characteristics. In this paper, the challenges encountered in dissimilar metal joining are enlisted with a brief discussion on the corresponding causes. As discussed in the literature, several methods exist to form dissimilar joints. However, arc-based fusion methods are prominently used. Therefore, an overview of these methods is presented along with the applications in which these methods have been used. The study provides a brief account of the materials that have been successfully joined using these methods and the influence of significant parameters including filler materials on the effectiveness of dissimilar joining.
Carbon Fibre Reinforced Composite Material: Review of Properties and Processing for various Metal Matrix Materials
Authors: Sandhanshiv Rahul D. , Patel D. M.
Published: May 2020

Carbon Fibres (CF) are used as a reinforcing material from past few decades. Carbon Fibres are reinforced in Metal matrix composites (MMC), Ceramic matrix composites (CMC) & polymer matrix composites (PMC). Numerous Research work was done on Carbon Fiber Reinforced Polymer Composites (CFRP), but Carbon Fiber Reinforced Metal Matrix Composites (CFMMC) & Carbon Fiber Reinforced Ceramic Matrix Composites (CF-CMC) have wide scope to explore. This Paper reviews effect of Carbon Fibre reinforcement on Mechanical, Tribological and Morphological Properties of various Metal Matrix Materials. This paper also presents various processing techniques of Carbon Fibre Reinforced Composite Material.
Effect of fire retardancy materials in fibre reinforced composite plate for false ceilings- A Review
Authors: Rawal Shannay , Ramachandran M.
Published: May 2020

The use of fillers in composite material development and manufacturing has been in commercial use for decades. These fillers induce and/or enhance desirable characteristics in the composite matrix. Flammability is a major deterrent contributing to the reduced scope of utility of completely biodegradable composites. The ability of any material to act as a flame retardant is influenced not only by explicit factors such as the material’s melting temperature and thermal degradation factor, but also by various implicit factors such as the multiple transformations taking place in the material and the compounds that are generated due to the material’s exposure to elevated temperatures. The paper studies and compares the mechanism of fire retardancy of four popular fillers and aims to determine their effectiveness in introducing fire retardancy in biodegradable false ceiling materials. The results show that the properties of fire retardancy can be measured in terms of heat release rates, limiting oxygen indexes and thermogravimetric analyses. Final comments are on the testing standards used to check fire retardancy
Friction Stir Welding Processing, Materials and its Applications.
Authors: shimpi Rajendra , Sandesh Kumar Cheruku , katarane Rajnish
Published: May 2020

Friction stir welding (FSW) is solid state welding process for joining the two similar or dissimilar materials. Friction stir welding process is alternative joining process for thin plates and pipes. In this process non consumable tool is used to join two work faces by friction. FSW process is energy efficient and environment friendly process. In this paper summery of research work done by researchers for Friction stir welding process is presented. The aftermath of this work is to elaborate the overview of numerical analysis and overview of process parameters like tool tip angle, Tool geometry; Tool and joint Materials and Joint design. FSW process can be used for joining different materials. In current research the materials used for experimentation by different researches and its applications are summarized. All the vital factors are covered here for making the process for improvement of effectiveness/cost reduction. After refining all the process, researcher has found a scope in joining the different / alternative joining process, in different sectors.
Finite Element Analysis for Time Varying Mesh Stiffness behavior of different shapes of spalling
Authors: Lodwal Akhilesh , Tiwari Ashesh
Published: May 2020

Time Varying gear mesh stiffness is the variation of stiffness for the one contact period of a gear pair. Spalling on gear tooth is one of the most common defects in gear transmission. The loss of surface materials due to tooth spall reduces the Time-Varying Mesh Stiffness (TVMS) of the gear pair. The time varying mesh stiffness is the change in mesh stiffness for a gear pair in one contact period. The evaluation of the TVMS of the pair of gear tooth under gear tooth spalling conditions may be useful in finding its dynamic behavior or instant change in TVMS behavior may be the signal of fault developed. The potential energy method is used for analytical calculation of time varying mesh stiffness of the gear. The tooth spall may be of any shape and in this paper we have assumed the spall to be circular, triangular and elliptical and conducted analytical calculation to find TVMS and compare with healthy gear pair. The same gear pair with three shape of spall and modelled and verified through finite element analysis. The data may be used for further analysis. Also a number of shape may be modelled in future.