bluuebunny/crossref_metadata_2025 huggingface dataset:
Corrigendum to: Improved region-specific emission factors for enteric methane emissions from cattle in smallholder mixed crop: livestock systems of Nandi County, Kenya
Authors: Ndung’u P. W. , Bebe B. O. , Ondiek J. O. , Butterbach-Bahl K. , Merbold L. , Goopy J. P.
Published: August 2020

National greenhouse-gas (GHG) inventories in most developing countries, and in countries in Sub-Saharan Africa in particular, use default (Tier I) GHG emission factors (EFs) provided by the Intergovernmental Panel on Climate Change (IPCC) to estimate enteric methane (CH4) emissions from livestock. Because these EFs are based on data primarily from developed countries, there is a high degree of uncertainty associated with CH4 emission estimates from African livestock systems. Accurate Tier II GHG emission reporting from developing countries becomes particularly important following the Paris Climate agreement made at COP21, which encourages countries to mitigate GHG emissions from agricultural sources. In light of this, the present study provides improved enteric CH4 emission estimates for cattle in Nandi County, Western Kenya, representing a common livestock production system found in East Africa. Using the data from measurements of liveweight and liveweight change, milk production and locomotion collected from 1143 cattle in 127 households across 36 villages over three major agro-ecological zones covering a full year, we estimated total metabolic energy requirements. From this and assessments of digestibility from seasonally available feeds, we estimated feed intake and used this to calculate daily CH4 production by season, and, subsequently, created new EFs. Mean EFs were 50.6, 45.5, 28.5, 33.2 and 29.0 kg CH4/head.year for females (>2 years), males (>2 years), heifers (1–2 years), young males (1–2 years) and calves (4 emissions in some African livestock systems.
Roost selection in concrete culverts by the large-footed myotis (Myotis macropus) is limited by the availability of microhabitat
Authors: Gorecki Vanessa , Rhodes Monika , Parsons Stuart
Published: August 2020

The large-footed myotis (Myotis macropus) is a specialist trawling bat with flexible roosting behaviour, being able to switch between caves, tree hollows and artificial roosts such as bridges, tunnels and culverts. However, little is known about how this species selects culvert roost sites in urban landscapes where hollows may be limited or absent. We surveyed 57 concrete culverts and found 21 M. macropus roosts comprising day and maternity roost sites; 305 bats were captured. Colony sizes averaged 20.6 ± 17.7 (range = 4–49) for maternity roosts and 2.0 ± 0.8 (range = 1–3) for day roosts. Roost culverts differed significantly from available culverts predominantly in terms of availability of microhabitat (lift holes and crevices). Roost culverts had lift holes that had greater cavity dimensions than available culverts and crevices were found only at roost culverts. Culverts containing microhabitat were a limited resource in this urban landscape and so increasing their availability may provide more urban roost sites for this specialist species.
Finding the neural correlates of collaboration using a three-person fMRI hyperscanning paradigm
Authors: Xie Hua , Karipidis Iliana I. , Howell Amber , Schreier Meredith , Sheau Kristen E. , Manchanda Mai K. , Ayub Rafi , Glover Gary H. , Jung Malte , Reiss Allan L. , Saggar Manish
Published: August 2020

Significance

It is well-known that the presence of others drastically changes how we behave, yet a majority of social neuroscience studies are limited to single-person neuroimaging experiments. Using simultaneous imaging of multiple interacting brains (also known as hyperscanning), recent studies have started to examine the brain basis underlying social cognition beyond passive observation. Here we performed a three-person functional MRI hyperscanning study to investigate the brain-to-brain coupling using a social game of
Pictionary
. Our results highlight the importance of the theory-of-mind network, especially a brain region in the right temporo-parietal junction for improved triadic collaboration. Our work lays the foundation for studying the brain basis of complex and truly social group interactions.
Archetypal landscapes for deep neural networks
Authors: Verpoort Philipp C. , Lee Alpha A. , Wales David J.
Published: August 2020

Significance

Deep neural networks have reached impressive predictive capability for many challenging tasks, yet it remains unclear why they work. Training neural networks involves minimizing a complex, high-dimensional, nonconvex loss function, yet, empirically, it proves possible to produce useful models without rigorous global optimization. To provide insight into this observation, we analyze the structure of the loss-function landscape of deep neural networks and show that it features either a single funnel or low barriers between minima. Such landscapes are relatively easy to optimize and are qualitatively different from the energy landscape of a structural glass. More generally, our results demonstrate how the methodology developed for exploring molecular energy landscapes can be exploited to extend our understanding of machine learning.
The duration of travel impacts the spatial dynamics of infectious diseases
Authors: Giles John R. , zu Erbach-Schoenberg Elisabeth , Tatem Andrew J. , Gardner Lauren , Bjørnstad Ottar N. , Metcalf C. J. E. , Wesolowski Amy
Published: August 2020

Significance

The spatial dynamics of infectious-disease spread are driven by the biology of the pathogen and the connectivity patterns among human populations. Models of disease spread often use mobile-phone calling records to calculate the number of trips made among locations in the population, which is used as a proxy for population connectivity. However, the amount of time people spend in a destination (trip duration) also impacts the probability of onward disease transmission among locations. Here, we developed models that incorporate trip duration into the mechanism of disease spread, which helps us understand how fast and how far a pathogen might spread in a human population.
Objective assessment of stored blood quality by deep learning
Authors: Doan Minh , Sebastian Joseph A. , Caicedo Juan C. , Siegert Stefanie , Roch Aline , Turner Tracey R. , Mykhailova Olga , Pinto Ruben N. , McQuin Claire , Goodman Allen , Parsons Michael J. , Wolkenhauer Olaf , Hennig Holger , Singh Shantanu , Wilson Anne , Acker Jason P. , Rees Paul , Kolios Michael C. , Carpenter Anne E.
Published: August 2020

Significance

We developed a strategy to avoid human subjectivity by assessing the quality of red blood cells using imaging flow cytometry and deep learning. We successfully automated traditional expert assessment by training a computer with example images of healthy and unhealthy morphologies. However, we noticed that experts disagree on ∼18% of cells, so instead of relying on experts’ visual assessment, we taught a deep-learning network the degradation phenotypes objectively from images of red blood cells sampled over time. Although training with diverse samples is needed to create and validate a clinical-grade model, doing so would eliminate subjective assessment and facilitate research. The time-based deep-learning strategy may also prove useful for other biological progressions, such as development and disease progression.
Universal motion of mirror-symmetric microparticles in confined Stokes flow
Authors: Georgiev Rumen N. , Toscano Sara O. , Uspal William E. , Bet Bram , Samin Sela , van Roij René , Eral Huseyin Burak
Published: August 2020

Significance

Particles of all shapes and sizes flowing through tight spaces are ever present in applications across length scales ranging from blood flow through tissue capillaries to industrial-scale processes. To date, separating these particles relies on methods employing external force fields. Currently underexplored, omnipresent fluid–structure interactions hold the key to shape-based separation independent of external intervention. By leveraging experiments, theory, and simulations, we show how the symmetry of a particle determines its overall trajectory: In particular, mirror-symmetric particles, both strongly and weakly confined, follow a universal path. We propose minimalistic scaling relations to describe how particle shape affects the parameterization of the universal path. These findings could be used to “program” particle trajectories in lab-on-a-chip devices and industrial separation processes.
A recurrent circuit implements normalization, simulating the dynamics of V1 activity
Authors: Heeger David J. , Zemlianova Klavdia O.
Published: August 2020

Significance

A family of recurrent circuit models is proposed to explain the dynamics of neural activity in primary visual cortex (V1). Each of the models in this family exhibits steady-state output responses that are already known to fit a wide range of experimental data from diverse neural systems. These models can recapitulate the complex dynamics of V1 activity, including oscillations (so-called gamma oscillations, ∼30 to 80 Hz). This theoretical framework may also be used to explain key aspects of working memory and motor control. Consequently, the same circuit architecture is applicable to a variety of neural systems, and V1 can be used as a model system for understanding the neural computations in many brain areas.
Multiple timescales of neural dynamics and integration of task-relevant signals across cortex
Authors: Spitmaan Mehran , Seo Hyojung , Lee Daeyeol , Soltani Alireza
Published: August 2020

Significance

The brain exhibits a tremendous amount of heterogeneity, and to make sense of this seemingly random system neuroscientists have explored various ideas to organize it into distinct areas, each performing certain computations. One such idea is the timescale at which neural response fluctuates. Here, we developed a comprehensive method to estimate multiple timescales in neural response and link these timescales to processing of task-relevant signals and behavioral adjustments. We found multiple types of timescales that increase across cortical areas in parallel while being independent of each other and of selectivity to task-relevant signals. Our results suggest that there are multiple independent mechanisms underlying generations of neural dynamics on different timescales.
Evaluating insecticide resistance across African districts to aid malaria control decisions
Authors: Moyes Catherine L. , Athinya Duncan K. , Seethaler Tara , Battle Katherine E. , Sinka Marianne , Hadi Melinda P. , Hemingway Janet , Coleman Michael , Hancock Penelope A.
Published: August 2020

Significance

Malaria control in Africa largely relies on the use of insecticides to prevent mosquitoes from transmitting the malaria parasite to humans; however, these mosquitoes have evolved resistance to these insecticides. To manage this threat to malaria control, it is vital that we map locations where the prevalence of resistance exceeds thresholds defined by insecticide resistance management plans. A geospatial model and data from Africa are used to predict locations where thresholds of resistance linked to specific recommended actions are exceeded. This model is shown to provide more accurate next-year predictions than two simpler approaches. The model is used to generate maps that aid insecticide resistance management planning and that allow targeted deployment of interventions that counter specific mechanisms of resistance.
Two-step release of kinase autoinhibition in discoidin domain receptor 1
Authors: Sammon Douglas , Hohenester Erhard , Leitinger Birgit
Published: August 2020

Significance

Receptor tyrosine kinases (RTKs) are proteins on the surface of animal cells that transmit signals into the cell. Binding of an extracellular signal protein to the RTK activates its intracellular enzyme (kinase). This process needs to be tightly controlled, as unwanted RTK activation can lead to disease. The discoidin domain receptors, DDR1 and DDR2, are unusual RTKs that are activated by a major structural protein, collagen. Here we show how the enzyme activity of DDR1 is inhibited by a protein segment outside of the kinase domain and how this inhibition is overcome by tyrosine phosphorylation. Our findings reveal an important regulatory mechanism of DDRs and open up avenues for inhibitor design in diseases caused by unwanted DDR signaling.
Genetic diversity of soil invertebrates corroborates timing estimates for past collapses of the West Antarctic Ice Sheet
Authors: Collins Gemma E. , Hogg Ian D. , Convey Peter , Sancho Leopoldo G. , Cowan Don A. , Lyons W. Berry , Adams Byron J. , Wall Diana H. , Green T. G. Allan
Published: August 2020

Significance

Changes in the extent of ice sheets through evolutionary timescales have influenced the connectivity of soil invertebrate populations across the Antarctic landscape. We use genetic divergences to estimate isolation times for soil invertebrates along the Transantarctic Mountains. Four species of Collembola (Arthropoda) each showed genetically distinct populations at locations likely isolated for millions of years. Two further species were less genetically diverse although also range restricted. Our genetic data corroborate climate reconstructions and estimates of past warm periods of reduced ice and absent ice shelf in the Ross Sea region, during which time open seaways would have facilitated dispersal of Collembola, and possibly other taxa.
Brain-wide structural and functional disruption in mice with oligodendrocyte-specificNf1deletion is rescued by inhibition of nitric oxide synthase
Authors: Asleh Jad , Shofty Ben , Cohen Nadav , Kavushansky Alexandra , López-Juárez Alejandro , Constantini Shlomi , Ratner Nancy , Kahn Itamar
Published: August 2020

Significance

This study assessed the effects of myelin decompaction on motor behavior and brain-wide structural and functional connectivity, and the effect of nitric oxide synthase inhibition byN-nitro-l-arginine methyl ester (L-NAME) on these imaging measures. We report that inducible oligodendrocyte-specific inactivation of theNf1gene, which causes myelin decompaction, results in reduced initial motor coordination. Using diffusion-based magnetic resonance imaging (MRI), we show reduced myelin integrity, and using functional MRI, we show reduced functional connectivity in awake passive mice. L-NAME administration results in rescue of the pathology at the mesoscopic level, as measured using imaging procedures that can be directly applied to humans to study treatment efficacy in clinical trials.
A mutation in POLR3E impairs antiviral immune response and RNA polymerase III
Authors: Ramanathan Aravind , Weintraub Michael , Orlovetskie Natalie , Serruya Raphael , Mani Dhivakar , Marcu Orly , Stepensky Polina , Weisblum Yiska , Djian Esther , Shaag Avraham , Revel-Vilk Shoshana , Fried Iris , Kotler Moshe , Rouvinski Alex , Wolf Dana , Elpeleg Orly , Jarrous Nayef
Published: August 2020

Significance

The innate immune system constitutes the host defense frontline against viruses. This system comprises several interrelated signal transduction pathways, one of which implicates the viral DNA sensor RNA polymerase (Pol) III. However, the link of this polymerase to innate immunity in humans remains largely unknown. Here, we describe a homozygous mutation (D40H) in the POLR3E gene, coding for a protein subunit of Pol III, in a child with disseminated viral infections and Langerhans cell histiocytosis. This mutation is related to diminished interferon induction and increased cell susceptibility to infection by cytomegalovirus. Strikingly, the D40H mutation leads to formation of functionally defective transcription complexes of Pol III. Our study links POLR3E and Pol III to an innate immundeficiency condition in humans.
Alterations of the gut ecological and functional microenvironment in different stages of multiple sclerosis
Authors: Takewaki Daiki , Suda Wataru , Sato Wakiro , Takayasu Lena , Kumar Naveen , Kimura Kimitoshi , Kaga Naoko , Mizuno Toshiki , Miyake Sachiko , Hattori Masahira , Yamamura Takashi
Published: August 2020

Significance

We have compared gut microbiomes in the different stages of multiple sclerosis (MS) based on both microbial and functional analyses using fecal samples. Together with microbial composition data, metagenomic functional and metabolite data revealed a reduced level of microbial butyrate and propionate biosynthesis in the gut of relapsing remitting MS (RRMS). On the other hand, in the gut of secondary progressive MS (SPMS), we revealed an enhancement in microbial DNA mismatch repair, which was consistent with excessive fecal oxidation shown in sulfur metabolomic analysis. As elevated oxidative stress is closely associated with chronic neuroinflammation and neurodegeneration, the present result opens a way to microbiome data-assisted management of MS, useful for prevention of disease progression.
Between vos and usted
Authors: López Alonzo Karen
Published: August 2020

This chapter examines how Nicaraguan Spanish
speakers alternate between vos and
usted to index power negotiations in
(a)symmetric exchanges during a baseball practice. The variation in
pronominal exchanges shows directionalities: certain pronoun usage
can mitigate, demonstrate solidarity, or empower commands. I
research (1) the direction
(voseo/ustedeo) of mitigation
of the message, (2) the relationship (symmetric/asymmetric) of
alternation between vos and usted,
and (3) how uses of ustedeo are redefined from
established definitions of “formality.” This study has a pragmatic
focus based on courtesy theory. Vos and
usted alternated actively, offering innovative
practices as acts of power. Speakers use polite alternatives when
familiarity and affect are negotiated through the use of
voseo or ustedeo as a
pragmatic value of the request.
Variation and pragmatic enrichment
Authors: García Christina
Published: August 2020

Dar + gerund is a periphrastic
benefactive found in the Spanish of highland Ecuador and southern
Colombia. Prior research has focused on the construction’s origin,
syntactic constraints, and politeness: the present study examines
the pragmatic restrictions of dar + gerund
declaratives. Using native speaker intuitions and heuristics from
previous studies, I show that the most significant implication
present is that it is not the sole responsibility of the agent to do
the task. Thus, Daniel dio lavando la ropa is
felicitous if Daniel is part of a group of people responsible for
washing the clothes or if it was someone else’s responsibility
entirely, but infelicitous if Daniel was solely responsible.
Español neutro and marketing in Latin American
and U.S. audiovisual media
Authors: Cipria Alicia
Published: August 2020

This chapter has a descriptive and a theoretical
aim. The descriptive aim involves elucidation of the term
neutro in different contexts and analysis of
phonetic/phonological features usually associated with the type of
“neutral” Spanish as marketed by global media conglomerates. The
theoretical aim is to link this Spanish “from nowhere” with issues
of standardization and with globalization-related concepts such as
anonymity, commodification, agency, and disembedding. Data come from
publicly available interviews of dubbing professionals, coaching
videos on “neutralization” of a local accent, and excerpts of TV
show dubbings previously outsourced by Miami-based conglomerates, in
tandem with Bogotá and Mexico DF, to other Latin American
countries.
Language policy and education in Peru
Authors: Salcedo Arnaiz Daniela
Published: August 2020

This chapter presents a state of the art in
language policy and education in Peru, focusing on the importance of
language ideologies when designing and applying policy. Within the
Peruvian context, I have selected three works published in the last
decade to give an account of certain common beliefs behind the
decision-making of the government and other institutions regarding
language in education. Next, based on some of the ideologies
presented by these scholars, I reflect both on the progress and the
challenges that policy-makers still need to face to create deep and
long-lasting change. If we do not discuss underlying language
ideologies in the educational and academic spheres and analyze them
critically in order to contest their biased and discriminatory
nature, they might change but popular mentalities will not.
Twenty years of Guaraní-Spanish bilingual education in
Paraguay
Authors: Gynan Shaw N.
Published: August 2020

The Paraguayan constitution instituted
Guaraní-Spanish bilingualism in 1992. Although law provides for
Guaraní literacy instruction with Spanish as a second language, the
de facto model for the two decades following officialization was one
of Spanish literacy instruction with Guaraní as a second language.
This model works well in bilingual districts; however, the 2002
Paraguayan census reported 1,319,777 monolingual Guaraní speakers,
and 146,618 households that identified as Guaraní-dominant. Test
results of over 300 third graders are incontrovertible: Spanish
literacy instruction with Guaraní as a second language produces
semilingualism (i.e., written production at less than half of
comprehension). Bringing Paraguayan education into line with legal
requirements is a priority for the sake of children’s academic
linguistic proficiency and the future of Guaraní.
A loss-of-function NUAK2 mutation in humans causes anencephaly due to impaired Hippo-YAP signaling
Authors: Bonnard Carine , Navaratnam Naveenan , Ghosh Kakaly , Chan Puck Wee , Tan Thong Teck , Pomp Oz , Ng Alvin Yu Jin , Tohari Sumanty , Changede Rishita , Carling David , Venkatesh Byrappa , Altunoglu Umut , Kayserili Hülya , Reversade Bruno
Published: August 2020

Failure of neural tube closure during embryonic development can result in anencephaly, one of the most common birth defects in humans. A family with recurrent anencephalic fetuses was investigated to understand its etiology and pathogenesis. Exome sequencing revealed a recessive germline 21-bp in-frame deletion in NUAK2 segregating with the disease. In vitro kinase assays demonstrated that the 7–amino acid truncation in NUAK2, a serine/threonine kinase, completely abrogated its catalytic activity. Patient-derived disease models including neural progenitor cells and cerebral organoids showed that loss of NUAK2 activity led to decreased Hippo signaling via cytoplasmic YAP retention. In neural tube–like structures, endogenous NUAK2 colocalized apically with the actomyosin network, which was disrupted in patient cells, causing impaired nucleokinesis and apical constriction. Our results establish NUAK2 as an indispensable kinase for brain development in humans and suggest that a NUAK2-Hippo signaling axis regulates cytoskeletal processes that govern cell shape during neural tube closure.
On the causal hierarchy of Lorentzian length spaces
Authors: Hau Luis Aké , Cabrera Pacheco Armando J , Solis Didier A
Published: August 2020

In this work we provide the full description of the upper levels of the classical causal ladder for spacetimes in the context of Lorenztian length spaces, thus establishing the hierarchy between them. We also show that global hyperbolicity, causal simplicity, causal continuity, stable causality and strong causality are preserved under distance homothetic maps.
Large magnetocaloric effect in LiLnP4O12 (Ln = Gd, Tb, Dy) single crystals
Authors: Petrov Dimitar N , Long Phan The , Koshkid’Ko Yu S , Ćwik J , Nenkov K
Published: August 2020

We have studied the magnetic and magnetocaloric (MC) properties of lithium lanthanide tetraphosphates LiLnP4O12 (Ln = Gd, Tb, Dy) single crystals (SCs) upon the magnetization (M) and heat-capacity (Cp) measurements. Detailed investigations in the temperature range T = 2–300 K indicate that all SCs exhibit paramagnetic (PM) character with effective PM moments close to those expected for free Ln
3+ ions. The magnetic contribution to Cp takes place strongly at temperatures below 20 K that enhances the values of the parameters characteristic for the MC effect. Under an applied field H = 50 kOe, the values of the maximum magnetic entropy change (|

Δ

S
m

max

|) at 2 K are about 27.6, 15.9 and 11.7 J kg−1 K−1 for Ln = Gd, Tb and Dy, respectively, corresponding to refrigerant capacity (RC) of 133 ∼ 254 J kg−1. Among the studied SCs, the maximum adiabatic temperature change (

Δ

T

a
d

max

) obtained for the system Ln = Gd at a field change H = 20 kOe is about 13 K, which can be achieved by using a permanent magnet. With the large values of |

Δ

S
m

max

|, RC and

Δ

T

a
d

max

, and the absence of magnetic hysteresis, LiLnP4O12 are considered as alternatively potential candidates for adiabatic magnetic refrigeration applications at sub-helium temperatures. It is believed that the different magnetic and MC properties among the LiLnP4O12 SCs are related to the ground-state nature and spin-orbit interaction of Ln
3+ ions.
Determination of the complex refractive index of compound semiconductor alloys for optical device modelling
Authors: Schygulla Patrick , Fuß-Kailuweit Peter , Höhn Oliver , Dimroth Frank
Published: August 2020

In this paper a method is presented to accurately and quickly interpolate a dataset of the complex refractive index of arbitrary compound semiconductors. The method is based on a parameter morphing algorithm which maps critical points of two endpoint materials with known optical parameter sets onto each other. Every desired intermediate material composition can be interpolated if the composition dependence of the band gap is known for the given material system. The accuracy and stability of the proposed procedure is validated experimentally using spectral ellipsometry and reflection measurements. Test samples of two III–V semiconductor material systems, AlGaAs and GaInAsP, with various compositions were grown using metalorganic vapour phase epitaxy and the morphed parameter sets are compared to corresponding measurement results. Modelling the absorption of a solar cell device and comparing it to the external quantum efficiency is presented as an application example of this method. The interpolation method is demonstrated to be a powerful tool for optical and electro-optical modelling of semiconductor structures if parameters of the complex refractive index are not available for the exact material composition.
The emergence of tunable negative electrocaloric effect in ferroelectric/paraelectric superlattices
Authors: Ji Ye , Chen W J , Zheng Yue
Published: August 2020

The electrocaloric effect in ferroelectrics provides a promising solid-state refrigeration technology to meet the urgent demand for heat management in the integrated circuits. Usually, ferroelectrics show a positive electrocaloric effect, i.e. the application of an electric field causes an increase in temperature. In contrast, the negative electrocaloric effect is also possible but much less explored. These two effects, if occur in the same system, could be combined to improve the cooling performance. Here we report the occurrence of both positive and negative electrocaloric effects in ferroelectric/paraelectric PbTiO3/SrTiO3 superlattice based on phase-field simulations. The superlattice is found to stabilize a variety of vortex dipole states (with the different number of vortex) when the PbTiO3 and SrTiO3 layers have suitable thicknesses. The unique response of these topological states to the external electric field gives rise to both positive and negative electrocaloric effect, and the latter is associated with the field-dependent vortex-to-polar state transformation. The multiplicity of the vortex dipole states brings tuning freedom for the optimization of electrocaloric properties. Moreover, the electrocaloric effect is also sensitive to the strength of the screening effect determined by the thickness of the SrTiO3 layer. We thus demonstrate a novel mechanism of negative electrocaloric effect in ferroelectrics with topological dipole states and indicates the screening effect as an effective way to engineer the electrocaloric performance.
Pixel-level detection and measurement of concrete crack using faster region-based convolutional neural network and morphological feature extraction
Authors: Li Shengyuan , Zhao Xuefeng
Published: August 2020

Crack characteristics are important indicator reflecting the safety status of concrete structures. Current pixel-level crack detection methods generally used several semantic segmentation networks. However, those semantic segmentation network-based methods need expensive pixel-level annotation of training and test images. To overcome these problems, this paper proposed a pixel-level detection and measurement of concrete crack using a faster region-based convolutional neural network (faster R-CNN) and morphological feature extraction techniques. The faster R-CNN is trained on a database including 4861 crack images, and, consequently, records with 90.91% average precision (AP). The trained faster R-CNN is used to detect cracks from backgrounds of images, and then the morphological feature extraction techniques are used to segment pixel-level cracks and measure crack maximum widths and lengths. Comparative study is conducted to examine the performance of the proposed approach using a fully convolutional network (FCN)-based method. The results show that the proposed method substantiates quite performances and can indeed detect and measure concrete crack in realistic situations.
High-performance metal-semiconductor-metal ZnSnO UV photodetector via controlling the nanocluster size
Authors: Huang Chun-Ying , Lin Tsai-Jung , Liao Pei-Chun
Published: August 2020

Solution processing of amorphous oxide semiconductors (AOS) is used for electronic and optoelectronic applications. However, the device performance is much lower than that for a device that is fabricated using vacuum processing. This study uses acetylacetone (acac) as an additive in the precursor solution to reduce the nanocluster size in a ZnSnO (ZTO) film. A metal-semiconductor-metal (MSM)-type UV photodetector (PD) is fabricated using as-prepared ZTO film. ZTO film that features a smaller nanocluster size, so more oxygen vacancies are induced, which produces more electrons and the photocurrent is increased. The surface at the metal/semiconductor interface is smoother so there is greater contact with fewer interface states and the dark current is decreased. An extremely high photo-to-dark current ratio (PDCR) of 1314 is achieved for a solution-processed ZTO MSM-type PD.
Quantitative modeling of bacterial quorum sensing dynamics in time and space*
Authors: Li Xiang , Qi Hong , Zhang Xiao-Cui , Xu Fei , Yin Zhi-Yong , Huang Shi-Yang , Wang Zhao-Shou , Shuai Jian-Wei
Published: August 2020

Quorum sensing (QS) refers to the cell communication through signaling molecules that regulate many important biological functions of bacteria by monitoring their population density. Although a wide spectrum of studies on the QS system mechanisms have been carried out in experiments, mathematical modeling to explore the QS system has become a powerful approach as well. In this paper, we review the research progress of network modeling in bacterial QS to capture the system’s underlying mechanisms. There are four types of QS system models for bacteria: the Gram-negative QS system model, the Gram-positive QS system model, the model for both Gram-negative and Gram-positive QS system, and the synthetic QS system model. These QS system models are mostly described by the ordinary differential equations (ODE) or partial differential equations (PDE) to study the changes of signaling molecule dynamics in time and space and the cell population density variations. Besides the deterministic simulations, the stochastic modeling approaches have also been introduced to discuss the noise effects on kinetics in QS systems. Taken together, these current modeling efforts advance our understanding of the QS system by providing systematic and quantitative dynamics description, which can hardly be obtained in experiments.
Phase-field simulation of superconductor vortex clustering in the vicinity of ferromagnetic domain bifurcations*
Authors: Mehdi Jafri Hasnain , Wang Jing , Yang Chao , Wang Jun-Sheng , Huang Hou-Bing
Published: August 2020

Superconductors and ferromagnets are highly non-compatible materials due to the natures of their respective electronic states. But when artificially brought together, they develop interesting characteristics, one of which, vortex clustering, is discussed here in this paper. Phase-field and micromagnetic simulations are performed to investigate the superconductor and ferromagnet bilayer, respectively. The ferromagnet with uniaxial anisotropy is observed to develop the maze domain, whereas the superconductor subjected to the influence of the ferromagnetic stray field displays a vortex pattern. Clustered vortices in superconductors at certain locations are observed to be precisely located over magnetic domain bifurcations. The enhanced out-of-plane stray field at bifurcations around the curved domain walls and the convergent Lorentz force due to screening currents in superconductor are attributed to the formation of clusters at bifurcation sites. Segregation of the inter-vortex spacing between straight and bifurcated domain is clearly observed. More importantly, inter-vortex spacing is predicted to serve as a precise tool to map local ferromagnet domain shapes.
A carbon monitoring system for mapping regional, annual aboveground biomass across the northwestern USA
Authors: Hudak Andrew T , Fekety Patrick A , Kane Van R , Kennedy Robert E , Filippelli Steven K , Falkowski Michael J , Tinkham Wade T , Smith Alistair M S , Crookston Nicholas L , Domke Grant M , Corrao Mark V , Bright Benjamin C , Churchill Derek J , Gould Peter J , McGaughey Robert J , Kane Jonathan T , Dong Jinwei
Published: August 2020

This paper presents a prototype Carbon Monitoring System (CMS) developed to produce regionally unbiased annual estimates of aboveground biomass (AGB). Our CMS employed a bottom-up, two-step modeling strategy beginning with a spatially and temporally biased sample: project datasets collected and contributed by US Forest Service (USFS) and other forestry stakeholders in 29 different project areas in the northwestern USA. Plot-level AGB estimates collected in the project areas served as the response variable for predicting AGB primarily from lidar metrics of canopy height and density (R2 = 0.8, RMSE = 115 Mg ha−1, Bias = 2 Mg ha−1). This landscape model was used to map AGB estimates at 30 m resolution where lidar data were available. A stratified random sample of AGB pixels from these landscape-level AGB maps then served as training data for predicting AGB regionally from Landsat image time series variables processed through LandTrendr. In addition, climate metrics calculated from downscaled 30 year climate normals were considered as predictors in both models, as were topographic metrics calculated from elevation data; these environmental predictors allowed AGB estimation over the full range of observations with the regional model (R2 = 0.8, RMSE = 152 Mg ha−1, Bias = 9 Mg ha−1), including higher AGB values (>400 Mg ha−1) where spectral predictors alone saturate. For both the landscape and regional models, the machine-learning algorithm Random Forests (RF) was consistently applied to select predictor variables and estimate AGB. We then calibrated the regional AGB maps using field plot data systematically collected without bias by the national Forest Inventory and Analysis (FIA) Program. We found both our project landscape and regional, annual AGB estimates to be unbiased with respect to FIA estimates (Biases of 1% and 0.7%, respectively) and conclude that they are well suited to inform forest management and planning decisions by our contributing stakeholders.

Social media abstract

Lidar-based biomass estimates can be upscaled with Landsat data to regionally unbiased annual maps.
Classical capacity of generalized Pauli channels
Authors: Siudzińska Katarzyna
Published: August 2020

Finding the classical capacity of a quantum channel is not easy, yet we are able to analytically calculate this capacity for new channels. We analyze the bounds of the Holevo capacity and classical capacity for the generalized Pauli channels. In particular, by generalizing earlier results for the Weyl channels, we obtain the lower and upper bounds of the Holevo capacity and show that, if these bounds coincide, the Holevo capacity is weakly additive. We also prove the weak additivity of the lower bound. Two new examples of the generalized Pauli channels with known classical capacity are presented. Finally, we relate the change rate of the classical capacity to the P-divisibility of Pauli channels.
Research on the Fiscal and Tax Policies of Low Carbon Leading China’s Development
Authors: Jinduo Hou
Published: August 2020

In recent years, the greenhouse effect, extreme weather, and other phenomena brought about by global warming have further intensified, and it has gradually become the focus of attention of the international community. Facing severe climate problems, reducing carbon dioxide and other greenhouse gas emissions has become an inevitable choice. With China’s economy towards high-quality development, it does not only face the constraints of resources but also needs to deal with environmental constraints. The low-carbon event should take into account economic development and environmental protection and help China’s economic transformation and upgrading. The low-carbon event should take into account economic development and environmental protection and help China’s economic transformation and upgrading. In the face of the greenhouse gas effect of carbon emissions, it is necessary to limit it to a reasonable range. And it is essential to implement reasonable and practical carbon reduction policies. Moreover, the study of China’s fiscal and taxation policies for carbon emission reduction has excellent demonstration significance for the developing countries, energy cooperation in the future, cooperation on climate change, and so on.
Prediction of the antifreeze of the concrete structure based on random forest and wavelet neural network
Authors: Tang Yangyi , Wu Xianguo , Chen Hongyu , Zeng Tiemei
Published: August 2020

The durability of concrete is the focus of research in the field of engineering, and the resistance of concrete is one of the important indicators of concrete durability. Based on the prediction of early resistance to concrete based on the random forest combined with the wavelet neural network algorithm, 12 factors affecting concrete antifreeze were selected from the ratio level of concrete material, and the relative dynamic elastic mode was used as the evaluation index of concrete resistance, and the importance evaluation and feature variable selection of influencing factors were used by random forest, and a concrete antifreeze prediction model based on RF-WNN (random forest-wave neural network) was established. The example analysis is carried out by taking the project project as an example, and the calculation of the wavelet neural network and BP neural network prediction model without the influence factor screening is compared to obtain the mean square root error and the fit superiority respectively. The results show that the prediction results of RF-WNN model are closer to the actual value and the prediction accuracy is higher, and the proposed RF-WNN prediction model provides an effective method for achieving concrete antifreeze prediction.
A neural network based method for sensitive frequency component analysis of cavitation fault
Authors: Yu Jiongmin , Fu Dongliang , Zhou Pu , Li Jiatong , Ye Fei , Shen Yufei
Published: August 2020

In General, the frequency feature of cavitation was obtained by comparing it with normal signal. However, when there were a large number of samples, it was difficult to analyse the sensitive features of cavitation fault effectively. So, a neural network based method for sensitive frequency component analysis of cavitation fault was proposed, and Empirical Mode Decomposition(EMD) method, Fourier Transform and neural network were used. Firstly, the raw vibration signal was decomposed to 5 Intrinsic Mode Function(IMF) components and the frequency spectrum of each component were computed. So, the dataset of raw signal was divided into 5 datasets which contained different frequency components. And a neural network was built, trained and tested by the different datasets. By comparing the diagnosis accuracy of the neural network, the sensitivity of different IMF was analysed. And it is verified that the method can effectively analyse the sensitive frequency components of cavitation faults, reduce the size of the neural network.
Research of NOx and PM10 pollutants in Cluj-Napoca with the mobile system for mitigating public health risks
Authors: Băldean D L , Andrei L , Borzan A I
Published: August 2020

The present research is conducted in order to show the possibilities of creating a smart and advanced mobile system capable of investigations regarding the chemical composition of the atmospheric air in the metropolitan areas using flexible technologies and some part of the existing infrastructure. Experimental measurements are made using a mobile station for data recording connected to the internet and with a link to the air quality stations. Taking into consideration the values of different chemical compounds within the atmospheric air, the data processing station may create a chemical map indicating the higher risk of air toxicity. Nitrogen oxides and particulate matter are some of the essential chemical pollutants generated these days by modern industries and transportation activities. By installing the proper technologies and networking capabilities on a current car the research team has made a practical investigation of actual chemical values in the metropolitan area of Cluj-Napoca by accessing the NO, NO2, NOx, and PM 10 data retrieving lines. Necessary changes in hourly retrieved data show that road traffic and other human activities do change the air quality level and its chemical composition. An air map is provided for some moments of the day, including the four stations in Cluj-Napoca city. The practical research is intended to present the technological capability and its embedding potential for the new series models of cars which may thus indicate a proper route in order to avoid critical points and to reduce the toxic chemical overload of some areas.
Friction induced heating properties of the polyamide/steel type contacts
Authors: Lates M T
Published: August 2020

The endurance and the life time of the mechanical transmissions are highly influenced by the functioning conditions and, not at least, by the materials that they are manufactured from. The increase of the endurance and functioning life time, corroborated with a friendly impact with the environment, is one of the main aims of the worldwide research areas of today. According to this, the development of new materials characterised by low costs and high endurance represents one of the solutions obtained by the specific scientific research. The paper investigates the friction induced heating properties of the polyamide/steel type contacts by considering dry friction conditions. It is studied the contact between a steel made pin and a PA46 and PTFE added PA46 polyamide made disk, under different testing conditions, depending on the rotational speed of the disk and the normal force, at the environmental temperature. The tests are achieved on a tribometer equipped with a pin-on-disc module and, as output, the friction coefficient is measured. Due to the friction is developed a heating of the local contact area. The heat is calculated according to the measured friction coefficient, the normal load and the relative sliding velocity. Finally there are given conclusions regarding the friction induced heating properties of the tested materials.
Study of Vulnerabilities in Designing and Using Automated Vehicles based on SWOT method for Chevrolet Camaro
Authors: Bec P , Borzan A I , Frunză M , Băldean D L , Berindei I
Published: August 2020

Travel sickness of the passenger, lack of human control over driving, high level of complexity in construction and programming, possibility of technical failure, limited or no driving engagement are just some of the possible vulnerabilities when using an automated or an autonomous vehicle. There are also important benefits and clear advantages such as more time for relaxing, resting, sleeping, reading, or working during the travel. Therefore is a “must”, to study the process of designing and using automated vehicles in order to outline vulnerabilities which may provide the mitigating solutions. As majority of the studies regarding vulnerabilities of the automated vehicles consist in fundamental research investigations a SWOT analyse of vulnerabilities in designing and using autonomous cars is thus necessary. The present work investigates methodological and designing aspects for researching the vulnerabilities in the process of developing and implementing automated driving, based on SWOT approach, simulation tools, practical measurement, experimental testing, sampling, graphical modelling, programming, and ethical considerations. Moreover, some aspects of the SWOT method led by multiple engineering and ethical problems are brought up and highlighted. Part of the data from conducted research concerning the designing and using autonomous vehicles made in a dynamic-based driving environment and with a real car are also applicable in sustaining the arguments.
The use of finite element analysis in studying deformations of parts clamped in machine tool devices
Authors: Stánáșel I , Tocuț P D , Veres R
Published: August 2020

Increasing the productivity and quality of products while reducing production costs are the main objectives of manufacturing companies in the market economy. For companies that produce parts using cutting processes, these objectives are strongly influenced, among other factors,by the devices used during the manufacturing process. Devices must allow the clamping of workpieces to be done in a short period of time, to have simple construction, to be cheap while positioning and installing errors to be minimal to ensure that the parts correspond to the manufacturing documentation. The calculation of clamping errors of workpieces and devices involves complex analysis, therefore in order to accurately determine these errors, data obtained from experiments, sometimes costly and difficult to be done, are used. This paper presents the clamping force calculation of a prismatic part, as well as the study of elastic deformations that appear by clamping it in the device, using finite element analysis.
Implementation in MATLAB Simulink of a basic electric vehicle
Authors: Moldovanu D
Published: August 2020

In order to have a better understanding of influencing factors when designing an electric vehicle, the author implemented a model in MATLAB Simulink of a basic electric vehicle taking into consideration several factors, with room for improvements and addons to further studies. The purpose was to have a basic model for teaching. The model takes into consideration the basic aerodynamics of the vehicle, the electric motor (implemented via transfer function), the vehicle velocity calculation from the sum of acting forces and validation of the model. Validation of the model was done by comparing the output data like vehicle velocity with the real measurements done by the manufacturer itself. After the validation, a PI controller was implemented, and two instances were compared. The author considers that students should learn by doing, especially when simulation-based design is easy to understand.