bluuebunny/crossref_metadata_2025 huggingface dataset:
Functional characterisation of substrate-binding proteins to address nutrient uptake in marine picocyanobacteria
Authors: Ford Benjamin A. , Sullivan Geraldine J. , Moore Lisa , Varkey Deepa , Zhu Hannah , Ostrowski Martin , Mabbutt Bridget C. , Paulsen Ian T. , Shah Bhumika S.
Published: December 2021

Marine cyanobacteria are key primary producers, contributing significantly to the microbial food web and biogeochemical cycles by releasing and importing many essential nutrients cycled through the environment. A subgroup of these, the picocyanobacteria (Synechococcus and Prochlorococcus), have colonised almost all marine ecosystems, covering a range of distinct light and temperature conditions, and nutrient profiles. The intra-clade diversities displayed by this monophyletic branch of cyanobacteria is indicative of their success across a broad range of environments. Part of this diversity is due to nutrient acquisition mechanisms, such as the use of high-affinity ATP-binding cassette (ABC) transporters to competitively acquire nutrients, particularly in oligotrophic (nutrient scarce) marine environments. The specificity of nutrient uptake in ABC transporters is primarily determined by the peripheral substrate-binding protein (SBP), a receptor protein that mediates ligand recognition and initiates translocation into the cell. The recent availability of large numbers of sequenced picocyanobacterial genomes indicates both Synechococcus and Prochlorococcus apportion >50% of their transport capacity to ABC transport systems. However, the low degree of sequence homology among the SBP family limits the reliability of functional assignments using sequence annotation and prediction tools. This review highlights the use of known SBP structural representatives for the uptake of key nutrient classes by cyanobacteria to compare with predicted SBP functionalities within sequenced marine picocyanobacteria genomes. This review shows the broad range of conserved biochemical functions of picocyanobacteria and the range of novel and hypothetical ABC transport systems that require further functional characterisation.
Dual‐mode linearity enhanced power amplifier with wideband AM‐PM compensation for 5–6‐GHz FeLAA applications
Authors: Li Jiajin , Zhang Zhihao , Zhang Gary
Published: December 2021

This letter presents a 5–6‐GHz dual‐mode power amplifier (PA) realized for further enhanced licensed assisted access application of downlink transmission. The output matching network with multiple harmonic traps and the wideband AM‐PM compensation technique are used in the design. To achieve high linear output power with less variation in the wide frequency range, different bias voltages of the first stage PA are set for dual‐mode operation. In the range 5–6 GHz, the PA delivers > 30 dBm saturated output power and reaches 24.4–24.8 dBm linear power at −35 dBc adjacent channel leakage ratio.
Experimental analysis of fractional order PIλDμ controller for improvement of power quality in smart grid environment
Authors: Sharma Monika , Rajpurohit Bharat Singh
Published: December 2021

Power electronics load is considered to be a strengthening factor that leads the system operators more concerned about power quality issues. Poor power quality can lead to distinctive operation of electrical components and devices, which may cause heavy economic loss to the customers and power network operators. An application of fractional order PIλDμ (FOPIλDμ) controller for power quality improvement in smart power distribution systems is presented here. Analytical design steps are presented for the FOPIλDμ controller. A genetic algorithm is used for tuning the control parameters of the FOPIλDμ controller optimally. The FOPIλDμ controller is employed and evaluated for shunt active power filter (APF) to filter out harmonics and improve reactive power compensation for non‐stationary, non‐linear load conditions for a smart power distribution system. Effectiveness of FOPIλDμ controller for instantaneous reactive power theory based PQ control algorithm applied to shunt APF is validated using a small‐scale laboratory experimental setup. The experimental results confirm the excellent performance of the FOPIλDμ controller in terms of its superior transient response, significant reduction in harmonic distortion, and improved reactive power compensation in a smart grid environment.
Frequency analysis of representative flood control water level stations in Puyang River
Authors: Wang Yang , Zhang Shuhui , Zhang Ziyi , Su Caichao , Ding Peng , Cao Guangtian
Published: December 2021

Puyang river basin is located in the north central part of Zhejiang Province, which is one of the most important river basins in Zhejiang Province. The lower reaches of Puyang River are easily influenced by tide in Hangzhou Bay and flood in Qiantang River. When Puyang river floods, it often meets Fuchun River and floods occur at the same time. The flood discharge of Puyang river is blocked and the water level rises and rises, which makes the Puyang River vulnerable to disaster. Water level frequency analysis is the basis of Puyang river planning and flood control plan. The representative flood control water level stations of Puyang River include Zhuji station and wenjiayan station. The frequency analysis of these representative stations is helpful to determine the water level of these key nodes under different frequencies, and to provide basic data for accurate flood control of Puyang River and ensure the safety of flood control.
Multi scale characteristics of Antarctic temperature change in January from 1982 to 2020
Authors: Huifang Guo , Fangfang Yin , Cao Guangtian
Published: December 2021

Antarctica is a sensitive area of global temperature change. Analyzing the temperature change in Antarctica can provide a basis for the analysis of global climate change The shared data provided by the automatic weather station plan are analyzed, and the relatively complete January temperature of Antarctic 8905 station from 1981 to 2020 is selected for analysis. Using the multi-scale analysis function of wavelet analysis, Morlet wavelet function is selected to carry out continuous wavelet transform on the daily temperature data, and the real part, modulus square and variance of continuous wavelet change are analyzed. It is found that the daily temperature of Antarctica is There are 14, 27, 72, 268, 380 and 665 day main periods for temperature changes. The trend analysis of wavelet transform coefficients under each period shows that the Antarctic temperature is in a high temperature period of 14, 27, 72, 268, 380 and 665 day periods in the years after 2021. The maximum temperature in January in Antarctica has a 20-year main period, and the minimum temperature has a 14-year and 23-year main period, The average value has a main cycle of 6 years, 14 years and 24 years.
Load Forecasting of Distributed Energy in Industrial Park and Its Investment Linkage Analysis
Authors: Yin Shuo , Lu Yao , Wang Shiqian , Chai Zhe , Jin Man , Chen Xing , Hu Jie
Published: December 2021

Power grid enterprises are changing their function orientation and profit model under the background of new power system reform. Vector autoregressive model used for industrial park to forecast load of distributed energy is created in this paper, which provides the data to the analysis of the investment environment of grid enterprises. We excavate the core influencing factors of grid investment in incremental distribution parks based on the linkage of grid investment influencing factors in system dynamics.
Adapting sustainability and energy efficiency principles to architectural education: A conceptual model proposal for the design studio sequence
Authors: Ceylan Salih
Published: December 2021

Architectural education is the first step into the professional career of an architect. It has strong connections with the profession itself regarding the technological trends and the needs of the society. Therefore, emerging challenges and developments in the world of architecture like environmental problems and sustainability issues need to be addressed by the educational programs of architecture. In addition to this, sustainable Development Goals (SDG) Program of United Nations puts an important responsibility on the shoulders of architectural educators. SDG includes both architectural and educational goals such as quality education, affordable and clean energy, sustainable cities and communities, and climate action. Accordingly, architectural education needs to be formed in a way to respond to the requirements of the contemporary global society. Design studio is the heart and core of architectural education. It is the place where all the theoretical and technical knowledge and skills gained in other courses become useful for the students to come up with design ideas and products. Additionally, design studios are not isolated environments. They form a series of courses by the consecutive repetition throughout the continuum of architectural education. Thus, they need to be treated as a developing sequence. Therefore, it is very important and valuable that the structure of the design studio sequence is improved and updated with suitable revisions towards emerging needs of the profession and society like the adaptation of sustainability principles, to reflect the dynamic character of architectural education itself. This paper presents a conceptual model proposal for the design studio sequence for the adaptation of sustainability principles to architectural education.
Analysis and Research on prefabricated building technology based on green low carbon environmental protection
Authors: Ni Wenjie
Published: December 2021

With the continuous progress of socialist construction, urban development is changing with each passing day, and various construction projects are continuously completed. At present, the State advocates low-carbon environmental protection and pays attention to ecological stability. Therefore, urbanization construction needs to be carried out under the concept of low-carbon environmental protection. The past construction technology has exposed many deficiencies in the continuous development and construction, such as serious waste of resources, neglect of environmental protection and low production efficiency, which has seriously hindered the transformation and development of the construction field, Prefabricated building technology has the characteristics of resource intensive, green environmental protection and high technical content, which perfectly meets the requirements of the development of the times. In the development of the times, prefabricated buildings gradually appear in people's sight, and are widely recognized by the public because of their green environmental protection, resource intensive and high technical content. Based on this, this paper mainly studies the prefabricated building technology under the current background of Green Low Carbon Environmental Protection.
Research and application of coal and gas outburst early warning system based on gas geological features
Authors: Zou Yunlong
Published: December 2021

The geological structure of coal mines has always been a dangerous object of attention in coal mine outburst prevention work. In order to realize coal mine safety information management and early warning of gas disasters, comprehensive use of gas geological theory, coal mine disaster warning theory, computer information technology and other analysis methods, considering the influence of geological structure, coal seam occurrence parameters, and gas parameters, an early warning indicator system for identifying the risk of coal and gas outbursts reflecting the geological characteristics of gas has been constructed. The coal and gas outburst risk identification and early warning system is constructed using the principle of multi-index step-by-step identification and extreme value determination, and it is applied on-site in the 3303 Measure Lane in the East Shaft Area of Sihe Mine. The research results show that the constructed early warning system can provide accurate early warning for the area (belt) affected by the geological structure by 10m, and can provide accurate early warning of coal and gas outbursts based on the outburst signs of gas geology such as the thickness of soft layers and changes in coal seam thickness. This technology provides effective support for coal mines to effectively prevent gas disasters and ensure coal mine production safety.
Discussion on numerical simulation method of salt-resistant polymer flooding in three types of reservoirs
Authors: Chen Jiqiang
Published: December 2021

According to the development characteristics of three types of reservoirs, this paper analyzes the main characteristics of salt-resistant polymer, and forms a highly targeted setting method for the key parameters of numerical simulation. At the same time, according to the actual situation of the salt-resistant test area, different injection parameter schemes are predicted, and the optimal design scheme is determined. Finally, the numerical simulation method of salt-resistant polymer flooding in three types of reservoirs is preliminarily formed.
Effect of packer design on hydraulic fracturing of coal seam
Authors: Klishin Sergei , Klishin Vladimir
Published: December 2021

The article addresses the issue of in-situ methane drainage from coal seams using multiple hydraulic fracturing. The authors undertake the stress–strain analysis of rock mass in the vicinity of a drainage borehole subjected to loading by sealing packers using the finite element method. The pressures at the packer and borehole wall contacts are calculated. It is shown how the length and spacing of the packers influence the values of the maximum axial tensile stresses on the borehole wall.
Phase transformations occurring during the formation of a welded joint from rail steel
Authors: Yuryev Alexey , Kozyrev Nikolay , Shevchenko Roman , Mikhno Alexey , Gutak Olga
Published: December 2021

The results of dilatometry, metallography and hardness testing of the decomposition process of supercooled austenite of R350LHT steel are presented. During continuous cooling and in isothermal conditions, continuous cooling transformation diagrams of supercooled austenite decomposition of steel R350LHT are constructed.
Research and development of a numerical model of methane and carbon dioxide filtration in a coal seam
Authors: Utkaev Eugeny , Makeev Maxim , Gerasimov Artem
Published: December 2021

The authors propose to inject СО2 into thin coal seams, which will not be developed and have no industrial value with the concomitant displacement of methane for the purpose of its utilization.
The NICU during COVID-19 Pandemic: Impact on Maternal Pediatric Medical Traumatic Stress (PMTS)
Authors: Raho Laura , Bucci Silvia , Bevilacqua Francesca , Grimaldi Teresa , Dotta Andrea , Bagolan Pietro , Aite Lucia
Published: December 2021

Objective The objective of this paper was to assess how hospital and outpatient clinic policies changes due to the coronavirus disease 2019 (COVID-19) pandemic impact pediatric medical traumatic stress (PMTS) symptoms in mothers of newborns admitted in a neonatal intensive care unit (NICU).

Study Design Observational case-control study included the comparison between mothers of infants admitted in the NICU at birth during the COVID-19 pandemic and mothers of infants admitted in the NICU before the COVID-19 pandemic. The control group was selected matching 1:1 with the study group for the following infants' clinical variables: gender, type of pathology, gestational age, weight at birth, day of recovery, ventilator time days, and associated malformations. The Italian version of the Impact of Event Scale—Revised (IES-R) was used as a measure of PMTS.

Result Mothers of the study group (50) scored significantly higher than mothers of the control group on three of four scales of IES-R (“IES-R total”: F = 6.70; p = 0.011; IES-R subscale “intrusion”: F = 7.45; p = 0.008; IES-R subscale “avoidance”: F = 8.15; p = 0.005). A significantly higher number of mothers in the study group scored above the IES-R total clinical cut-off compared with mothers of control group (72 vs. 48%; Chi2 = 6.00; p = 0.012).

Conclusion The COVID-19 pandemic acted as superimposed stress in mothers of newborns admitted in the NICU at birth determining high levels of PMTS. Clinicians and researchers should identify and implement novel strategies to provide family-centered care during the COVID-19 pandemic and beyond.

Key Points
Barriers to Adult Cochlear Implant Care in the United States: An Analysis of Health Care Delivery
Authors: Nassiri Ashley M. , Marinelli John P. , Sorkin Donna L. , Carlson Matthew L.
Published: December 2021

Persistent underutilization of cochlear implants (CIs) in the United States is in part a reflection of a lack of hearing health knowledge and the complexities of care delivery in the treatment of sensorineural hearing loss. An evaluation of the patient experience through the CI health care delivery process systematically exposes barriers that must be overcome to undergo treatment for moderate-to-severe hearing loss. This review analyzes patient-facing obstacles including diagnosis of hearing loss, CI candidate identification and referral to surgeon, CI evaluation and candidacy criteria interpretation, and lastly CI surgery and rehabilitation. Pervasive throughout the process are several themes which demand attention in addressing inequities in hearing health disparities in the United States.
Determining Cochlear Implant Candidacy in Adults: Limitations, Expansions, and Opportunities for Improvement
Authors: Zwolan Teresa A. , Basura Gregory
Published: December 2021

The safety, efficacy, and success of cochlear implants (CIs) are well established and have led to changes in criteria used by clinicians to determine who should receive a CI. Such changes in clinical decision-making have out-paced the slower-occurring changes that have taken place with regulatory bodies' and insurers' indications. We review the historical development of indications for CIs, including those of the U.S. Food and Drug Administration (FDA), Medicare, Medicaid, and private insurers. We report on expansion to include patients with greater residual hearing, such as those who receive Hybrid and EAS devices, and report on recent FDA approvals that place less emphasis on the patient's best-aided condition and greater emphasis on the ear to be treated. This includes expansion of CIs to patients with single-side deafness and asymmetric hearing loss. We review changes in the test materials used to determine candidacy, including transition from sentences in quiet to sentences in noise to the recent use of monosyllabic words and cognitive screening measures. Importantly, we discuss the recent trend to recommend CIs despite a patient not meeting FDA or insurers' indications (a practice known as “off-label”), which serves as attestation that current indications need to be updated.
4.1 Strain-Promoted Azide–Alkyne Cycloaddition (SPAAC): Background, Substrate Preparation, and Reactivity
Authors: Harris T. , Alabugin I. V.
Published: December 2021

This chapter discusses the creative synthetic approaches to azides and cycloalkynes, provides the rationale for controlling SPAAC reactivity through tuning cycloalkyne and azide backbone modifications, and highlights research on nitrone cycloadditions with cycloalkynes. This synthetic and knowledge toolset will help in the design of better cycloalkynes and their partners to answer challenging research questions and aid the development of new applications.
4.2 Applications of SPAAC and SPANC in Life Sciences
Authors: Janssen L. J. N. , Blanco-Ania D.
Published: December 2021

The bioorthogonal, strain-promoted azide–alkyne cycloaddition (SPAAC) and the strain-promoted alkyne–nitrone cycloaddition (SPANC) reactions have been used for conjugation with high affinity and specificity. In contrast to the cytotoxic copper-catalyzed cycloaddition, both SPAAC and SPANC are inert in biological environments. This chapter reviews the developments and applications of SPAAC and SPANC in life sciences reported since 2004, when Bertozzi et al. published the first bioorthogonal reaction.
Dissonant dementia: neuropsychiatry, awareness, and contradictions in cognitive decline
Authors: Fletcher James Rupert , Maddock Carol
Published: December 2021

This paper presents an analysis of contemporary neuropsychiatric meaning-making regarding dementia, encompassing distinct beliefs, practices and objects, and the peculiarities of its fragmented public manifestations. First, some core neuropsychiatric beliefs are discussed, arguing that the designation of those beliefs as exceptional truths engenders an imperialist ethic whereby the beliefs must be spread into other populations. Second, the enactment of this spread through dementia awareness is considered, whereby people are presented as having wrong beliefs to justify the promotion of alternative correct knowledge. Third, some emerging contradictions within neuropsychiatric dementia are outlined, as moves toward early diagnosis and “living well” sit uneasily beside notions of dementia as a frightening epidemic. The paper concludes that this produces dissonant dementia wherein contradictory meanings are held together. Finally, it is suggested that this dissonance will likely continue, underpinned by specific interests.
Study on bandgap vibration isolation of super-cell phononic crystals based on magnetorheological elastomers
Authors: Yu Guo-Jun , Wen Xi-Xi , Du Cheng-Bin , Wang Ling-Yun , Zhu Shao-Jie
Published: December 2021

A two-dimensional super-cell phononic crystal semi-active isolator based on magnetorheological elastomers is designed, which can be used for vibration isolation of mechanical devices at medium and high frequencies. The plane wave expansion method of the super-cell is introduced to model the dynamic characteristics of the proposed phononic crystal isolator. The influence of the constituent materials, dimension parameter of the super-cell, and magnetic field intensity on the band structure is investigated by the plane wave expansion method. The results show that the change of material will affect the bandgap frequency of the super-cell and the dimension parameter of the super-cell will affect the bandgap formation mechanism. It is worth pointing out that the bandgap frequency and width of the isolator can be adjusted by controlling the applied current of the magnetorheological elastomer. Therefore, this method offers a broad range of possibilities for phononic crystal vibration isolation design.
Digital health and precision prevention: shifting from disease-centred care to consumer-centred health
Authors: Canfell Oliver J. , Littlewood Robyn , Burton-Jones Andrew , Sullivan Clair
Published: December 2021

Digital disruption and transformation of health care is occurring rapidly. Concurrently, a global syndemic of preventable chronic disease is crippling healthcare systems and accelerating the effect of the COVID-19 pandemic. Healthcare investment is paradoxical; it prioritises disease treatment over prevention. This is an inefficient break–fix model versus a person-centred predict–prevent model. It is easy to reward and invest in acute health systems because activity is easily measured and therefore funded. Social, environmental and behavioural health determinants explain ~70% of health variance; yet, we cannot measure these community data contemporaneously or at population scale. The dawn of digital health and the digital citizen can initiate a precision prevention era, where consumer-centred, real-time data enables a new ability to count and fund population health, making disease prevention ‘matter’. Then, precision decision making, intervention and policy to target preventable chronic disease (e.g. obesity) can be realised. We argue for, identify barriers to, and propose three horizons for digital health transformation of population health towards precision prevention of chronic disease, demonstrating childhood obesity as a use case. Clinicians, researchers and policymakers can commence strategic planning and investment for precision prevention of chronic disease to advance a mature, value-based model that will ensure healthcare sustainability in Australia and globally.
Bringing organisations together during a pandemic: the case of an intersectoral community support group
Authors: Gardiner Shirley-Anne , Martin Priya
Published: December 2021

In early 2020, the COVID-19 pandemic emerged, posing multiple challenges to healthcare organisations and communities. The Darling Downs region in Queensland, Australia had its first positive case of COVID-19 confirmed in March 2020, which created understandable anxiety in the community. The Vulnerable Communities Group (VCG) was established to address this anxiety through open lines of communication to strengthen community resilience. This case study reports the evaluation of the VCG, plus lessons learned while establishing and running an intersectoral group, with stakeholders from more than 40 organisations, in response to the COVID-19 pandemic. An anonymous online survey with closed and open-ended questions was administered to participants. Data were subject to descriptive statistical tests and content analysis. Four categories were developed from the free text data for reporting: ‘Knowledge is power’, ‘Beating isolation through partnerships and linkages’, ‘Sharing is caring’, and ‘Ripple effects’. Whilst open communication and collaboration are always essential, they can be critically important during times of crisis. The VCG initiative is one example of tackling the challenges of the COVID-19 pandemic through bringing the community together. What is known about the topic? The COVID-19 pandemic has caused immense strain on the global community. It has thrust healthcare professionals and community leaders into an unforeseen situation, with little information being available on how to effectively deal with the pandemic to negate its effects. What does this paper add? This paper reports on the establishment and evaluation of the Vulnerable Communities Group (VCG) in the Toowoomba, Darling Downs region of Queensland, Australia in response to the COVID-19 pandemic, using a community of practice framework. It provides insight into how to establish and retain an intersectoral community of practice group during rapidly changing and challenging times, such as during the COVID-19 pandemic. What are the implications for practitioners? Practitioners can use a community of practice framework to establish and evaluate an intersectoral group, as described in our paper, to enhance community connectedness to reduce isolation and share information and resources to help negate the challenges caused by the COVID-19 pandemic.
Forest bird abundance can vary with cross-scale interactions involving climate, exurban cover and forest patch size
Authors: Chaudhary Anand , Gutzwiller Kevin J.
Published: December 2021

Abstract Context Climate and land use are among the most important drivers of global biodiversity change, and they may be operating at different spatial scales. The effects of cross-scale interactions (CSIs) between these drivers on avian abundance are poorly understood. Aims Our primary objective was to assess whether the abundances of eight forest bird species in the eastern United States were significantly associated with CSIs involving four subregional climate variables (breeding- and pre-breeding-season temperature and precipitation) and two landscape variables (percentage exurban cover and forest patch size). Methods For North American Breeding Bird Survey routes in six U.S. Environmental Protection Agency Level II ecoregions, we measured subregional climate variables within species maximum natal dispersal distances, and we measured landscape variables within species median natal dispersal distances. Using Akaike’s information criterion and negative-binomial regression, we compared the fits of 21 a priori competing models separately for each of the eight species, and separately for percentage exurban cover and forest patch size (8 × 2 = 16 model sets). Key results Total abundances during 2009–2013 of all eight species were associated with CSIs, which were informative in nine of the 16 best-supported models. The informative CSIs in the best-supported models involved all four subregional climate and both landscape variables. These results were evident after we accounted analytically for various methodological and environmental covariates, including within-scale interactions, that may otherwise have obscured the effects of CSIs. In some models, CSIs were more influential than were the associated additive effects, similar within-scale interactions, or other environmental variables, whereas in other models they were not. The associations between species abundances and CSIs were species-specific. Conclusions CSIs among global drivers of change may be common, and failure to identify CSI effects may result in misleading bird−landscape models. Implications Understanding how CSIs modify the effects of variables at different spatial scales may be crucial for effective broad-scale management of declining species. Conservation attention to species that are presently common but declining in abundance may help avoid extirpation in parts of their geographic ranges.
Honeycomb Lattice in Metal-Rich Chalcogenide Fe2Te
Authors: Guan Jia-Qi , Wang Li , Wang Pengdong , Ren Wei , Lu Shuai , Huang Rong , Li Fangsen , Song Can-Li , Ma Xu-Cun , Xue Qi-Kun
Published: December 2021

Two-dimensional honeycomb crystals have inspired intense research interest for their novel properties and great potential in electronics and optoelectronics. Here, through molecular beam epitaxy on SrTiO3(001), we report successful epitaxial growth of metal-rich chalcogenide Fe2Te, a honeycomb-structured film that has no direct bulk analogue, under Te-limited growth conditions. The structural morphology and electronic properties of Fe2Te are explored with scanning tunneling microscopy and angle resolved photoemission spectroscopy, which reveal electronic bands cross the Fermi level and nearly flat bands. Moreover, we find a weak interfacial interaction between Fe2Te and the underlying substrates, paving a newly developed alternative avenue for honeycomb-based electronic devices.
Enhanced Thermoelectric Properties of Cu
x
Se (1.75≤ x ≤2.10) during Phase Transitions
Authors: Yue Zhongmou , Zhao Kunpeng , Chen Hongyi , Qiu Pengfei , Chen Lidong , Shi Xun
Published: December 2021

Coupling of a phase transition to electron and phonon transports provides extra degree of freedom to improve the thermoelectric performance, while the pertinent experimental and theoretical studies are still rare. Particularly, the impaction of chemical compositions and phase transition characters on the abnormal thermoelectric properties across phase transitions are largely unclear. Herein, by varying the Cu content x from 1.75 to 2.10, we systemically investigate the crystal structural evolution, phase transition features, and especially the thermoelectric properties during the phase transition for Cu
x
Se. It is found that the addition of over-stoichiometry Cu in Cu
x
Se could alter the phase transition characters and suppress the formation of Cu vacancies. The critical scatterings of phonons and electrons during phase transitions strongly enhance the Seebeck coefficient and diminish the thermal conductivity, leading to an ultrahigh dimensionless thermoelectric figure of merit of ∼1.38 at 397 K in Cu2.10Se. With the decreasing Cu content, the critical electron and phonon scattering behaviors are mitigated, and the corresponding thermoelectric performances are reduced. This work offers inspirations for understanding and tuning the thermoelectric transport properties during phase transitions.
Post-Newtonian gravitational and scalar waves in scalar-Gauss–Bonnet gravity
Authors: Shiralilou Banafsheh , Hinderer Tanja , Nissanke Samaya M , Ortiz Néstor , Witek Helvi
Published: December 2021

Gravitational waves emitted by black hole binary inspiral and mergers enable unprecedented strong-field tests of gravity, requiring accurate theoretical modeling of the expected signals in extensions of general relativity. In this paper we model the gravitational wave emission of inspiralling binaries in scalar Gauss–Bonnet gravity theories. Going beyond the weak-coupling approximation, we derive the gravitational waveform to relative first post-Newtonian order beyond the quadrupole approximation and calculate new contributions from nonlinear curvature terms. We also compute the scalar waveform to relative 0.5PN order beyond the leading −0.5PN order terms. We quantify the effect of these terms and provide ready-to-implement gravitational wave and scalar waveforms as well as the Fourier domain phase for quasi-circular binaries. We also perform a parameter space study, which indicates that the values of black hole scalar charges play a crucial role in the detectability of deviation from general relativity. We also compare the scalar waveforms to numerical relativity simulations to assess the impact of the relativistic corrections to the scalar radiation. Our results provide important foundations for future precision tests of gravity.
Spacetime entanglement entropy of de Sitter and black hole horizons
Authors: Mathur Abhishek , Surya Sumati , X Nomaan
Published: December 2021

We calculate Sorkin’s manifestly covariant entanglement entropy

S

for a massive and massless minimally coupled free Gaussian scalar field for the de Sitter horizon and Schwarzschild de Sitter horizons, respectively, in d > 2. In de Sitter spacetime we restrict the Bunch–Davies vacuum in the conformal patch to the static patch to obtain a mixed state. The finiteness of the spatial

L

2

 norm in the static patch implies that

S

is well defined for each mode. We find that

S

for this mixed state is independent of the effective mass of the scalar field, and matches that of Higuchi and Yamamoto (2018 Phys. Rev. D 98 065014), where, a spatial density matrix was used to calculate the horizon entanglement entropy. Using a cut-off in the angular modes we show that

S
∝

A

c

, where A

c
is the area of the de Sitter cosmological horizon. Our analysis can be carried over to the black hole and cosmological horizon in Schwarzschild de Sitter spacetime, which also has finite spatial

L

2

 norm in the static regions. Although the explicit form of the modes is not known in this case, we use the boundary conditions of Qiu and Traschen (2020 Class. Quantum Grav.
37 135012) for a massless minimally coupled scalar field, to find the mode-wise

S

b
,
c

, where b, c denote the black hole and de Sitter cosmological horizons, respectively. As in the de Sitter calculation we see that

S

b
,
c

∝

A

b
,
c

after taking a cut-off in the angular modes.
Experimental investigations on rotation–vibration energy transfer in H2–N2 collisions
Authors: Nie Kunpu , Liu Jing , Xing Jun , Alghazi Abai
Published: December 2021

We investigated the rotational–vibrational impact energy transfer processes in a H2–N2 gas mixture system. The stimulated Raman pumping technique was used to excite H2 molecules to the (1, 7) high rotational states. The population of the H2(1, 7) level was verified by the coherent anti-Stokes Raman (CARS) spectra, the total pressure of the mixture was maintained at 500 Torr and nitrogen with different molar ratios was filled in the sample cell. The collisional deactivation rate coefficients of the excited state H2(1, 7) with H2 and N2 were obtained by fitting the experimental data with the Stern–Volmer equation. The multi-quantum near-resonant rotational relaxation process of H2(1, 7) colliding with N2 was confirmed by the time-resolved CARS profile measurements of H2(v = 1, J = 7, 5, 3) after the excitation of H2(1, 7). The results can provide data reference for atomic and molecular physics, atomic and molecular collisions, rotation and vibration excitation calculation, etc.
Interpretability of deep convolutional neural networks on rolling bearing fault diagnosis
Authors: Yang Huixin , Li Xiang , Zhang Wei
Published: December 2021

Despite the rapid development of deep learning-based intelligent fault diagnosis methods on rotating machinery, the data-driven approach generally remains a ‘black box’ to researchers, and its internal mechanism has not been sufficiently understood. The weak interpretability significantly impedes further development and application of the effective deep neural network-based methods. This paper contributes to understanding the mechanical signal processing of deep learning on the fault diagnosis problems. The diagnostic knowledge learned by the deep neural network is visualized using the neuron activation maximization and the saliency map methods. The discriminative features of different machine health conditions are intuitively observed. The relationship between the data-driven methods and the well-established conventional fault diagnosis knowledge is confirmed by the experimental investigations on two datasets. The results of this study can benefit researchers on understanding the complex neural networks, and increase the reliability of the data-driven fault diagnosis model in real engineering cases.
Deep learning model for imbalanced multi-label surface defect classification
Authors: Liu Yang , Yuan Yachao , Liu Jing
Published: December 2021

Automatic defect classification is vital to ensure product quality, especially for steel production. In the real world, the amount of collected samples with labels is limited due to high labor costs, and the gathered dataset is usually imbalanced, making accurate steel defect classification very challenging. In this paper, a novel deep learning model for imbalanced multi-label surface defect classification, named ImDeep, is proposed. It can be deployed easily in steel production lines to identify different defect types on the steel’s surface. ImDeep incorporates three key techniques, i.e. Imbalanced Sampler, Fussy-FusionNet, and Transfer Learning. It improves the model’s classification performance with multi-label and reduces the model’s complexity over small datasets with low latency. The performance of different fusion strategies and three key techniques of ImDeep is verified. Simulation results prove that ImDeep accomplishes better performance than the state-of-the-art over the public dataset with varied sizes. Specifically, ImDeep achieves about 97% accuracy of steel surface defect classification over a small imbalanced dataset with a low latency, which improves about 10% compared with that of the state-of-the-art.
A novel flexible hydrogel electrode with a strong moisturizing ability for long-term EEG recording
Authors: Shen Gencai , Gao Kunpeng , Zhao Nan , Yi Zhiran , Jiang Chunpeng , Yang Bin , Liu Jingquan
Published: December 2021

Objective. A novel flexible hydrogel electrode with a strong moisturizing ability was prepared for long-term electroencephalography (EEG) monitoring. Approach. The hydrogel was synthesized by polymerizing the N-acryloyl glycinamide monomer. And a proper amount of glycerin was added to the hydrogel to increase the moisture retention ability of the electrodes. The hydrogel shows high mechanical properties, and the liquid in the hydrogel produces a hydrating effect on the skin stratum corneum, which could decrease the contact impedance between skin and electrode. In addition, the installation of hydrogel electrode is very convenient, and the skin of the subject does not need to be abraded. Main results. Scanning electron microscope images show that there are a large number of micropores in the hydrogel, which provide storage space for water molecules. The average potential drift of the hydrogel electrode is relatively low (1.974 ± 0.560 µV min−1). The average contact impedance of hydrogel electrode in forehead region and hair region are 6.43 ± 0.84 kΩ cm2 and 13.15 ± 3.72 kΩ cm2, respectively. The result of open/closed paradigm, steady-state visual evoked potentials, and P300 visual evoked potential show that hydrogel electrode has excellent performance. Compared with the hydrogel without glycerin, the moisture retention ability of hydrogel containing glycerin was greatly improved. Significance. Compared with standard Ag/AgCl wet electrode, hydrogel electrode is more convenient to install and has strong moisture retention ability, which makes it have great potential in daily life for long-term EEG recording.
Magnetic properties of CrFeCoNi based high entory alloy
Authors: Yin Junqi , Eisenbach Markus , Daene Makrus , Malcolm Stocks G.
Published: December 2021

Monte Carlo simulations are performed on three high entropy alloys: Cr0.25Fe0.25Co0.25Ni0.25, Cr0.2Fe0.2Co0.2Ni0.2Pd0.2, and Cr0.2Mn0.2Fe0.2Co0.2Ni0.2, with exchange interactions extracted from The ab initio Korringa-Kohn-Rostoker method combined with the coherent potential approximation calculations. Using finite size scaling analyses, we estimate the magnetic phase transition temperature for the four component alloy to be 108(2) K, and although the individual critical exponents are different from 3D Heisenberg universality class, the reduced exponent follows Suzuki weak universality. With the additional Palladium component, the transition temperature elevates to about 200 K. In contrast, we find no magnetic order for the five component alloy with Manganese at any finite temperatures.
Design and Optimization of Star Recognition Algorithm Based on Hierarchical CNN
Authors: Lu Wentao , Hua Gengxin , Zhao Yunfu , Zhou Jiantao
Published: December 2021

With the rapid-development of AI technology, artificial intelligence algorithms for the aerospace applications have shown very good simulation performance in many areas. Among the spaceborne application fields, star identification can be seen as a typical pattern recognition process. It’s also the key part of attitude determination of the satellites, which requires the algorithm to be robust and efficient due to the limited computing and storing resources of the spaceborne computers. Nevertheless, most of the previous algorithms are not possible to be applied in practical due to the reasons above. This article proposes a strategy of constructing ‘net-structure’ images of stars to build the datasets for training and testing. Besides, a hierarchical convolutional neural network(CNN) with a small size is also designed. It performs good results on robustness and efficiency in the experiments. In the end, a method of fusing the Conv layers and the batch normalization (BN)layers is also adopted to further accelerate the algorithm.
Single object tracking algorithm in occlusion scene based on improved ECO
Authors: Xie Guorong , Jiang Rongqi , Qu Yi
Published: December 2021

To alleviate the occlusion problem in a single object tracking scene, this paper proposes an ECO-MHDU object tracking algorithm with a more powerful anti-occlusion performance based on the ECO tracker. The algorithm first uses the pre-trained MobileNetV3 lightweight backbone network on the ImageNet dataset to replace the ResNet network in the ECO to increase the speed of the algorithm to obtain the shallow and deep feature information of the image, while effectively using the attention mechanism in the MobileNetV3 network to strengthen the algorithm’s ability to extract target features; secondly, use the DropBlock operation on the acquired feature map to generate a random continuous mask on the feature map channel to improve the algorithm’s learning of the global robust spatial structure information; finally, a confidence update strategy is introduced into the GMM sample generation space. To improve the quality of training samples, unreliable tracking states such as confidence detection and occlusion are designed to avoid updating the sample space with damaging information. Compared with the ECO algorithm, the ECO-MHDU algorithm proposed in this paper has a success rate of 68.0% on the occlusion attributes of the OTB100 dataset, which is 2.3% higher than the ECO algorithm, and the ECO-MHDU algorithm also showed the best performance on the entire dataset sequence, with a success rate of 69.3%.
Vehicle and pedestrian target detection in auto driving scene
Authors: Yu Wanbo , Ren Pengjie
Published: December 2021

To improve the target detection accuracy and speed of autonomous driving in various weather environments and small target traffic senarios,an improved YOLOV4 target detection model based on CSPDarknet45_G backbone network is proposed in this paper.By adding a new DBG module which consists of DArknetConv2D + BN + GELU activation function,this model is enhanced in generalization ability and accuracy. We also improved Res unit residual module to enhance shallow features fusing with deep feathers and reduced the number of neurons in the CSP module to simplify the module structure.The K-Means++ clustering algorithm is introduced to obtain the size of the prior box used for target detection to satisfy the data set in this paper. In the captured target vehicle image data set, the model detection result shows that the improved YOLOV4 model achieve an average detection accuracy of 90.45%, a recall of 94.37%, and an FPS of 50 frames per second when the IOU is taken as 0.5, which meet the real-time and accuracy of the detection task in this paper.
Tumor imaging diagnosis analysis based on improved KNN algorithm
Authors: Wang Cailing , Li LeiChao , He SuQiang , Zhang Jing
Published: December 2021

As a simple, effective and non-parameter analysis method, knn is widely used in text classification, image recognition, etc. [1]. However, this method requires a lot of calculations in practical applications, and the uneven distribution of training samples will directly lead to a decrease in the accuracy of tumor image classification. To solve this problem, we propose a method based on dynamic weighted KNN to improve the accuracy of classification, which is used to solve the problem of automatic prediction and classification of medical tumor images based on image features and automatic abnormality detection. According to the classification of tumor image characteristics, it can be divided into two categories: benign and malignant. This method can assist doctors in making medical diagnosis and analysis more accurately. The experimental results show that this method has certain advantages compared with the traditional KNN algorithm.
Fractional strong matching preclusion of some Cartesian product graphs
Authors: Zhu Bo , Zhang Shumin , Ye Chenfu
Published: December 2021

The fractional strong matching preclusion number of a graph is the minimum number of edges and vertices whose deletion leaves the resulting graph without a fractional perfect matching. In this paper, we obtain the fractional strong matching preclusion number for the Cartesian product of a graph and a cycle. As an application, the fractional strong matching preclusion number for torus networks is also obtained.
The influence of color temperature mismatch in star simulator on positioning accuracy and magnitude measurement by star sensor
Authors: Wang Zhiyong , Liu Shishen , Sun Hao , Zhang Jingjing , Li Ruyou , Liu Chen
Published: December 2021

During the calibrating of star sensor, the calibration accuracy is greatly affected by the mismatch between the color temperature of the light and the to-be-measured star, which further affects the attitude measurement accuracy. This paper studied the near-infrared spectra of stars with different color temperatures, and analyzed the errors on star positioning and magnitude measurement of star sensor due to the color temperature mismatch. The results showed that in the central field of view, the spot centroid deviation caused by spectral mismatch is smaller than that in the edge field of view.And the defocus of the imaging surface also affects the spot centroid deviation. Besides, when calibrating with 6000K color temperature light, the maximum measurement error can reach -1.9126 magnitude.