bluuebunny/crossref_metadata_2025 huggingface dataset:
Special issue on ontologies and standards for intelligent systems: editorial
Authors: Olszewska Joanna Isabelle , Bermejo-Alonso Julita , Sanz Ricardo
Published: May 2022

Day by day, new intelligent systems and autonomous machines are being developed to help and assist humans in a myriad of activities ranging from smart manufacturing to smart cities. Such new-generation intelligent systems need to work in teams and communicate with humans and other agents/robots to share information and coordinate activities. Furthermore, there is an increasing demand from government agencies and the private sector alike to use Unmanned Aerial Vehicles (UAVs), Unmanned Ground Vehicles (UGVs), Unmanned Surface Vehicles (USVs), and Autonomous Underwater Vehicles (AUVs) for tasks including search and rescue, surveillance, and monitoring. As these intelligent systems have to interact with humans in several scenarios involving multi-agent collaboration, data collection, and decision-making, it is urgent to discuss the technical as well as the ethical aspects in their design and function. Hence, ontology-based models for this Robotics and Automation (R&A) domain have the potential to enable a clear communication among the different intelligent systems and stakeholders, the formulations of standards, and the building of AI-based and robotics systems with full alignment with what stakeholders expect from these intelligent systems, in terms of economical benefits and enhanced human well-being.
Dealing with the populist radical right in parliament: mainstream party responses toward the Alternative for Germany
Authors: Heinze Anna-Sophie
Published: May 2022

In recent years, populist radical right parties (PRRPs) have continued to establish themselves in parliaments across Europe. However, there is little research on party responses in parliaments. This article explores how mainstream parties have dealt with the Alternative for Germany (AfD) in state parliaments. Its contribution is twofold: theoretically, it links the existing literature on party responses to the parliamentary arena and proposes a comprehensive framework for analyzing party responses in parliament, distinguishing between the formal and the policy level. Moreover, it tries to understand the variation of responses by emphasizing three important factors: party ideology, the government–opposition divide, and the federal structure of parties. Empirically, the article explores the crucial variation of response patterns toward the AfD at the subnational level, which is often neglected in the study of PRRPs. The results show that party responses reflect an ongoing learning process with no ‘magic formula’ in sight. Overall, the article underlines the importance of party responses in the initial phase for the PRRPs’ impact and offers substantial theoretical and empirical impetus for future research.
Media portrayal of mental health at the 2020 Tokyo Olympic and Paralympic Games
Authors: Keal Jennifer , McCabe Thomas , Wright Jade , Renshaw Patrick
Published: May 2022

Abstract. Introduction: The media coverage of high-profile sporting events can bring increased pressure to athletes’ psychological wellbeing. There may be speculation regarding athletes’ mental state before, during and after competition potentially impacting on both the athlete’s wellbeing and public perception of the individual if a negative tone is attached to an article. As mental health understanding and literacy develop, media reporting of elite athlete mental health may contribute to shaping of opinions and help seeking behaviour. Thus, we have aimed to understand and analyse the tone and content of media reporting on a high-profile sporting event using qualitative methods to explore key aspects of the articles sampled. Methods: We selected two UK broadsheet newspapers available online (The Guardian and The Telegraph) and identified all text articles including the terms “Mental Health” and “Olympics” or “Paralympics” published between 23rd July 2019 and 30th November 2021. We selected articles relevant to the Tokyo 2020 Olympic and Paralympic Games and including mental health as a subject. Relevant articles were read in full, and we conducted a thematic analysis to explore how mental health was portrayed. Results: 581 results were generated from our initial search. Following screening and removal of irrelevant articles, we had 95 articles for analysis. We identified four themes relating to portrayal of mental health: Pressure, impact of COVID, Lack of specific diagnostic terms, and athletes as humans. Conclusion: Media portrayal of mental health at the Tokyo Games was generally positive and portrayed athletes as relatable, inspiring, and “human” rather than superhuman. Reporting particularly focused on athlete-specific factors in mental health conditions and the pressures of high-level competition.
An Integration of Numerical Modeling and Paleoenvironmental Analysis Reveals the Effects of Embankment Construction on Long‐Term Salt Marsh Accretion
Authors: Pannozzo N. , Smedley Rachel K. , Chiverrell Richard C. , Carnacina Iacopo , Leonardi Nicoletta
Published: May 2022

There are still numerous uncertainties over the influence of anthropogenic interventions on salt marsh dynamics. This study uses the Ribble Estuary as a test case and an integrated approach of numerical modeling and paleoenvironmental analysis to investigate the contribution of embankment construction to long‐term marsh accretion. Accretion rates derived using optically stimulated luminescence dating (OSL) were combined with a multi‐proxy paleoenvironmental investigation on sediment cores extracted from the salt marsh, the mobile seafloor of the central Irish Sea and the river catchment area. These analyses provided a first evolutionary perspective on the Ribble Estuary preceding any management interventions. The paleoenvironmental analyses were then compared to simulations conducted using the hydrodynamic model Delft3D to investigate the effects of embankment construction on estuarine hydrodynamics and morphodynamics of the salt marsh over the period constrained by the OSL. The numerical simulations showed that embankments were responsible for an overall intensification of the ebb currents in the system which promoted sediment export. The paleoenvironmental analyses showed that the marsh has been accreting at a rate of 4.61 to 0.86 cm yr−1 over the last ca. 190 years and that the high sedimentation rate was caused by a naturally high rate of sediment supply. The model‐data integration showed that the effects of the embankment construction on sediment transport did not compromise the long‐term resilience of the salt marsh because of the high rates of sediment supply and the river dredging which enhanced the flood dominance of the tide near the tidal flat.
Coherency of Lightning Sferics
Authors: Bai X. , Füllekrug M.
Published: May 2022

The amplitudes of lightning sferics are commonly used for data analyses, for example, in lightning location networks. This contribution investigates the coherency of lightning sferics, which is calculated from the phase of the analytic complex signal. The complex signal is obtained from the Hilbert transform with the recorded signal as the input signal. This analytic signal is composed of amplitudes with corresponding phases. Rigorous selection criteria are applied to ensure that consistent events are used to calculate distance‐dependent average sferics waveforms which are summarized in waveform banks for the amplitude and coherency. The impulse response to lightning flashes is derived from an averaged waveform which is used to detect individual lightning events. It is shown that the coherency waveform bank is in general agreement with the amplitude waveform bank, that is, the relative arrival times of the ground and sky waves. The coherency waveform bank exhibits the same number of skywaves on the logarithmic scale, but a less attenuated ground wave when compared to the amplitude waveform bank. The results of this study show that the phase of sferics offers additional information to amplitudes, which could potentially be used for the interferometric lightning location with long‐range lightning detection networks.
Energetic Charged Particle Fluxes Relevant to Ganymede's Polar Region
Authors: Paranicas C. , Mauk B. H. , Kollmann P. , Clark G. , Haggerty D. K. , Westlake J. , Liuzzo L. , Masters A. , Cassidy T. A. , Bagenal F. , Bolton S.
Published: May 2022

The JEDI instrument made measurements of energetic charged particles near Ganymede during a close encounter with that moon. Here we find ion flux levels are similar close to Ganymede itself but outside its magnetosphere and on near wake and open field lines. But energetic electron flux levels are more than a factor of 2 lower on polar and near‐wake field lines than on nearby Jovian field lines at all energies reported here. Flux levels are relevant to the weathering of the surface, particularly processes that affect the distribution of ice, since surface brightness has been linked to the open‐closed field line boundary. For this reason, we estimate the sputtering rates expected in the polar regions due to energetic heavy ions. Other rates, such as those related to radiolysis by plasma and particles that can reach the surface, need to be added to complete the picture of charged particle weathering.
Unidentified major p-type source in SnSe: Multivacancies
Authors: Nguyen Van Quang , Trinh Thi Ly , Chang Cheng , Zhao Li-Dong , Nguyen Thi Huong , Duong Van Thiet , Duong Anh Tuan , Park Jong Ho , Park Sudong , Kim Jungdae , Cho Sunglae
Published: May 2022

Tin selenide (SnSe) is considered a robust candidate for thermoelectric applications due to its very high thermoelectric figure of merit, ZT, with values of 2.6 in p-type and 2.8 in n-type single crystals. Sn has been replaced with various lower group dopants to achieve successful p-type doping in SnSe with high ZT values. A known, facile, and powerful alternative way to introduce a hole carrier is to use a natural single Sn vacancy, VSn. Through transport and scanning tunneling microscopy studies, we discovered that VSn are dominant in high-quality (slow cooling rate) SnSe single crystals, while multiple vacancies, Vmulti, are dominant in low-quality (high cooling rate) single crystals. Surprisingly, both VSn and Vmulti help to increase the power factors of SnSe, whereas samples with dominant VSn have superior thermoelectric properties in SnSe single crystals. Additionally, the observation that Vmulti are good p-type sources observed in relatively low-quality single crystals is useful in thermoelectric applications because polycrystalline SnSe can be used due to its mechanical strength; this substance is usually fabricated at very high cooling speeds.
Heat transfer control using a thermal analogue of coherent perfect absorption
Authors: Li Ying , Qi Minghong , Li Jiaxin , Cao Pei-Chao , Wang Dong , Zhu Xue-Feng , Qiu Cheng-Wei , Chen Hongsheng
Published: May 2022

Recent investigations on non-Hermitian physics have unlocked new possibilities to manipulate wave scattering on lossy materials. Coherent perfect absorption is such an effect that enables all-light control by incorporating a suitable amount of loss. On the other hand, controlling heat transfer with heat may empower a distinct paradigm other than using thermal metamaterials. However, since heat neither propagates nor carries any momentum, almost all concepts in wave scattering are ill-defined for steady-state heat diffusion, making it formidable to understand or utilize any coherent effect. Here, we establish a scattering theory for heat diffusion by introducing an imitated momentum for thermal fields. The thermal analogue of coherent perfect absorption is thus predicted and demonstrated as the perfect absorption of exergy fluxes and undisturbed temperature fields. Unlike its photonic counterpart, thermal coherent perfect absorption can be realized for regular thermal materials, and be generalized for various objects.
Quadrivalent mosaic HexaPro-bearing nanoparticle vaccine protects against infection of SARS-CoV-2 variants
Authors: Kang Yin-Feng , Sun Cong , Sun Jing , Xie Chu , Zhuang Zhen , Xu Hui-Qin , Liu Zheng , Liu Yi-Hao , Peng Sui , Yuan Run-Yu , Zhao Jin-Cun , Zeng Mu-Sheng
Published: May 2022

Emerging SARS-CoV-2 variants of concern (VOCs) harboring multiple mutations in the spike protein raise concerns on effectiveness of current vaccines that rely on the ancestral spike protein. Here, we design a quadrivalent mosaic nanoparticle vaccine displaying spike proteins from the SARS-CoV-2 prototype and 3 different VOCs. The mosaic nanoparticle elicits equivalent or superior neutralizing antibodies against variant strains in mice and non-human primates with only small reduction in neutralization titers against the ancestral strain. Notably, it provides protection against infection with prototype and B.1.351 strains in mice. These results provide a proof of principle for the development of multivalent vaccines against pandemic and potential pre-emergent SARS-CoV-2 variants.
Unraveling the electronegativity-dominated intermediate adsorption on high-entropy alloy electrocatalysts
Authors: Hao Jiace , Zhuang Zechao , Cao Kecheng , Gao Guohua , Wang Chan , Lai Feili , Lu Shuanglong , Ma Piming , Dong Weifu , Liu Tianxi , Du Mingliang , Zhu Han
Published: May 2022

High-entropy alloys have received considerable attention in the field of catalysis due to their exceptional properties. However, few studies hitherto focus on the origin of their outstanding performance and the accurate identification of active centers. Herein, we report a conceptual and experimental approach to overcome the limitations of single-element catalysts by designing a FeCoNiXRu (X: Cu, Cr, and Mn) High-entropy alloys system with various active sites that have different adsorption capacities for multiple intermediates. The electronegativity differences between mixed elements in HEA induce significant charge redistribution and create highly active Co and Ru sites with optimized energy barriers for simultaneously stabilizing OH* and H* intermediates, which greatly enhances the efficiency of water dissociation in alkaline conditions. This work provides an in-depth understanding of the interactions between specific active sites and intermediates, which opens up a fascinating direction for breaking scaling relation issues for multistep reactions.
Structural identification of vasodilator binding sites on the SUR2 subunit
Authors: Ding Dian , Wu Jing-Xiang , Duan Xinli , Ma Songling , Lai Lipeng , Chen Lei
Published: May 2022

ATP-sensitive potassium channels (KATP), composed of Kir6 and SUR subunits, convert the metabolic status of the cell into electrical signals. Pharmacological activation of SUR2- containing KATP channels by class of small molecule drugs known as KATP openers leads to hyperpolarization of excitable cells and to vasodilation. Thus, KATP openers could be used to treat cardiovascular diseases. However, where these vasodilators bind to KATP and how they activate the channel remains elusive. Here, we present cryo-EM structures of SUR2A and SUR2B subunits in complex with Mg-nucleotides and P1075 or levcromakalim, two chemically distinct KATP openers that are specific to SUR2. Both P1075 and levcromakalim bind to a common site in the transmembrane domain (TMD) of the SUR2 subunit, which is between TMD1 and TMD2 and is embraced by TM10, TM11, TM12, TM14, and TM17. These KATP openers synergize with Mg-nucleotides to stabilize SUR2 in the NBD-dimerized occluded state to activate the channel.
Mechanical instability generated by Myosin 19 contributes to mitochondria cristae architecture and OXPHOS
Authors: Shi Peng , Ren Xiaoyu , Meng Jie , Kang Chenlu , Wu Yihe , Rong Yingxue , Zhao Shujuan , Jiang Zhaodi , Liang Ling , He Wanzhong , Yin Yuxin , Li Xiangdong , Liu Yong , Huang Xiaoshuai , Sun Yujie , Li Bo , Wu Congying
Published: May 2022

The folded mitochondria inner membrane-cristae is the structural foundation for oxidative phosphorylation (OXPHOS) and energy production. By mechanically simulating mitochondria morphogenesis, we speculate that efficient sculpting of the cristae is organelle non-autonomous. It has long been inferred that folding requires buckling in living systems. However, the tethering force for cristae formation and regulation has not been identified. Combining electron tomography, proteomics strategies, super resolution live cell imaging and mathematical modeling, we reveal that the mitochondria localized actin motor-myosin 19 (Myo19) is critical for maintaining cristae structure, by associating with the SAM-MICOS super complex. We discover that depletion of Myo19 or disruption of its motor activity leads to altered mitochondria membrane potential and decreased OXPHOS. We propose that Myo19 may act as a mechanical tether for effective ridging of the mitochondria cristae, thus sustaining the energy homeostasis essential for various cellular functions.
Experimental research on surface acoustic wave microfluidic atomization for drug delivery
Authors: Huang Qing-Yun , Le Ying , Hu Hong , Wan Zhi-jian , Ning Jia , Han Jun-Long
Published: May 2022

This paper demonstrates that surface acoustic wave (SAW) atomization can produce suitable aerosol concentration and size distribution for efficient inhaled lung drug delivery and is a potential atomization device for asthma treatment. Using the SAW device, we present comprehensive experimental results exploring the complexity of the acoustic atomization process and the influence of input power, device frequency, and liquid flow rate on aerosol size distribution. It is hoped that these studies will explain the mechanism of SAW atomization aerosol generation and how they can be controlled. The insights from the high-speed flow visualization studies reveal that it is possible by setting the input power above 4.17 W, thus allowing atomization to occur from a relatively thin film, forming dense, monodisperse aerosols. Moreover, we found that the aerosol droplet size can be effectively changed by adjusting the input power and liquid flow rate to change the film conditions. In this work, we proposed a method to realize drug atomization by a microfluidic channel. A SU-8 flow channel was prepared on the surface of a piezoelectric substrate by photolithography technology. Combined with the silicon dioxide coating process and PDMS process closed microfluidic channel was prepared, and continuous drug atomization was provided to improve the deposition efficiency of drug atomization by microfluidic.
SARS-CoV-2 RNA and antibody dynamics in a Dutch household study with dense sampling frame
Authors: Han Wanda G. H. , Swart Arno , Bonačić Marinović. Axel , Eggink Dirk , Reimerink Johan , Wijsman Lisa A. , van der Veer Bas , van den Brink Sharon , van den Brandt Anne-Marie , van Tol Sophie , Godeke Gert-Jan , Brouwer Fion , Hoogerwerf Marieke ,   The Dutch F. F. X.-COVID-19 Research Group, van Gageldonk-Lafeber Arianne B. , van der Hoek Wim , van den Hof Susan , Meijer Adam , Reukers Daphne F. M. , Reusken Chantal , Roof Inge , Rots Nynke , Reukers Daphne F. M. , Rots Nynke , Reusken Chantal , Meijer Adam
Published: May 2022

This study investigated the dynamics of SARS-CoV-2 infection and diagnostics in 242 household members of different ages and with different symptom severity after SARS-CoV-2 exposure early in the pandemic (March–April 2020). Households with a SARS-CoV-2 confirmed positive case and at least one child in the Netherlands were followed for 6 weeks. Naso (NP)- and oropharyngeal (OP) swabs, oral fluid and feces specimens were analyzed for SARS-CoV-2 RNA and serum for SARS-CoV-2-specific antibodies. The dynamics of the presence of viral RNA and the serological response was modeled to determine the sampling time-frame and sample type with the highest sensitivity to confirm or reject a SARS-CoV-2 diagnosis. In children higher viral loads compared to adults were detected at symptom onset. Early in infection, higher viral loads were detected in NP and OP specimens, while RNA in especially feces were longer detectable. SARS-CoV-2-specific antibodies have 90% probability of detection from 7 days (total Ig) and 18 days (IgG) since symptom onset. For highest probability of detection in SARS-CoV-2 diagnostics early in infection, RT-PCR on NP and OP specimens are more sensitive than on oral fluid and feces. For SARS-CoV-2 diagnostics late after infection, RT-PCR on feces specimens and serology are more valuable.
Direct RNA targeted in situ sequencing for transcriptomic profiling in tissue
Authors: Lee Hower , Marco Salas Sergio , Gyllborg Daniel , Nilsson Mats
Published: May 2022

Highly multiplexed spatial mapping of transcripts within tissues allows for investigation of the transcriptomic and cellular diversity of mammalian organs previously unseen. Here we explore a direct RNA (dRNA) detection approach incorporating the use of padlock probes and rolling circle amplification in combination with hybridization-based in situ sequencing chemistry. We benchmark a High Sensitivity Library Preparation Kit from CARTANA that circumvents the reverse transcription needed for cDNA-based in situ sequencing (ISS) via direct RNA detection. We found a fivefold increase in transcript detection efficiency when compared to cDNA-based ISS and also validated its multiplexing capability by targeting a curated panel of 50 genes from previous publications on mouse brain sections, leading to additional data interpretation such as de novo cell clustering. With this increased efficiency, we also found to maintain specificity, multiplexing capabilities and ease of implementation. Overall, the dRNA chemistry shows significant improvements in target detection efficiency, closing the gap to other fluorescent in situ hybridization-based technologies and opens up possibilities to explore new biological questions previously not possible with cDNA-based ISS.
An efficient ANFIS-EEBAT approach to estimate effort of Scrum projects
Authors: Arora Mohit , Verma Sahil , Kavita  , Wozniak Marcin , Shafi Jana , Ijaz Muhammad Fazal
Published: May 2022

Software effort estimation is a significant part of software development and project management. The accuracy of effort estimation and scheduling results determines whether a project succeeds or fails. Many studies have focused on improving the accuracy of predicted results, yet accurate estimation of effort has proven to be a challenging task for researchers and practitioners, particularly when it comes to projects that use agile approaches. This work investigates the application of the adaptive neuro-fuzzy inference system (ANFIS) along with the novel Energy-Efficient BAT (EEBAT) technique for effort prediction in the Scrum environment. The proposed ANFIS-EEBAT approach is evaluated using real agile datasets. It provides the best results in all the evaluation criteria used. The proposed approach is also statistically validated using nonparametric tests, and it is found that ANFIS-EEBAT worked best as compared to various state-of-the-art meta-heuristic and machine learning (ML) algorithms such as fireworks, ant lion optimizer (ALO), bat, particle swarm optimization (PSO), and genetic algorithm (GA).
BeCaked: An Explainable Artificial Intelligence Model for COVID-19 Forecasting
Authors: Nguyen Duc Q. , Vo Nghia Q. , Nguyen Thinh T. , Nguyen-An Khuong , Nguyen Quang H. , Tran Dang N. , Quan Tho T.
Published: May 2022

From the end of 2019, one of the most serious and largest spread pandemics occurred in Wuhan (China) named Coronavirus (COVID-19). As reported by the World Health Organization, there are currently more than 100 million infectious cases with an average mortality rate of about five percent all over the world. To avoid serious consequences on people’s lives and the economy, policies and actions need to be suitably made in time. To do that, the authorities need to know the future trend in the development process of this pandemic. This is the reason why forecasting models play an important role in controlling the pandemic situation. However, the behavior of this pandemic is extremely complicated and difficult to be analyzed, so that an effective model is not only considered on accurate forecasting results but also the explainable capability for human experts to take action pro-actively. With the recent advancement of Artificial Intelligence (AI) techniques, the emerging Deep Learning (DL) models have been proving highly effective when forecasting this pandemic future from the huge historical data. However, the main weakness of DL models is lacking the explanation capabilities. To overcome this limitation, we introduce a novel combination of the Susceptible-Infectious-Recovered-Deceased (SIRD) compartmental model and Variational Autoencoder (VAE) neural network known as BeCaked. With pandemic data provided by the Johns Hopkins University Center for Systems Science and Engineering, our model achieves 0.98 $$R^2$$

R
2

and 0.012 MAPE at world level with 31-step forecast and up to 0.99 $$R^2$$

R
2

and 0.0026 MAPE at country level with 15-step forecast on predicting daily infectious cases. Not only enjoying high accuracy, but BeCaked also offers useful justifications for its results based on the parameters of the SIRD model. Therefore, BeCaked can be used as a reference for authorities or medical experts to make on time right decisions.
Entomopathogenic fungus disrupts the phloem-probing behavior of Diaphorina citri and may be an important biological control tool in citrus
Authors: Maluta Nathalie , Castro Thiago , Lopes João Roberto Spotti
Published: May 2022

Citrus is among the most important fruit crops worldwide; however, numerous pests and diseases affect the orchards, increasing production costs. The psyllid Diaphorina citri, is a vector of the phloem-limited bacteria ‘Candidatus Liberibacter spp.’, the causal agent of Huanglongbing (HLB) disease. The lack of a cure for HLB requires management of the vector, mainly by intensive use of chemical insecticides, leading to the selection of resistant populations. Our study determined the effects of the entomopathogenic fungus Cordyceps fumosorosea on the probing behavior of D. citri at different time points after the fungus was applied by spraying. The electrical penetration graph technique was used to monitor the stylet activities of D. citri after application of the microbiological product. The effects were more pronounced between 30 and 96 h after the insects were sprayed, with significant disruption of the stylet activities related to the phloem and directly associated with the transmission of HLB. Our study indicated that the microbiological product Challenger®, with the active ingredient C. fumosorosea fungus, can significantly change the probing behavior of D. citri, may be helpful in more-sustainable management of the vector, and can be used to reduce the spread of HLB.
Quasiparticle dynamics by effective $$\pi $$-field distortion
Authors: Cassiano Tiago de Sousa Araújo , de Oliveira Neto Pedro Henrique , e Silva Geraldo Magela
Published: May 2022

Modeling dynamical processes of quasiparticles in low dimensional $$\pi $$
π
-conjugated systems is challenging due to electron-phonon coupling. We show that this interaction leads to linear potential energy terms in the lattice Lagrangian similar to a local “gravitational” field. The presence of quasiparticles deforms this field in a way analogous to a low-dimension solution of general relativity. Our calculations with analytical expressions for effective $$\pi $$
π
-fields yield the correct band structure and deliver proper time evolution of the quasiparticle’s properties. Furthermore, we report a sharp reduction in the dynamics computational time up to two orders of magnitude, a result that has major simulation implications.
Influences of dielectric constant and scan rate on hysteresis effect in perovskite solar cell with simulation and experimental analyses
Authors: Huang Jun-Yu , Yang You-Wei , Hsu Wei-Hsuan , Chang En-Wen , Chen Mei-Hsin , Wu Yuh-Renn
Published: May 2022

In this work, perovskite solar cells (PSCs) with different transport layers were fabricated to understand the hysteresis phenomenon under a series of scan rates. The experimental results show that the hysteresis phenomenon would be affected by the dielectric constant of transport layers and scan rate significantly. To explain this, a modified Poisson and drift-diffusion solver coupled with a fully time-dependent ion migration model is developed to analyze how the ion migration affects the performance and hysteresis of PSCs. The modeling results show that the most crucial factor in the hysteresis behavior is the built-in electric field of the perovskite. The non-linear hysteresis curves are demonstrated under different scan rates, and the mechanism of the hysteresis behavior is explained. Additionally, other factors contributing to the degree of hysteresis are determined to be the degree of degradation in the perovskite material, the quality of the perovskite crystal, and the materials of the transport layer, which corresponds to the total ion density, carrier lifetime of perovskite, and the dielectric constant of the transport layer, respectively. Finally, it was found that the dielectric constant of the transport layer is a key factor affecting hysteresis in perovskite solar cells.
Geochemical evidence for the internal migration of gas condensate in a major unconventional tight petroleum system
Authors: Wood James M. , Cesar Jaime , Ardakani Omid H. , Rudra Arka , Sanei Hamed
Published: May 2022

Unconventional petroleum systems go through multiple episodes of internal hydrocarbon migration in response to evolving temperature and pressure conditions during burial and uplift. Migrated fluid signatures can be recognized using stable carbon isotope and PVT compositional data from produced samples representative of in-situ petroleum fluids. Such samples, however, are seldom collected due to operational complexity and high cost. Here, we use carbon isotope and PVT data from co-produced hydrocarbon gas and liquid to provide evidence for widespread migration of gas-condensate in the Montney unconventional petroleum system of western Canada. Extended C1–C33isotopic profiles exhibit convex upward signatures with C4–C5maxima at low molecular weight, and increasing or nearly uniform signatures at high molecular weight. Additionally, recombination PVT compositional data show C6–C15condensate concentrations are higher than expected for unmodified oils. The combined convex upward and increasing or uniform isotopic signatures are interpreted as mixing profiles formed by the introduction of high-maturity gas-condensate (C1–C15) to shallower zones with in-situ hydrocarbon fluids of lower thermal maturity. The recognition of widespread gas-condensate migration adds to the complex history of internal hydrocarbon migration within the Montney tight-petroleum system including previously identified migration episodes of early oil and late-stage methane-rich gas.
Development of a textile based protein sensor for monitoring the healing progress of a wound
Authors: ElSaboni Yomna , Hunt John A. , Stanley Jessica , Moffatt Christine , Wei Yang
Published: May 2022

This article focuses on the design and fabrication of flexible textile-based protein sensors to be embedded in wound dressings. Chronic wounds require continuous monitoring to prevent further complications and to determine the best course of treatment in the case of infection. As proteins are essential for the progression of wound healing, they can be used as an indicator of wound status. Through measuring protein concentrations, the sensor can assess and monitor the wound condition continuously as a function of time. The protein sensor consists of electrodes that are directly screen printed using both silver and carbon composite inks on polyester nonwoven fabric which was deliberately selected as this is one of the common backing fabric types currently used in wound dressings. These sensors were experimentally evaluated and compared to each other by using albumin protein solution of pH 7. A comprehensive set of cyclic voltammetry measurements was used to determine the optimal sensor design the measurement of protein in solution. As a result, the best sensor design is comprised of silver conductive tracks but a carbon layer as the working and counter electrodes at the interface zone. This design prevents the formation of silver dioxide and protects the sensor from rapid decay, which allows for the recording of consecutive measurements using the same sensor. The chosen printed protein sensor was able to detect bovine serum albumin at concentrations ranging from 30 to 0.3 mg/mL with a sensitivity of $$0.0026 \mu $$

0.0026
μ

A/M. Further testing was performed to assess the sensor’s ability to identify BSA from other interferential substances usually present in wound fluids and the results show that it can be distinguishable.
Modified precordial lead ECG SafOne on electrocardiography recordings
Authors: Dewi Wan Nishfa , Safri Safri , Rosma Iswadi Hasyim
Published: May 2022

Adaptability in precordial lead placement is one of the sources of electrocardiography inaccuracy. The present experimental study aimed to investigate the modified precordial lead ECG SafOne on electrocardiography recordings. Fourteen subjects were selected using purposive sampling. All the artefacts that emerged in the ECG recording results from the subjects using both the modified precordial lead ECG SafOne and precordial lead standard ECG were measured and identified. Data were analysed using a t test to examine the difference in the artefacts from all ECG recordings. The electrocardiography recordings of males aged 21–25 years using modified precordial lead ECG SafOne showed that out of 168 precordial leads from 14 subjects, two indicated artefact images in lead II (1.19%) and three in lead III (1.79%). The statistical test showed no significant difference in terms of artefacts that emerged in the electrocardiography recording results from both standard ECG and modified precordial lead ECG SafOne (p = 0.096). The modified precordial lead ECG SafOne showed no significant effect on ECG recordings related to artefacts. Additionally, the precordial lead ECG SafOne had no substantial difference in the presence of artefacts compared to the standard ECG. Therefore, ECG SafOne was usable as an ECG precordial lead for electrocardiography recording.
Spatial distribution and source identification for heavy metals in surface sediments of East Dongting Lake, China
Authors: Yuan Yi , Liu Baolin , Liu Hao
Published: May 2022

Dongting Lake is one of the most important inland freshwater lakes in China. To investigate the spatial distribution and seasonal variation characteristics of heavy metals (Cr, Co, Cu, Zn, Cd, and Pb) in the lake, 53 surface sediment samples were collected in the East Dongting Lake (ED Lake) in the wet and dry seasons. Results show Cr, Co, Cu, Zn, Cd, and Pb contents were 1.7 (1.9), 1.8 (2.0), 2.9 (3.0), 1.9 (1.9), 11.7 (13.1), and 2.0 (2.2)-fold of their geochemical soil background values of Hunan province (China) in the wet (dry) season. Spatial and seasonal heterogeneity could be found in the distribution of Cr, Co, Cu, Zn, and Pb in the surface sediments. The enrichment factor (EF) suggested that Cd has reached severe enrichment in the sediment. The result of the geo-accumulation index ($${I}_{geo}$$

I

geo

) indicated that Cr, Co, Cu, Zn, and Pb were at levels corresponding to low contamination, and moderately to highly polluted with Cd. Multivariate statistical analysis including pearson correlation analysis and principal component analysis was used for the identification of potential sources of the heavy metals in the sediments. The results showed that Cu, Zn, and Pb from the sediments of the East Dongting Lake in the wet and dry seasons were possibly anthropogenic sources, such as emissions from mining and smelting while Al, Fe, and Cr are attributed for natural sources. Cd enrichment in the sediments is influenced by both natural factors, and human activities in local areas.
Heat transfer through hydrogenated graphene superlattice nanoribbons: a computational study
Authors: Dehaghani Maryam Zarghami , Habibzadeh Sajjad , Farzadian Omid , Kostas Konstantinos V. , Saeb Mohammad Reza , Spitas Christos , Mashhadzadeh Amin Hamed
Published: May 2022

Optimization of thermal conductivity of nanomaterials enables the fabrication of tailor-made nanodevices for thermoelectric applications. Superlattice nanostructures are correspondingly introduced to minimize the thermal conductivity of nanomaterials. Herein we computationally estimate the effect of total length and superlattice period ($$l_{p}$$

l
p

) on the thermal conductivity of graphene/graphane superlattice nanoribbons using molecular dynamics simulation. The intrinsic thermal conductivity ($$\kappa_{\infty }$$

κ
∞

) is demonstrated to be dependent on $$l_{p}$$

l
p

. The $$\kappa_{\infty }$$

κ
∞

of the superlattice, nanoribbons decreased by approximately 96% and 88% compared to that of pristine graphene and graphane, respectively. By modifying the overall length of the developed structure, we identified the ballistic-diffusive transition regime at 120 nm. Further study of the superlattice periods yielded a minimal thermal conductivity value of 144 W m−1 k−1 at $$l_{p}$$

l
p

 = 3.4 nm. This superlattice characteristic is connected to the phonon coherent length, specifically, the length of the turning point at which the wave-like behavior of phonons starts to dominate the particle-like behavior. Our results highlight a roadmap for thermal conductivity value control via appropriate adjustments of the superlattice period.
Influence of caffeine on the maximal isometric and concentric force produced by skinned fibers
Authors: Fukutani Atsuki , Kunimatsu Shiho , Isaka Tadao
Published: May 2022

Caffeine is one of the most famous and widely used ergogenic drugs, especially by athletes to improve sports performance. Caffeine is known to enhance muscle contraction by facilitating Ca2+ release from the sarcoplasmic reticulum. While the effect of caffeine on the cross-bridge dynamics has also investigated, the results is controversial. Therefore, the purpose of this study was to examine the influence of caffeine on cross-bridge dynamics using skinned fiber preparations from rabbit soleus (N = 19 in total). We performed isometric contractions at an average sarcomere length of 2.4 μm; thereafter, skinned fibers were shortened by 20% of the fiber length at a velocity of 0.1 mm/s (slow shortening) or 0.5 mm/s (fast shortening). The contractions were performed under both normal and caffeine-containing activating solution conditions to compare the isometric, slow concentric, and fast concentric forces between conditions. The isometric force did not differ between normal and caffeine-containing activating solution conditions. Similarly, the concentric forces obtained during the slow and fast shortening trials did not differ between conditions. We also measured the stiffness and the rate of force redevelopment (kTR) during the isometric contraction phase and found that these values were not different between normal and caffeine conditions. Based on these results, we conclude that the influence of caffeine on cross-bridge dynamics is negligible, and the ergogenic effect of caffeine, from the view of muscle contractility, is by facilitating Ca2+ release, as suggested in previous studies, and not by modulating the cross-bridge dynamics.
Phosphinoamido ligand supported heterobimetallic rare-earth metal–palladium complexes: versatile structures and redox reactivities
Authors: Du Jun , He Xiuyan , Hong Dongjing , Zhou Shuangliu , Fang Huayi , Cui Peng
Published: May 2022

Phosphinoamido ligand supported heterobimetallic rare-earth metal–palladium complexes show versatile structures and redox reactivities.
Biexcitons in CdSe nanoplatelets: geometry, binding energy and radiative rate
Authors: Macias-Pinilla David F. , Planelles Josep , Climente Juan I.
Published: May 2022

The biexciton ground state of colloidal nanoplatelets is calculated using Variational Quantum Monte Carlo. The binding energy dependence on spatial and dielectric confinement is elucidated. The 2D Haynes rule is violated.
O-Methylation of carboxylic acids with streptozotocin
Authors: Zeng Li-Yan , Liu Yang , Han Jiakun , Chen Jinhong , Liu Shuwen , Xi Baomin
Published: May 2022

Streptozotocin (STZ), DNA-alkylating agents in clinical, was newly explored as an agent for O-methyl esterification. With STZ, carboxylic acids, sulfonic acids and phosphorous acids were transformed into methyl esters in 4 hours at RT with good yield after simple workup.
Halogen-free instinct flame-retardant waterborne polyurethanes: composition, performance, and application
Authors: Yin Xuan , Li Liqi , Pang Haosheng , Luo Yunjun , Zhang Bing
Published: May 2022

Ideal halogen-free instinct flame-retardant waterborne polyurethanes have high flame-retardant efficiency, environmental friendliness, fine compatibility, and good thermostability.
Visualizing the mode of action and supramolecular assembly of teixobactin analogues in Bacillus subtilis
Authors: Morris Michael A. , Vallmitjana Alexander , Grein Fabian , Schneider Tanja , Arts Melina , Jones Chelsea R. , Nguyen Betty T. , Hashemian Mohammad H. , Malek Melody , Gratton Enrico , Nowick James S.
Published: May 2022

FRET microscopy experiments demonstrate supramolecular assembly of teixobactin molecules on Bacillus subtilis, providing further evidence that teixobactin is a supramolecular antibiotic.
Adaptive resource management for cognitive power line communication system
Authors: Fu Meiming , Wang Kang , Xu Bo , Xu Shuming , Wu Weihua
Published: May 2022

The authors investigate the adaptive resource allocation problem for cognitive power line communication system. The dynamic optimisation model is employed to maximise the energy‐aware network utility, which is defined as the difference of the weighted network throughput and the power consumption. Then, the authors decompose the stochastic optimisation into a traffic management subproblem and a joint subchannel and power allocation subproblem. Since the joint subchannel and power allocation subproblem is a mixed integer non‐linear optimisation, a continuity relaxation and Lagrange dual method is proposed to obtain the optimal solution of the mixed integer non‐linear optimisation subproblem. After that, the authors develop an adaptive power line communication resource allocation algorithm to cope with the power line communication network dynamics only according to the current network state information. Finally, we derive a trade‐off mechanism between network utility and network delay, in which the network delay is proportional to the control parameter V and the network utility is proportional to the parameter . Simulation results not only show the effectiveness but also verify the theoretical analysis of our proposed algorithm.
Optimal attitude consensus for multi rigid bodies network considered on the lie group SO(3) with connectivity preserving property
Authors: Mansourinasab Sara , Sojoodi Mahdi , Moghadasi S. Reza
Published: May 2022

This paper proposes distributed optimal attitude consensus control for single‐integrator multi rigid bodies with undirected network evolving on Special Orthogonal Group SO(3) while simultaneously guarantees the connectivity preservation property for agents using descent gradient algorithm. Since by Use of the Euclidean distance on Lie group as a measure of the energy of the state does not define and preserve the topology of SO(3); besides, solving the Hamilton–Jacobi–Bellman equation in optimal control problems shows difficulty implementing Euclidean distances and limits the results for SO(3) configuration state spaces. As a result, in this paper, the generic distance on SO(3) associated to the natural Riemannian metric structure is used. Using this structure, Firstly, a distributed potential function based consensus control law is applied to the system exploiting Riemannian distance on SO(3). Then, for relaxing some restrictive conditions, finite‐time convergence, and increasing the speed of convergence the kinematic optimal control on SO(3) is considered. Referring to the proposed potential function designed in the previous section, an inverse optimal attitude consensus control problem is considered, which is solved by an inverse optimal control method. Finally, the designed method validates via two simulation examples.
Data‐driven spatio‐temporal analysis of wildfire risk to power systems operation
Authors: Umunnakwe Amarachi , Parvania Masood , Nguyen Hieu , Horel John D. , Davis Katherine R.
Published: May 2022

Wildfires are natural or man‐made disasters that continuously threaten portions of the transmission and distribution grid, and thus the stability of the electric grid. This paper presents a two‐stage framework for assessing power system‐wildfire risk using a data‐driven wildfire prediction model. The first stage of the framework estimates the spatio‐temporal probability of potential wildfire ignition and propagation using a deep neural network in combination with the wildfire physical spread model. Analysis reveals similar spatial and temporal patterns between the model‐predicted wildfire ignition potential and actual wildfire ignition. Motivated by these observations, the second stage assesses the wildfire risk in the power grid operation in terms of potential loss of load by de‐energisation, through combining geospatial information system data of the power grid topology and the stochastic spatio‐temporal wildfire model developed in the first stage. The electric power utility applications introduced by the proposed framework are twofold: 1) a spatio‐temporal risk model for proactive de‐energisation against potential power system failure‐induced wildfire, and 2) a spatio‐temporal spreading model for optimal grid operations against exogenous wildfire. The proposed model, based on real‐world dataset, is demonstrated on the IEEE 24‐bus test system mapped to a study area in Northern California, while the results illustrate the proposed model can achieve the best performance in potential wildfire ignition detection (AUC of 0.995) compared to other baselines, as well as demonstrates the risk‐aware operation of the power system enabled by the proposed framework.
Graph convolutional network‐based image matting algorithm for computer vision applications
Authors: Dong Li , Liang Zheng , Wang Yue
Published: May 2022

Image matting plays a vital role in a variety of computer vision tasks including video editing and image fusion. Previously presented image matting algorithms might fail in producing favorable results since most of them concentrate on the similarity between the neighboring pixels while neglecting the corresponding spatial relationship. To address this issue, an end‐to‐end image matting framework through leveraging deep learning mechanism and graph theory is proposed. The proposed pipeline is a concatenation of one deep feature extraction component and a Graph Convolutional Network (GCN). The former part takes an image and its corresponding trimap as inputs and can generate the pixel‐wise features, which are then exploited as the input of the GCN locating at the latter part of the proposed framework. The GCN would refine the features for every pixel and predict the alpha matte outcome of the image. The approach outperforms a group of state‐of‐the‐art matting techniques as shown by the theoretical analysis and experimental results in terms of both accuracy and visual effects.