bluuebunny/crossref_metadata_2025_split huggingface dataset:
LkARF7 and LkARF19 overexpression promote adventitious root formation in a heterologous poplar model by positively regulating LkBBM1
Authors: Tao Gui-Yun , Xie Yun-Hui , Li Wan-Feng , Li Kui-Peng , Sun Chao , Wang Hong-Ming , Sun Xiao-Mei 
Published: April 2023

AbstractCuttage propagation involves adventitious root formation induced by auxin. In our previous study, Larix kaempferi BABY BOOM 1 (LkBBM1), which is known to regulate adventitious root formation, was affected by auxin. However, the relationship between LkBBM1 and auxin remains unclear. Auxin response factors (ARFs) are a class of important transcription factors in the auxin signaling pathway and modulate the expression of early auxin-responsive genes by binding to auxin response elements. In the present study, we identified 14 L. kaempferi ARFs (LkARFs), and found LkARF7 and LkARF19 bound to LkBBM1 promoter and enhanced its transcription using yeast one-hybrid, ChIP-qPCR, and dual-luciferase assays. In addition, the treatment with naphthalene acetic acid promoted the expression of LkARF7 and LkARF19. We also found that overexpression of these two genes in poplar promoted adventitious root formation. Furthermore, LkARF19 interacted with the DEAD-box ATP-dependent RNA helicase 53-like protein to form a heterodimer to regulate adventitious root formation. Altogether, our results reveal an additional regulatory mechanism underlying the control of adventitious root formation by auxin.
Cloud energy storage in power systems: Concept, applications, and technical challenges
Authors: Khezri Rahmat , Bahramara Salah , Mahmoudi Amin 
Published: April 2023

AbstractCloud energy storage (CES) in the power systems is a novel idea for the consumers to get rid of the expensive distributed energy storages (DESs) and to move to using a cloud service centre as a virtual capacity. Although the different characteristics and applications of the energy storages are reviewed in some papers, there is no review study on the CES concepts, formulations, applications, and challenges. Therefore, the main contribution of this paper is to review the applications of the CES and its technical challenges in the power systems. For this purpose, the concept and fundamentals of the CES, as well as their role in supporting the consumers and the power network, are described first. The flow of information in a CES is then discussed, and the roles of the operator, consumers, and facilities, as the main sectors of the CES are explained. The existing studies are classified and discussed regarding the different applications of the CES in the power systems and their drawbacks are highlighted. The operation and planning (feasibility) problems of the CES are investigated. Reviewing the existing studies shows that comprehensive models are required to address the energy management (EM) and feasibility analysis of the CES applications. To address this challenge, the general formulations are presented for the planning and the operation scheduling problems of the CES. In addition, addressing different CES applications in the power systems leads to some technical challenges which are described. Finally, future directions are suggested for potential researchers to continue the studies on the CES integration and application.
Attention‐based sensor fusion for emotion recognition from human motion by combining convolutional neural network and weighted kernel support vector machine and using inertial measurement unit signals
Authors: Zhao Yan , Guo Ming , Sun Xuehan , Chen Xiangyong , Zhao Feng 
Published: April 2023

AbstractThe remarkable development of human–computer interactions has created an urgent need for machines to be able to recognise human emotions. Human motions play a key role in emphasising and conveying emotions to meet the complexity of daily application scenarios, such as medical rehabilitation and social education. Therefore, this paper aims to explore hidden emotional states from human motions. Accordingly, we proposed a novel approach for emotion recognition using multiple inertial measurement unit (IMU) sensors worn on different body parts. First, the mapping relationship between emotion and human motion was established through fuzzy comprehensive evaluation, and data were collected for six emotional states: sleepy, bored, excited, tense, angry, and distressed. Second, the preprocessed data were used as input in a lightweight convolutional neural network to extract discriminative features. Third, an attention‐based sensor fusion module was developed to obtain the importance scores of each IMU sensor for generating a fused feature representation. In the recognition phase, we constructed a weighted kernel support vector machine (SVM) model with an auxiliary fuzzy function to improve the weight calculation method of kernel functions in a multiple kernel SVM. Finally, the results obtained are compared with those of similar state‐of‐the‐art studies, the proposed method showed a higher accuracy (99.02%) for the six emotional states mentioned above. These findings may promote the development of social robots with non‐verbal emotional communication capabilities.
Workflow, Time Requirement, and Quality of Medication Documentation with or without a Computerized Physician Order Entry System—A Simulation-Based Lab Study
Authors: Jungreithmayr Viktoria , Haefeli Walter E. , Seidling Hanna M. ,   and Implementation Team
Published: April 2023

Abstract
Background The introduction of a computerized physician order entry (CPOE) system is changing workflows and redistributing tasks among health care professionals.
Objectives The aim of this study is to describe exemplary changes in workflow, to objectify the time required for medication documentation, and to evaluate documentation quality with and without a CPOE system (Cerner® i.s.h.med).
Methods Workflows were assessed either through direct observation and in-person interviews or through semistructured online interviews with clinical staff involved in medication documentation. Two case scenarios were developed consisting of exemplary medications (case 1 = 6 drugs and case 2 = 11 drugs). Physicians and nurses/documentation assistants were observed documenting the case scenarios according to workflows established prior to CPOE implementation and those newly established with CPOE implementation, measuring the time spent on each step in the documentation process. Subsequently, the documentation quality of the documented medication was assessed according to a previously established and published methodology.
Results CPOE implementation simplified medication documentation. The overall time needed for medication documentation increased from a median of 12:12 min (range: 07:29–21:10 min) without to 14:40 min (09:18–25:18) with the CPOE system (p = 0.002). With CPOE, less time was spent documenting peroral prescriptions and more time documenting intravenous/subcutaneous prescriptions. For physicians, documentation time approximately doubled, while nurses achieved time savings. Overall, the documentation quality increased from a median fulfillment score of 66.7% without to 100.0% with the CPOE system (p < 0.001).
Conclusion This study revealed that CPOE implementation simplified the medication documentation process but increased the time spent on medication documentation by 20% in two fictitious cases. This increased time resulted in higher documentation quality, occurred at the expense of physicians, and was primarily due to intravenous/subcutaneous prescriptions. Therefore, measures to support physicians with complex prescriptions in the CPOE system should be established.
The prospects for, and implications of, emissions trading in shipping
Authors: Christodoulou Anastasia , Cullinane Kevin 
Published: April 2023

AbstractThe decarbonisation of shipping has become a high priority on the environmental and political agenda. The prospect of implementing an Emissions Trading System (ETS) for shipping has come to prominence as a proposed mechanism for speeding up the decarbonisation of the industry, with the EU taking proactive action to include shipping within the EU ETS by 2023. This paper analyses and provides a qualitative review of the historical development of the discussions and actions taken at both global level (by the International Maritime Organization (IMO)) and at regional level within the EU. A SWOT analysis of the potential implementation of an ETS for shipping is then presented. The paper concludes that an ETS for shipping can incentivise greater investment in, and deployment of, green technologies that will have the effect of reducing the carbon footprint of the shipping industry. However, the speed and significance of this effect will depend upon the specific shipping market segment and the relative stage in shipping market cycles over time. It is further concluded that despite the imminent unilateral introduction of shipping into the EU ETS, it is important that the IMO continues its work to develop a global ETS that promotes a ‘level playing field’ for competition within the sector and eliminates the risk of carbon leakage.
The corporate executive leadership team and its diversity: impact on innovativeness and sustainability of the bioeconomy
Authors: Hakovirta Marko , Denuwara Navodya , Topping Peter , Eloranta Jorma 
Published: April 2023

AbstractSenior executives have a major role in leading corporations both strategically and operationally. In large corporations, the executive team is leading through their respective organizations, ensuring that corporate strategy is executed efficiently and effectively. In addition, executive management plays the key role in shaping the culture and the values of the corporation. There exists a wealth of research conducted on executive management team dynamics and the success factors related to their performance. This study examines how diversity in executive management impacts the perceived innovativeness of companies. We compare the most innovative companies and the largest players in the bioeconomy. Currently, the bioeconomy has received a lot of attention as it is considered one of the industries associated with solving global societal and environmental challenges. However, it is not perceived as highly innovative and is considered to be lacking in diversity among senior executive teams. This study adds to the body of knowledge connecting innovation, diversity, and corporate leadership and highlights similarities and differences from diversity perspective related to the companies investigated.
E-band widely tunable, narrow linewidth heterogeneous laser on silicon
Authors: Guo Joel , Xiang Chao , Morin Theodore J. , Peters Jonathan D. , Chang Lin , Bowers John E. 
Published: April 2023

We demonstrate a heterogeneously integrated laser on silicon exhibiting a sub-20 kHz Lorentzian linewidth over a wavelength tuning range of 58 nm from 1350 to 1408 nm, which are record values to date for E-band integrated lasers in the literature. Wide wavelength tuning is achieved with an integrated Si ring-resonator-based Vernier mirror, which also significantly reduces the Lorentzian linewidth. Such a record performance leverages a mature heterogeneous III–V/Si platform and marks an important milestone in E-band optical fiber communications and in reaching visible wavelengths via second harmonic generation for optical atomic clock applications.
Size estimates for nanoplates
Authors: Morassi Antonino , Rosset Edi , Sincich Eva , Vessella Sergio 
Published: April 2023

Abstract
We consider the problem of determining, within an elastic isotropic nanoplate in bending, the possible presence of an inclusion made of different elastic material. Under suitable a priori assumptions on the unknown inclusion, we provide quantitative upper and lower estimates for the area of the unknown defect in terms of the works exerted by the boundary data when the inclusion is present and when it is absent.
Recent progress in transparent memristors
Authors: Shi Yuxin , Zhang Yanna , Li Guoqiang 
Published: April 2023

Abstract
Memristors are one of the most promising next-generation nonvolatile storage devices because of their unique structure and excellent performance. Transparent memristors with multifunctional coupling are one of the future development directions for functionally integrated electronics. Compared to other memristors, transparent memristors have enormous advantages in stability and optoelectronic devices due to their transparency. These advantages will enable transparent memristors to have more potential applications, such as in optoelectronic neuromorphic systems, artificial intelligence, and human visual systems. Therefore, it is necessary to analyze trends in transparent memristors in order to realize these applications. Here, we review three application areas : nonvolatile memory, artificial synapses, and neural networks. The resistive switching mechanism of transparent memristors is introduced through the overall and local effects. Finally, application prospects and challenges of transparent memristors are summarized, which provides an insightful guide to developing transparent electronic devices further.
Investigation the effect of dopant Te on CdSe thin films deposited by RF magnetron sputtering method
Authors: Kumar Devendra , Lal Chiranji , Veer Dharm , Singh Deshraj , Kumar Pawan , Katiyar Ram S 
Published: April 2023

Abstract
CdSe and CdSe:Te thin films were grown on glass substrates by RF magnetron sputtering. The doping percentage of Tellurium (Te) in CdSe was 7% for the CdSe:Te thin film. The microscopic images of the films were found to be uniform and homogeneous in nature with a uniform grain and no cracks, and the grain size of CdSe was higher than CdSe:Te thin film. CdSe:Te thin film shows a higher absorption coefficient compared to CdSe in the visible region. The Energy band gaps were found to be 2.01 and 1.73 eV for CdSe and CdSe:Te thin films, respectively. The incorporation of Te atom into the CdSe structure has enhanced the mobility and changed the type of conductivity from n-type to p-type.
A tribological characteristics and experimental analysis of novel chlorella biodiesel blends on engine performance
Authors: Saranraj I , Ganesan S , Pandiyarajan R 
Published: April 2023

Abstract
The present work proposes an investigation to assess the viability of novel mineral-based biodiesel developed from chlorella emersonii, a species of green algae. A single-cylinder, water-cooled, the four-stroke diesel engine was used in the experiments. Among the different biodiesel blends that were investigated for their tribological and engine performance characteristics, the B40 chlorella emersonii biodiesel blend exhibited the least coefficient of friction and while B40 and B100 blends offered enhanced performance characteristics. Comparatively, the remaining test fuel blends attained higher steady-state coefficient rates of friction: B10 (30.8%), B20 (16.21%), B60 (7.7%), B90 (18.2%), and mineral diesel (39.44%). B100 fuel blend exhibited the highest Flash temperature parameter of 83 °C while mineral diesel exhibited the lowest at 58.4 °C. These values were inversely proportional to their respective wear scar diameters with mineral diesel showing the highest wear scar diameter at 0.768 mm. The diameter of the wear scar yielded minimal wear for fuel blends from B40 to B100 and mineral diesel. The corrosion physiognomies of the test fuel blends were investigated, and the B40 fuel blend demonstrated lower corrosion characteristics with a steady-state coefficient of friction of 0.081 when compared to the other fuel blends. The investigated gasoline blends (B40 and B100) were tested on a diesel engine, which demonstrated reduced brake thermal efficiency and a wider range of brake-specific energy consumption under peak load circumstances. The B40 fuel blend exhibited better emissions performance during testing where the unburnt hydrocarbons, carbon monoxide, and smoke emitted were 10.94%, 15.7%, and 23.4% less than mineral diesel.
Neural co-processors for restoring brain function: results from a cortical model of grasping
Authors: Bryan Matthew J , Preston Jiang Linxing , P N Rao Rajesh 
Published: April 2023

Abstract

Objective. A major challenge in designing closed-loop brain-computer interfaces is finding optimal stimulation patterns as a function of ongoing neural activity for different subjects and different objectives. Traditional approaches, such as those currently used for deep brain stimulation, have largely followed a manual trial-and-error strategy to search for effective open-loop stimulation parameters, a strategy that is inefficient and does not generalize to closed-loop activity-dependent stimulation. Approach. To achieve goal-directed closed-loop neurostimulation, we propose the use of brain co-processors, devices which exploit artificial intelligence to shape neural activity and bridge injured neural circuits for targeted repair and restoration of function. Here we investigate a specific type of co-processor called a ‘neural co-processor’ which uses artificial neural networks and deep learning to learn optimal closed-loop stimulation policies. The co-processor adapts the stimulation policy as the biological circuit itself adapts to the stimulation, achieving a form of brain-device co-adaptation. Here we use simulations to lay the groundwork for future in vivo tests of neural co-processors. We leverage a previously published cortical model of grasping, to which we applied various forms of simulated lesions. We used our simulations to develop the critical learning algorithms and study adaptations to non-stationarity in preparation for future in vivo tests. Main results. Our simulations show the ability of a neural co-processor to learn a stimulation policy using a supervised learning approach, and to adapt that policy as the underlying brain and sensors change. Our co-processor successfully co-adapted with the simulated brain to accomplish the reach-and-grasp task after a variety of lesions were applied, achieving recovery towards healthy function in the range 75%–90%. Significance. Our results provide the first proof-of-concept demonstration, using computer simulations, of a neural co-processor for adaptive activity-dependent closed-loop neurostimulation for optimizing a rehabilitation goal after injury. While a significant gap remains between simulations and in vivo applications, our results provide insights on how such co-processors may eventually be developed for learning complex adaptive stimulation policies for a variety of neural rehabilitation and neuroprosthetic applications.
The impact of fusion-born alpha particles on runaway electron dynamics in ITER disruptions
Authors: Lier A. , Papp G. , Lauber Ph. W. , Pusztai I. , Särkimäki K. , Embreus O. 
Published: April 2023

Abstract
In the event of a tokamak disruption in a D-T plasma, fusion-born alpha particles take several milliseconds longer to thermalise than the background. As the damping rates drop drastically following the several orders of magnitudes drop of temperature, Toroidal Alfvén Eigenmodes (TAEs) can be driven by alpha particles in the collapsing plasma before the onset of the current quench. We employ kinetic simulations of the alpha particle distribution and show that the TAEs can reach sufficiently strong saturation amplitudes to cause significant core runaway electron (RE) transport in unmitigated ITER disruptions. As the eigenmodes do not extend to the plasma edge, this effect leads to an increase of the RE plateau current. Mitigation via massive material injection however changes the Alfvén frequency and can lead to mode suppression. A combination of the TAE-caused core RE transport with other perturbation sources could lead to a drop of runaway current in unmitigated disruptions.
Non-invasive range-shift measurement for therapeutic carbon-ion beams by detecting SEB with a CdTe imager
Authors: Tsuda M. , Yamaguchi M. , Toyokawa H. , Yabe T. , Nagao Y. , Kawachi N. , Satori R. , Sakai M. , Kada W. , Kamiya T. 
Published: April 2023

Abstract
Non-invasive range measurement of particle beams is important to prevent deviation of the irradiated area in particle therapy. In this study, we made an experiment of imaging carbon-ion beams by setting the projection ranges into an acrylic target from 4.29 cm to 7.65 cm by a pitch of 0.21 cm. Secondary electron bremsstrahlung (SEB) generated on the beam trajectories were detected for the imaging by use of a pinhole camera system consisting of a pinhole collimator and a position-sensitive cadmium-telluride semiconductor detector (CdTe imager). Beam images were acquired, and their profiles along the longitudinal axis were numerically analyzed, to obtain a suitable parameter that was strongly correlated with the set range. Then we could propose a scheme to measure the particle beam range in the target during irradiation by use of the CdTe imager. As a result, the range shift can be measured in the case of the acrylic target with an accuracy of 0.1 cm.
Numerical modeling and analysis of AZO/Cu2O transparent solar cell with a TiO2 buffer layer
Authors: Sliti Naama , Touihri Saâd , Nguyen Ngoc Duy 
Published: April 2023

Abstract
In the present work, titanium dioxide (TiO2) is sandwiched as a buffer layer between n-type aluminum-doped zinc oxide (AZO) and p-type cuprous oxide (Cu2O), increasing the efficiency of metal oxide-based solar cells. The effects of the device parameters such as thicknesses, carrier concentrations, and defect densities were investigated by numerical simulation to obtain optimal performance of Cu2O-based solar cells. Our findings reveal that by the incorporation of TiO2 thin film, the efficiency of the solar cell increases remarkably from 2.54 to 5.02 %. The optimal thicknesses of the Cu2O and TiO2 layers are in the range of 10 μm and 0.1 μm, respectively. We obtained optimal photo-electric conversion efficiency of 10.17 % and open-circuit voltage of 1.35 V while achieving 8.90 mA/cm2 short-circuit current density and 84.12 % fill factor, using structure parameters of 0.2 μm AZO, 0.1 μm TiO2 and 10 μm Cu2O with optimal acceptor-type dopant density in Cu2O of 1E17 cm−3 and donor-type dopant density in TiO2 of 1E18 cm−3.
Investigation on the non-linear behaviour of silicon nanowires and assessment of the biosensing potential
Authors: Hakim M M A 
Published: April 2023

Abstract
We perform a rigorous study on the conduction characteristics of long, low doped and relatively thick p-type silicon nanowire (SiNW) with different bias polarities/strengths to find out the origin of the non-linear electrical characteristics and to find out the applicable bias window for ensuring the gate responsive operation as biosensor. Depending on the polarity and strength of the drain bias (VDS)/liquid gate voltage (VGS), conduction is found to be confined in the bulk, in the surface accumulation region or in a path that comprises both accumulation region and the bulk thereby results in the diode or transistor like non-linear output characteristics. Although the SiNW is long without any junctions in the source/drain, the transfer characteristics exhibits a distinct shift with the increase of VDS when VDS is positive. The non-linear characteristics of SiNW is analysed to extract the gate responsive biasing window and it is found that the positive VDS application provides the flexibility of choosing diverse range of VDS and VGS voltages. As such, the shift in the transfer characteristic which is not appreciated for logic operation appears to be beneficiary for nanowire biosensors. This study sheds light on the variable electrical characteristics of SiNW reported in the literature and shows the way to choose appropriate bias conditions for biosensing applications.