bluuebunny/crossref_metadata_2025 huggingface dataset:
The importance of hydrology in routing terrestrial carbon to the atmosphere via global streams and rivers
Authors: Liu Shaoda , Kuhn Catherine , Amatulli Giuseppe , Aho Kelly , Butman David E. , Allen George H. , Lin Peirong , Pan Ming , Yamazaki Dai , Brinkerhoff Craig , Gleason Colin , Xia Xinghui , Raymond Peter A.
Published: March 2022

Significance

Stream/river carbon dioxide (CO
2
) emission has significant spatial and seasonal variations critical for understanding its macroecosystem controls and plumbing of the terrestrial carbon budget. We relied on direct fluvial CO
2
partial pressure measurements and seasonally varying gas transfer velocity and river network surface area estimates to resolve reach-level seasonal variations of the flux at the global scale. The percentage of terrestrial primary production (GPP) shunted into rivers that ultimately contributes to CO
2
evasion increases with discharge across regions, due to a stronger response in fluvial CO
2
evasion to discharge than GPP. This highlights the importance of hydrology, in particular water throughput, in terrestrial–fluvial carbon transfers and the need to account for this effect in plumbing the terrestrial carbon budget.
Goal discrimination in hippocampal nonplace cells when place information is ambiguous
Authors: Zhang Lu , Prince Stephanie M. , Paulson Abigail L. , Singer Annabelle C.
Published: March 2022

Significance

Goal-directed spatial navigation has been found to rely on hippocampal neurons that are spatially modulated. We show that “nonplace” cells without significant spatial modulation play a role in discriminating goals when environmental cues for goals are ambiguous. This nonplace cell activity is performance-dependent and is modulated by gamma oscillations. Finally, nonplace cell goal discrimination coding fails in a mouse model of Alzheimer’s disease (AD). Together, these results show that nonplace cell firing can signal unique task-relevant information when spatial information is ambiguous; these signals depend on performance and are absent in a mouse model of AD.
Viable offspring derived from single unfertilized mammalian oocytes
Authors: Wei Yanchang , Yang Cai-Rong , Zhao Zhen-Ao
Published: March 2022

Significance

In mammals, parthenogenesis is limited because of problems arising from genomic imprinting. Here, we report live mammalian offspring derived from single unfertilized eggs. This was achieved by the targeted DNA methylation rewriting of seven imprinting control regions. By designing guide RNAs with protospacer adjacent motif (PAM) sequences matching one allele but not the other, dCas9-Dnmt3a or dCpf1-Tet1 enables targeted DNA methylation editing in an allele-specific manner. The success of parthenogenesis in mammals opens many opportunities in agriculture, research, and medicine.
Half of US population exposed to adverse lead levels in early childhood
Authors: McFarland Michael J. , Hauer Matt E. , Reuben Aaron
Published: March 2022

Lead is a developmental neurotoxicant in wide industrial use that was once broadly distributed in the environment. The extent of the US population exposed in early life to high levels of lead is unknown, as are the consequences for population IQ. Serial, cross-sectional blood–lead level (BLL) data from National Health and Nutrition Examination Survey (NHANES), a nationally representative sample of US children aged 1 to 5 (
n
= 11,616) from 1976 to 1980 to 2015 to 2016 was combined with population estimates from the US Census, the Human Mortality Database, and the United Nations. NHANES and leaded gasoline consumption data were used to estimate BLLs from 1940 to 1975. We estimated the number and proportion of people that fall within seven BLL categories (<4.99; 5 to 0.9.99; 10 to 14.9: 15 to 19.9; 20.24.9; 25 to 29.9; and ≥30 µg/dL), by year and birth cohort, and calculated IQ points lost because of lead exposure. In 2015, over 170 million people (>53%) had BLLs above 5 µg/dL in early life (±2.84 million [80% CI]), over 54 million (>17%) above 15 µg/dL, and over 4.5 million (>1%) above 30 µg/dL (±0.28 million [80% CI]). BLLs greater than 5 µg/dL were nearly universal (>90%) among those born 1951 to 1980, while BLLs were considerably lower than 5 µg/dL among those born since 2001. The average lead-linked loss in cognitive ability was 2.6 IQ points per person as of 2015. This amounted to a total loss of 824,097,690 IQ points, disproportionately endured by those born between 1951 and 1980.
The parasites of language
Authors: Tang Aubrey
Published: March 2022

This article examines how “parasitical” political language can help explore a new understanding of oppositional
opinions in a global context of political polarization. By parasitical political language, I refer to what speech act theorist
J.L. Austin calls “infelicitous speech acts”, language that is used unsuccessfully. Jacques Derrida argues that these “incorrect”
utterances can escape from an already determined context and extend to a more liberated kind of communication. To explore the
potentially “positive” effect of parasitical language, this article examines the utterances of Hong Kong protesters prior to the
2020 US elections as infelicitous speech acts. Their radical political approach, surprisingly, spawned an anti-globalist activist
subculture shared by protesters in other parts of the world.
The collapse of dialogue, consent, and the controversy over Kristen Roupenian’s “Cat Person”
Authors: Roxburgh Natalie
Published: March 2022

This paper provides a Bakhtinian reading of Kristen Roupenian’s “Cat Person” in order to register the status of
dialogue pertaining to questions of sexual coercion and consent in the wake of the #metoo movement. I identify two prominent
discourses in the short story: feminist critiques of domination (perspectives that account for structural imbalances that tend to
put men in a hierarchy above women) and sex-positive feminism (a worldview that promotes female sexual agency). These two
discourses, this paper argues, are relevant to understanding why a collapse of dialogue ensues in the narrative. I then use “Cat
Person” to propose a way of contemplating the contemporary media landscape as a generator of failed dialogue.
Letters to nowhere
Authors: Tanović Una
Published: March 2022

In her study of epistolarity and world literature,Bower (2017)observes that letters “travel easily” and so are an obvious form for writing about migration and transnational dialogue. From another perspective, however, the epistolary may contain an empty promise: letters, after all, are sometimes waylaid or mislaid, unsent or undeliverable. This paper investigates the epistle and epistolary conventions in two short stories by US migrant writers – Edwidge Danticat’s “Children of the Sea” (1993) and Aleksandar Hemon’s “A Coin” (1997) – in which dialogue across national borders is made impossible under extreme political circumstances. I argue that Danticat and Hemon undermine the dialogic writing that is a basic generic epistolary convention to caution against ignoring asymmetries of power in situations of forced migration.
Development of the Blue Economy concept in Eastern Africa: strategic frameworks and a simmering conflict
Authors: Amuhaya Claire A. , Degterev Denis A.
Published: March 2022

Eastern African small island states played a role in advancing the ‘Blue Economy’ concept prior to the Rio+20 summit in 2012, when it emerged on a global stage. As their main concern they cited threats caused by climate change to marine life, on which they are highly dependent. This briefing explores the uneven development of the various national policies geared towards the concept. It notes an emphasis on economic policies neglecting climate change and dispute settlement policies, and identifies a need for the development of an all-encompassing regional approach to maximise Blue Economy benefits in Eastern Africa.
Forensic Imaging: A Powerful Tool in Modern Forensic Investigation
Authors: Zhang Min
Published: March 2022

Forensic imaging is a non-invasive examination process during the forensic investigation. It is mainly used in forensic pathology as an adjunct to the traditional autopsy. In the past two decades, forensic imaging has been vigorously developed by forensic experts from computed tomography (CT) to multiple augmented techniques through CT and magnetic resonance imaging (MRI). The application field of forensic imaging has also been broadened as its advantages are recognised by more forensic practitioners. In addition to the forensic pathology, this technique has been used in other forensic disciplines, including forensic anthropology, forensic odontology, forensic ballistics and wildlife forensics, etc. This article reviews the development of forensic imaging as the practice and research development in different forensic disciplines based on the relevant literature analysis.
Electric field sensing characteristics of ZnO/SiO2/Si surface acoustic wave devices
Authors: Liu Zhirong , Zhu Min , Xu Caihua , Bao Wenqi , Xie Liqiang , Zhang Haitao , Han Yueqi
Published: March 2022

Existing microelectro mechanical systems (MEMSs) electric field sensors have movable parts and electronic components. The movable parts are susceptible to external vibration, and the electronic components distort the distribution of the measured electric field. Therefore, we proposed a novel MEMS electric field sensor based on surface acoustic wave (SAW) technology. The SAW electric field sensor is a delay line device with an interdigital transducer and a reflector. The substrate of the device is a ZnO/SiO2/Si multilayer structure. The ZnO piezoelectric layer is not only used as the propagation medium of SAW, but also used as the sensing film of the external electric field. Then, the external electric field could be detected by analyzing the change of the eigenfrequency of the SAW. The multilayer structure of the substrate was prepared by MEMS process. The interdigital transducer and the reflector are fabricated by the lift-off process. The SAW sensor is characterized at different external electric field strengths by a network analyzer. The sensitivity of the sensor was 0.23 kHz/(kV m−1) and the nonlinearity was 6.8%.
Fault detection of electrolyzer plate based on improved Mask R-CNN and infrared images
Authors: Zhu Hongqiu , Peng Tianyu , Dai Yusi , Zhou Can , Sun Bei
Published: March 2022

Non-ferrous metals are very important strategic resources, and electrolysis is an essential step in refining non-ferrous metals. In the electrolysis process, plate short circuit is the most common fault, which seriously affects output and energy consumption. The rapid and accurate detection of faulty plates is of great significance to the metal refining process. Given the weak generalization ability and complex feature rule design of traditional object detection algorithms, and the poor detection effect of existing deep learning models in infrared images with many interference factors, an improved Mask R-CNN-based fault detection algorithm is proposed to improve the generation strategy and non-maximum suppression algorithm of proposals to reduce the missed detection. We also propose a globally generalized intersection over union loss function to characterize better the position and scale relationship between the predicted box and target box, which is beneficial to the bounding box regression. The experimental results show that the improved model has an accuracy rate 10.4% higher than the original model, reaching 86.8%. Compared with the common one- and two-stage object detection models, the improved model has a stronger detection ability. This algorithm has some reference value for the accurate detection and location of electrolytic cell faults.
Self-powering vibration sensor based on a cantilever system with a single-electrode mode triboelectric nanogenerator
Authors: Hosangadi Prutvi Sagar , Korrapati Mallikarjuna , Gupta Dipti
Published: March 2022

Here, we report a vibration sensor based on a single-electrode mode triboelectric nanogenerator (TENG). The main objective of this study is to develop a vibration sensor (architecture) that can be employed in any application with minor design changes to meet individual objectives. Hence, a cantilever-based vibration system is selected, which offers optimum design control in fine-tuning the sensor to operate in the desired frequency spectrum. The cantilever’s proof mass is suspended by isotropic linear elastic material constituting a scalable and tunable cantilever–mass system. The oscillations create contact separation between the triboelectric-active layers (i.e. fluorinated ethylene–propylene copolymer and screen-printed zinc oxide), which develop triboelectric waveforms. This voltage waveform is used for both sensing and powering mechanisms. At resonance, the device produces peak-to-peak voltage, short-circuit current, and power density of 25 V, 10 µA, and 1.38 W m−2, respectively. To measure the influence of change in cantilever properties, we varied the number of cantilevers and evaluated the sensor performance. The sensor is reliable with >99% accuracy in a broad frequency range of 0–400 Hz. The sensor exhibits a maximum sensitivity of 14 V g−1 and can charge a 1 µF capacitor to 2.75 V in <150 s. The sensor is further tested on a lab-scale vacuum pump with known (induced) faults to estimate the sensor’s competence in detecting the machinery faults. Considering the market acceptability, the sensor is developed with established manufacturing techniques such as screen-printing, and laser cutting. This study hopes to bridge the lab-to-market gap for TENG-based (vibration) sensors.
Designing physics board games: a practical guide for educators
Authors: Cardinot Adriana , McCauley Veronica , A Fairfield Jessamyn
Published: March 2022

Board games can be a highly engaging and motivating resource to support physics teaching at all educational levels. However, the development of board games to facilitate the communication of complex science subjects may not be an easy task for those with no prior experience in designing games. For instance, the various classification of educational game features, proliferation of game mechanics and lack of scholarly guidance for designing and on their efficacy in formal learning may hinder the game development process. To address this issue, this study presents a hands-on game development framework for science educators and researchers on how to design educational science games. The framework is divided into five steps with simple exercises that build upon each other to create a student-centred educational resource as well as providing a means of evaluation.
Analysis of an adaptive lead weighted ResNet for multiclass classification of 12-lead ECGs
Authors: Zhao Z , Murphy D , Gifford H , Williams S , Darlington A , Relton S D , Fang H , Wong D C
Published: March 2022

Background. Twelve lead ECGs are a core diagnostic tool for cardiovascular diseases. Here, we describe and analyse an ensemble deep neural network architecture to classify 24 cardiac abnormalities from 12 lead ECGs. Method. We proposed a squeeze and excite ResNet to automatically learn deep features from 12-lead ECGs, in order to identify 24 cardiac conditions. The deep features were augmented with age and gender features in the final fully connected layers. Output thresholds for each class were set using a constrained grid search. To determine why the model made incorrect predictions, two expert clinicians independently interpreted a random set of 100 misclassified ECGs concerning left axis deviation. Results. Using the bespoke weighted accuracy metric, we achieved a 5-fold cross-validation score of 0.684, and sensitivity and specificity of 0.758 and 0.969, respectively. We scored 0.520 on the full test data, and ranked 2nd out of 41 in the official challenge rankings. On a random set of misclassified ECGs, agreement between two clinicians and training labels was poor (clinician 1: κ = −0.057, clinician 2: κ = −0.159). In contrast, agreement between the clinicians was very high (κ = 0.92). Discussion. The proposed prediction model performed well on the validation and hidden test data in comparison to models trained on the same data. We also discovered considerable inconsistency in training labels, which is likely to hinder development of more accurate models.
Analytical model for collisional impurity transport in tokamaks at arbitrary collisionality
Authors: Fajardo D , Angioni C , Maget P , Manas P
Published: March 2022

The physics governing the collisional transport of impurities in tokamak plasmas can change significantly depending on four main parameters, namely the collisionality, the impurity charge and mass, and the trapped particle fraction, which can vary widely from the core to the edge of a fusion device. We present an analytical model for collisional impurity transport with a consistent dependence on broad scans in these four parameters, showing good agreement with the drift-kinetic code NEO. Radial profiles of collisional fluxes are calculated for different impurity species using ASDEX Upgrade experimental profiles as well as ITER simulated profiles, and they are also compared to NEO. This model is well suited for fast integrated modelling applications due to its low computational cost.
Performance analysis of a hybrid agent for quantum-accessible reinforcement learning
Authors: Hamann Arne , Wölk Sabine
Published: March 2022

In the last decade quantum machine learning has provided fascinating and fundamental improvements to supervised, unsupervised and reinforcement learning (RL). In RL, a so-called agent is challenged to solve a task given by some environment. The agent learns to solve the task by exploring the environment and exploiting the rewards it gets from the environment. For some classical task environments, an analogue quantum environment can be constructed which allows to find rewards quadratically faster by applying quantum algorithms. In this paper, we analytically analyze the behavior of a hybrid agent which combines this quadratic speedup in exploration with the policy update of a classical agent. This leads to a faster learning of the hybrid agent compared to the classical agent. We demonstrate that if the classical agent needs on average ⟨J⟩ rewards and ⟨T⟩cl epochs to learn how to solve the task, the hybrid agent will take

⟨

T

⟩

q

⩽

α

s

α

o

⟨

T

⟩

c
l

⟨

J

⟩

epochs on average. Here, α

s
and α

o
denote constants depending on details of the quantum search and are independent of the problem size. Additionally, we prove that if the environment allows for maximally α

o

k
max sequential coherent interactions, e.g. due to noise effects, an improvement given by ⟨T⟩q ≈ α

o
⟨T⟩cl/(4k
max) is still possible.
Analysis of the timing of freely falling antihydrogen
Authors: Rousselle Olivier , Cladé Pierre , Guellati-Khelifa Saïda , Guérout Romain , Reynaud Serge
Published: March 2022

We evaluate the accuracy to be expected for the measurement of free fall acceleration of antihydrogen in the GBAR experiment, accounting for the recoil transferred in the photodetachment process. We show that the uncertainty on the measurement of gravity comes mainly from the initial velocity dispersion in the ion trap so that the photodetachment recoil is not the limiting factor to the precision as a naive analysis would suggest. This result will ease the constraints on the choice of the photodetachment laser parameters.
Acoustoelectric current in graphene due to electron deformation potential and piezoelectric phonon couplings
Authors: Nafees Subhana , Ashraf S S Z , Obaidurrahman M
Published: March 2022

Recent studies strongly indicate that graphene can be used as a channel material for converting surface acoustic waves to acoustoelectric current, which is a resource for various exciting technological applications. On the theoretical side, studies on phonon amplification/attenuation and acoustoelectric current at low temperatures in graphene have reported approximate analytical results under exceedingly simplifying conditions using the Boltzmann transport equation. Overcoming the earlier simplifying assumptions, we investigate both numerically and analytically the governing kinetic equations for amplification/attenuation and acoustoelectric current, taking into account the piezoelectric and deformation potential electron phonon coupling mechanism in the semi classical Boltzmann transport formalism approach, and obtain analytical results that are in reasonable agreement with the reported experimental results.
Gravitational baryogenesis and dark matter from light black holes
Authors: Smyth Nolan , Santos-Olmsted Lillian , Profumo Stefano
Published: March 2022

We study a scenario in which the baryon asymmetry is created through Hawking radiation from primordial black holes via a dynamically-generated chemical potential. This mechanism can also be used to generate the observed dark matter abundance, regardless of whether or not the black holes fully evaporate. In the case that evaporation ceases, the observed dark matter abundance is generically comprised of both relic black holes and an asymmetric dark matter component. We show that this two-component dark matter scenario can simultaneously account for the observed baryon asymmetry and the cosmological dark matter, a possibility which evades constraints on either individual candidate.
Bubble wall velocities in local equilibrium
Authors: Ai Wen-Yuan , Garbrecht Björn , Tamarit Carlos
Published: March 2022

It is commonly expected that a friction force on the bubble
wall in a first-order phase transition can only arise from a
departure from thermal equilibrium in the plasma. Recently however,
it was argued that an effective friction, scaling as γ2

w
 
(with γ
w
being the Lorentz factor for the bubble wall
velocity), persists in local equilibrium. This was derived assuming
constant plasma temperature and velocity throughout the wall. On the
other hand, it is known that, at the leading order in derivatives,
the plasma in local equilibrium only contributes a correction to the
zero-temperature potential in the equation of motion of the
background scalar field. For a constant plasma temperature, the
equation of motion is then completely analogous to the vacuum case,
the only change being a modified potential, and thus no friction
should appear. We resolve these apparent contradictions in the
calculations and their interpretation and show that the recently
proposed effective friction in local equilibrium originates from
inhomogeneous temperature distributions, such that the
γ2

w
-scaling of the effective force is violated. Further, we
propose a new matching condition for the hydrodynamic quantities in
the plasma valid in local equilibrium and tied to local entropy
conservation. With this added constraint, bubble velocities in local
equilibrium can be determined once the parameters in the equation of
state are fixed, where we use the bag equation in order to
illustrate this point. We find that there is a critical value of the
transition strength αcrit such that bubble walls run
away for α>αcrit.
The nuclear symmetry energy from relativistic Brueckner-Hartree-Fock model *
Authors: Wang Chencan , Hu Jinniu , Zhang Ying , Shen Hong
Published: March 2022

The microscopic mechanisms of the symmetry energy in nuclear matter are investigated in the framework of the relativistic Brueckner-Hartree-Fock (RBHF) model with a high-precision realistic nuclear potential, pvCDBonn A. The kinetic energy and potential contributions to symmetry energy are decomposed. They are explicitly expressed by the nucleon self-energies, which are obtained through projecting the G-matrices from the RBHF model into the terms of Lorentz covariants. The nuclear medium effects on the nucleon self-energy and nucleon-nucleon interaction in symmetry energy are discussed by comparing the results from the RBHF model and those from Hartree-Fock and relativistic Hartree-Fock models. It is found that the nucleon self-energy including the nuclear medium effect on the single-nucleon wave function provides a largely positive contribution to the symmetry energy, while the nuclear medium effect on the nucleon-nucleon interaction, i.e., the effective G-matrices provides a negative contribution. The tensor force plays an essential role in the symmetry energy around the density. The scalar and vector covariant amplitudes of nucleon-nucleon interaction dominate the potential component of the symmetry energy. Furthermore, the isoscalar and isovector terms in the optical potential are extracted from the RBHF model. The isoscalar part is consistent with the results from the analysis of global optical potential, while the isovector one has obvious differences at higher incident energy due to the relativistic effect.
A Common Envelope Jets Supernova (CEJSN) Impostor Scenario for Fast Blue Optical Transients
Authors: Soker Noam
Published: March 2022

I propose a new scenario, the polar common envelope jets supernova (CEJSN) impostor scenario, to account for AT2018cow-like fast blue optical transients (FBOTs). The polar CEJSN impostor scenario evolves through four main phases. (1) A red supergiant (RSG) star expands to tidally interact with a neutron star (NS) companion (or a black hole). The interaction increases the RSG mass loss rate to form a circumstellar matter (CSM) halo to r ≃ 0.1 pc. (2) Shortly before the onset of a common envelope evolution (CEE) and about a year before explosion the NS accretes mass from the RSG envelope and launches jets that inflate two opposite lobes in the CSM within ≈100 au. (3) The NS-RSG system enters a CEE phase during which the system ejects most of the envelope mass in a dense equatorial outflow. (4) At the termination of the CEE the leftover envelope forms a circumbinary disk around the NS-core system. The NS accretes mass from the circumbinary disk and launches energetic jets that, when colliding with the fronts of the CSM lobes, power an FBOT event. The low mass of the jets-lobes interaction zones and their large distance, of about 100 au, from the center account for the fast transient. In the future the core collapses to form a second NS. In the far future the two NSs might merge. I suggest that FBOTs and similar fast transients are CEJSN impostors which compose a large fraction of the progenitors of NS-NS merger binaries.
Joint Control Strategy of Microgrid Inverter Based on Optimal Control and Residual Dynamic Compensation
Authors: Hu Changbin , Liu Chao , Luo Shanna , Yan Heming
Published: March 2022

With the continuous development of microgrid, the inverter under traditional PID control is difficult to meet the power quality requirements of microgrid. In order to improve the anti-interference ability and transient response speed of the output voltage of Isolated AC microgrid inverter, a dynamic compensation control structure combining linear quadratic optimal control and disturbance residual generator is proposed in this paper. Firstly, the quadratic optimal controller is established based on the inverter model. Secondly, the residual generator is established to observe the residual value of the disturbed system. Then, the dynamic compensation controller is designed according to the superposition principle, and a control signal opposite to the influence caused by the disturbance is output at the output of the controller. The disturbance signals can cancel each other without knowing the specific disturbance form. Finally, the experiments of load switching, three-phase imbalance and nonlinear load are designed on MATLAB/Simulink simulation software to verify the effectiveness of the control strategy proposed in this paper.
Dynamic Compensation Control Strategy for DC Converter Based on Linear Optimal Quadratic
Authors: Hu Changbin , Wang Huiru , Luo Shanna , Huang Yufei
Published: March 2022

Aiming at the problem of DC bus voltage fluctuation, a DC-DC converter control method combining LQR (Linear Optimal Quadratic) and dynamic compensation control is proposed. Firstly, the state space model of DC-DC converter is established. Secondly, according to the following characteristics of LQR controller, the error of the controlled output is introduced into the integral control as an extended state to eliminate the output tracking error. Then, in order to suppress the voltage fluctuation caused by load switching of DC-DC converter during power grid operation, a dynamic compensation structure based on disturbance observer is designed through robust coprime decomposition and Euler parameterization theory. The structure compensates directly at the input of the current loop, and the compensation controller Q(s) is calculated by model matching. Finally, the simulation is carried out by Matlab / Simulink. The results show that without changing the structural parameters of the original system, the new control architecture can effectively suppress the DC bus voltage fluctuation caused by load theft and power fluctuation, and enhance the anti-interference performance and dynamic performance of the system.
Energy Saving Control of Integrated Energy Multi-Energy Complementary Coupling Space Heating System Based on Fuzzy Theory
Authors: Hu Changbin , Zhao Xinyu , Luo Shanna , Lu Xiaojun
Published: March 2022

Because the traditional solar-ground source heat pump heating system uses temperature difference controllers to control most, it causes the problem of large energy consumption of the equipment. In order to improve such problems, the complexity of the space heating control system is considered comprehensively, and the fuzzy strategy is used to improve the previous control system. TRNSYS was used to build a heating system simulation model, MATLAB was used to build a solar heating system fuzzy controller model, and the two models were coupled to jointly simulate the internal temperature change and energy consumption of the space under the same environmental conditions and different controllers. Experiments show that under the design conditions, the solar collector is greatly affected by the light, the temperature of the hot water storage tank is controlled between 58°C and 65°C. Using the traditional temperature difference controller, the system COP (Coefficient Of Performance) is low and the energy consumption is large, and the economic benefits are not high; the use of the fuzzy controller can increase the system COP by 6.1%, reduce the energy consumption by 22.85%, and save 8.71 yuan in the daily economic benefits of the system.
Research on BIM model lightweighting methods and IoT technology application in the context of WebGL
Authors: Yuan Yuhe , Yang Jing , Shao Ruping , Mao Jiahuan , Zhang Chengwei
Published: March 2022

In view of the fact that most of the existing building information modeling (BIM) platforms are based on the Client/Server (C/S) mode of client-side applications, which brings about problems such as weak data interoperability, poor model semantic integrity and bad user-friendliness, this paper proposed an IFC-JSON and IFC-glTF model file format conversion process based on WebGL and an improved Draco algorithm that can further lighten glTF files. The experimental results showed that this option can effectively reduce data redundancy, then combined IoT (Internet of Things) as well as sensor technology in project practice to collect and transmit building-related O&M data, and finally visualised the equipment status of the building on the Web based on WebGL technology, providing a new application way for the combination of BIM technology and IOT technology in the browser/server mode.
Computing offloading method with low power consumption constraint for smart grid
Authors: Wu Yuebin , Lu Pengcheng , Bu Xiande , Liu Shidong , Zhong Cheng , Liu Chuan
Published: March 2022

With the development of the Power Internet of Things, power transmission and transformation business have a wide range of operation, large regional differences, a wide variety of equipment and other problems, making the access and deployment of mass sensors with low power consumption crucial. In order to realize the cloud-side collaborative computing of the Internet of Things, it is necessary to build a low-power information acquisition and transmission network, and realize the low-power deployment of the low-power sensor network and equipment. The embedded node device can be used as the basis of low-power transmission network to realize low-power transmission of cloud-side collaborative computing information, combined with the existing low-power transmission and transformation equipment.
Intelligent computing and analysis of breakdown voltage of rod-rod long air gap
Authors: Yao Xiuyuan , Yang Bingxue , Geng Jianghai , Su Yu , Yu Hua , Yang Guohua , Wang Xinwei
Published: March 2022

The discharge characteristics of air gap is one of the important factors to determine the insulation level which is crucial for electrical engineering construction. In order to calculate the 50% breakdown voltage of rod-rod air gap under different meteorological conditions and different gap distances, we take the positive standard switching impulse test data of rod-rod air gap under different meteorological conditions as samples. Based on training set, a breakdown voltage prediction model of rod-rod air gap under different meteorological conditions was established by cuckoo search optimized weighted support vector regression (CS-ω-SVR). The results show that the average absolute percentage error of the test set is 3.6%, which verifies the validity of this computing method. The method can provide reference for the computation of air gap breakdown voltage under different altitudes and extreme meteorological conditions.
Reinforcement Learning Optimized Intelligent Electricity Dispatching System
Authors: Xiao Xinhang
Published: March 2022

With the rapid development of artificial intelligence, new changes are coming to all walks of life including traditional manufacturing industry, bio-pharmaceutical industry, electric-power industry, etc.. For electric-power industry, many machine learning algorithms have been used to achieve intelligent dispatch of electricity, intelligent electricity equipment fault diagnosis and more optimized customer management, among which the automation of power network is one of the most important issue ensuring safe operation of electricity grid. In the recent years, intelligent dispatch method based on big data analysis has been used in intellectual scheduling of electricity and has got significant promotion. However, the intelligent dispatch on big data analysis needs tremendous history data that is sometime not that easy to get. Moreover, once a small probability event happens, the big data based intelligent dispatch method may lose efficacy, thus in this paper we proposed a new intelligent dispatch model based on the reinforcement learning that is more robust, safer and with higher efficiency. Finally, according to the empirical study result, our model outperforms the traditional methods, where the average economic benefit in the test area increases more than 25%, fluctuation of distribution is more stable than before and the carbon emission decreases about 30%.
Numerical study of RC slabs under two-point contact explosion load
Authors: Yuan Xinjing , Song Jian
Published: March 2022

As an important bearing component of bridge, bridge deck is the key to bridge passage. In this paper, a solid model of reinforced concrete slab is established in LS-DYNA software, and the parameters are designed as the amount of explosive and the distance between explosives. The numerical simulation of two-point explosion test is carried out, and the damage mechanism and dynamic response of reinforced concrete slab under two-point explosion load are proposed. The results show that there is a phenomenon of energy accumulation in two-point contact explosion. At the same charge, the failure characteristics and dynamic response of RC slabs are related to the distance between the blast points. When the distance is small (30cm), the stress wave encounters and superposition strengthens between the blast points. When the spacing is large (60cm), the stress waves do not meet between the burst points, but reach the back burst surface and the side of the plate at the same time, and the damage is serious near the side of the plate, and the peak acceleration is small.
Experimental study on head loss coefficients of tailrace surge tank for Baihetan hydropower station
Authors: Sun Hongliang , Yang Fei , Cai Fulin , Chen Yimin , Xu Jianrong
Published: March 2022

The scale and hydraulic inertia of the tailrace surge tank of Baihetan hydropower station are huge. Its resistance characteristics are directly related to the accuracy of the calculation results of the hydraulic transient process, the stability of the unit operation, the economy and safety of the project. The influence of split ratio, cross-sectional area of the restricted orifice and unit operation on the head loss coefficient of Baihetan surge tank was studied by model experiment method. The results show that the head loss coefficient increases with the increase of split ratio and decreases with the increase of the cross-sectional area of the restricted orifice. Under the diffluence condition, the head loss coefficient of the restricted orifice in double unit operation is obviously larger than that in single unit operation. Under the confluence condition, the head loss coefficients of the restricted orifice in single and double unit operation are the same. The deviation will be large when using the recommended value in the specification, the experimental results are more reasonable. The research conclusions will provide technical support for the design and operation of Baihetan hydropower station as well as reference for similar projects.
Design and Simulation of LLC Resonant Converter for Hydrogen Production Based on Proton Exchange Membrane Electrolysis
Authors: Zhang Haifeng , Fan Zerui , Zhou Jinghua , Shen Ze
Published: March 2022

This paper studies the relationship between the parameters in LLC resonant circuit based on the fundamental wave analysis method, analyzes the gain curve and the soft-switching conditions of the power tube, gives the selection method of the parameters k and Q and calculates the resonant component parameters. In this paper, a closed-loop frequency modulation control method is used to control the DC output voltage of the resonant converter. At the same time, mathematical modeling and analysis are carried out for the electrochemical model and thermal model of the proton exchange membrane (PEM) hydrogen production electrolyzer, and the Simulink simulation tool is used to complete the joint simulation of the PEM electrolysis model and the LLC resonant converter. The simulation results fully reflect the actual control process.
Analysis for Gas in Transformer Oil based on improved GM (1, N) Grey
Authors: Zhu QiFei , Lv ZhaoPeng , Liu LiPeng , Zhang Jing , Lou Gao , Tian XingJun
Published: March 2022

Based on the traditional gray GM (1, N) model, with seven kinds of gas fusion in transformer oil predicted, the actual detection times for the gas is less, the sequence accuracy is greatly reduced with an large error, and it will not conform to the standard judgment for the smooth curve. Therefore, an adaptive regression algorithm is proposed to revise each calculation result of its GM model to modify the model error. Through simulation, the sequence curves of the N data by error correction are obviously closer with a greater correlation degree. The improved gray prediction model can effectively improve the accuracy of traditional GM (1, N).
Research and Demonstration of Intelligent Multi-Physical Quantity Integration Sensor for Transmission Lines
Authors: Wei Liang , Li Yongcheng , Cui Zhimei , Wang Baoshi , Huang Guanlang , Wang Zhiming , Wei Jie
Published: March 2022

The digital grid requires sensors to be widely deployed, safe, and reliable. At present, the single functional sensors suffered from redundant sensing system, repeated construction and low utilization rate. Therefore, this paper researched the multi-physical quantity integration sensor for a quad-bundle spacer on 500kV transmission lines. The sensor was composed of self-supplying rings and the monitoring host. Based on the non-contact current measurement technology, energy supply technology, intelligent sensing technology, low power consumption technology, reliability design technology, and other advanced technologies, this paper designed the hardware, software, and protective structure of the sensor, which can monitor the current and temperature of bubbles, channel side image and infrared image on transmission lines, ambient temperature, humidity, and air pressure. Finally, the multi-physical quantity integration sensors have been used on transmission lines in China Southern Power Grid, and the functions were verified. The sensors promote the automation, information, and digitization of monitoring transmission lines.
Finite Element Analysis and Optimization of the Planar Steel Tubular K-Joints
Authors: Chen Ying , Yang Qingtao , Wang Dongchen
Published: March 2022

Planar steel tubular K-joints feature various geometric forms and intricate load states, whose bearing capacity is influenced by a number of factors. To address the problems above, a research on the bearing capacity of common planar K-joints in practical engineering projects was conducted. Based on numerical simulation, nonlinear finite element analysis on four kinds of planar K-joints was carried out in ANSYS. The bearing capacity and failure modes of those K-joints were figured out. The bearing capacity of each combination was compared. The results provided by finite element analysis was compared with those derived from codes. The design of K-joints was optimized, thereby improving the bearing capacity and satisfy requirements of engineering projects.
Low power optimization method for contactless micro intelligent voltage sensor communication network
Authors: Sun Hongdi , Chen Renze , Zhou Ke , Wang Xiaoming
Published: March 2022

Aiming at the problems of high power consumption and low success rate in contactless micro voltage sensor communication network, a low power consumption optimization method of contactless micro voltage sensor communication network is proposed. By calculating the average power consumption of micro voltage sensor nodes in the communication network area, the energy balance degree of micro voltage sensor nodes is obtained. When the micro voltage sensor nodes meet the sleep probability of communication network area coverage factor, the power consumption of voltage sensor communication network is calculated. By defining the information entropy of communication network data set, the conditional entropy of data feature classification of communication network is obtained, and the high-power data is eliminated by using the validity kernel function of data features. Combined with the low-power optimization algorithm of micro voltage sensor communication network, the low-power optimization of micro voltage sensor communication network is realized. The experimental results show that the optimization method in this paper can not only reduce the power consumption of data transmission in contactless micro voltage sensor communication network, but also improve the success rate of data transmission, and has better optimization effect.
The CMS HGCAL silicon region architecture specification and optimisation
Authors: Noy M.
Published: March 2022

An overview of the electronics readout/trigger architecture for the CMS HGCAL will be given. To respond to physics performance requirements, data rates, trigger-primitive generation and radiation tolerance has been extremely challenging. Each HGCAL endcap includes ∼300 m2of active silicon in 50 layers, with a largely inhomogenous layout with limited commonality between layers. An agile, python-based counting scheme was implemented that creates tables of component counts. These are subsequently incorporated in the architecture specifications document and costbook, providing critical input to the mechanical design and integration optimisation.
Characterization of 128 × 128 MM-PAD-2.1 ASIC: a fast framing hard x-ray detector with high dynamic range
Authors: Gadkari D. , Shanks K.S. , Hu H. , Philipp H.T. , Tate M.W. , Thom-Levy J. , Gruner S.M.
Published: March 2022

We characterize a new x-ray Mixed-Mode Pixel Array Detector
(MM-PAD-2.1) Application Specific Integrated Circuit (ASIC). Using
an integrating pixel front-end with dynamic charge removal
architecture, the MM-PAD-2.1 ASIC extends the maximum measurable
x-ray signal (in 20 keV photon units) to > 107
 x-rays/pixel/frame while maintaining a low read noise across the
full dynamic range, all while imaging continuously at a frame rate
of up to 10 kHz. The in-pixel dynamic charge removal mechanism
prevents saturation of the input amplifier and proceeds in parallel
with signal integration to achieve deadtime-less measurements with
incident x-ray rates of > 1010 x-rays/pixel/s. The ASIC format
consists of 128 × 128 square pixels each 150 μm on a
side and is designed to be 3-side buttable so large arrays can be
effectively tiled. Here we use both laboratory x-ray sources and the
Cornell High Energy Synchrotron Source (CHESS) to characterize two
single ASIC prototype detectors for both low (single x-ray) and high
incident flux detection. In the first detector the ASIC was solder
bump-bonded to a 500 μm thick Si sensor for efficient
detection of x-rays below  20 keV, whereas the second detector used
a 750 μm thick CdTe sensor for x-rays above ∼ 20 keV.
Development of a CsI(Tl) scintillator based gamma probe for the identification of nuclear materials in unknown areas
Authors: Kim G. , Lee J. , Jeong S. , Kim M.
Published: March 2022

In case of nuclear accident or an act of terrorism, such as
planting a dirty bomb, the nuclear and radioactive materials could
be spread over a large area. The environmental radioactivity
information has to be obtained rather fast in order to secure the
safety of any activity in these potentially high-level radiation
contaminated areas. In addition, a lack of both social
infrastructure and environmental radiation information may be
expected in this area. Therefore, the sampling process must be
carried out in a timely and efficient manner. In this study, a probe
operated via a distribution method was developed to improve the
efficiency of the sampling process by identifying the location and
nuclides of leaked materials. For distribution type operation,
CsI(Tl) and SiPM were applied to the sensor part of the probe to
operate at low voltage operation and for durability. In addition,
the power consumption of the data acquisition module and the weight
of the probe were optimized for distribution through drones, battery
operation, and wireless communication. The energy resolution of this
probe was 10.84% at 662 keV and it showed adequate characteristics
in the spectrum of nuclear materials. In addition, the practical
operability of this probe was verified through determination of the
minimum detectable dose rate condition and the difference in the
measured values based on the landing orientation.
Global fossil carbon emissions rebound near pre-COVID-19 levels
Authors: Jackson R B , Friedlingstein P , Le Quéré C , Abernethy S , Andrew R M , Canadell J G , Ciais P , Davis S J , Deng Zhu , Liu Zhu , Korsbakken J I , Peters G P
Published: March 2022

Fossil CO2 emissions in 2021 grew an estimated 4.2% (3.5%–4.8%) to 36.2 billion metric tons compared with 2020, pushing global emissions back close to 2019 levels (36.7 Gt CO2).