bluuebunny/crossref_metadata_2025 huggingface dataset:
Physiological and Pathophysiological Consequences of Mechanical Ventilation
Authors: Silva Pedro Leme , Ball Lorenzo , Rocco Patricia R.M. , Pelosi Paolo
Published: April 2022

Mechanical ventilation is a life-support system used to ensure blood gas exchange and to assist the respiratory muscles in ventilating the lung during the acute phase of lung disease or following surgery. Positive-pressure mechanical ventilation differs considerably from normal physiologic breathing. This may lead to several negative physiological consequences, both on the lungs and on peripheral organs. First, hemodynamic changes can affect cardiovascular performance, cerebral perfusion pressure (CPP), and drainage of renal veins. Second, the negative effect of mechanical ventilation (compression stress) on the alveolar-capillary membrane and extracellular matrix may cause local and systemic inflammation, promoting lung and peripheral-organ injury. Third, intra-abdominal hypertension may further impair lung and peripheral-organ function during controlled and assisted ventilation. Mechanical ventilation should be optimized and personalized in each patient according to individual clinical needs. Multiple parameters must be adjusted appropriately to minimize ventilator-induced lung injury (VILI), including: inspiratory stress (the respiratory system inspiratory plateau pressure); dynamic strain (the ratio between tidal volume and the end-expiratory lung volume, or inspiratory capacity); static strain (the end-expiratory lung volume determined by positive end-expiratory pressure [PEEP]); driving pressure (the difference between the respiratory system inspiratory plateau pressure and PEEP); and mechanical power (the amount of mechanical energy imparted as a function of respiratory rate). More recently, patient self-inflicted lung injury (P-SILI) has been proposed as a potential mechanism promoting VILI. In the present chapter, we will discuss the physiological and pathophysiological consequences of mechanical ventilation and how to personalize mechanical ventilation parameters.
Surgical Treatment for Severe Primary Midbrain and Upper Pons Hemorrhages Using a Subtemporal Tentorial Approach
Authors: Wu Jie , Wu Xiao , Zhang Yong , Du Wei , Wei Ke , Yao Guo Jie
Published: April 2022

Objectives It is unclear whether surgical hematoma evacuation should be performed in cases of primary brainstem hemorrhages (PBH). Here, we analyzed 15 cases with severe primary midbrain and upper pons hemorrhages to assess the associations between the subtemporal tentorial approach and patient functional outcomes and mortality.

Design A total of 15 patients diagnosed with severe primary midbrain and upper pons hemorrhages who had previously received the subtemporal tentorial approach at our facility from January 2018 and March 2019 were analyzed. All surviving cases received a follow-up at 6 months after surgery. The Glasgow Coma Scale and Glasgow Outcome Scale (GOS) scores were analyzed 1 and 6 months after surgery, respectively. Demographic data, lesion characteristics, and follow-up data were retrospectively collected.

Results All patients successfully underwent surgical evacuation for hematomas using the subtemporal tentorial approach. The overall survival rate for these cases was 66.7% (10/15). At the last follow-up, 26.7% of patients (4/15) exhibited healthy function (GOS score: 4), 20.0% (3/15) showed disability (GOS score: 3) and 20.0% (3/15) were in a vegetative state (GOS score: 2).

Conclusions Based on the results uncovered in this study, the subtemporal tentorial approach was found to be both safe and feasible and may be beneficial for the treatment of severe primary midbrain and upper pons hemorrhages, but a more comprehensive and comparative study is required to further confirm these results.
2D materials-enabled optical modulators: From visible to terahertz spectral range
Authors: Gan Xuetao , Englund Dirk , Van Thourhout Dries , Zhao Jianlin
Published: April 2022

Two-dimensional (2D) materials with layered structures have a variety of exceptional electronic and optical attributes for potentially developing basic functions of light wave technology from light-emitting to -modulating and -sensing. Here, we present state-of-the-art 2D materials-enabled optical intensity modulators according to their operation spectral ranges, which are mainly determined by the optical bandgaps of the 2D materials. Leveraging rich electronic structures from different 2D materials and the governed unique light–matter interactions, the working mechanisms and device architectures for the enabled modulators at specific wavelength ranges are discussed. For instance, the tunable excitonic effect in monolayer transition metal dichalcogenides allows the modulation of visible light. Electro-absorptive and electro-refractive graphene modulators could be operated in the telecom-band relying on their linear dispersion of the massless Dirac fermions. The bendable electronic band edge of the narrow bandgap in few-layer black phosphorus promises the modulation of mid-infrared light via the quantum-confined Franz–Keldysh or Burstein–Moss shift effect. Electrically and magnetically tunable optical conductivity in graphene also supports the realizations of terahertz modulators. While these modulators were demonstrated as proof of concept devices, part of them have great potential for future realistic applications, as discussed with their wavelength coverage, modulation depth, insertion loss, dynamic response speed, etc. Specifically, benefiting from the well-developed technologies of photonic chips and optical fibers in telecom and datacom, the 2D materials-based modulators integrated on these photonic structures are expected to find applications in fiber and chip optical communications. The free-space mid-infrared and terahertz modulators based on 2D materials can expect application in chemical bond spectroscopy, free-space communications, and environment/health sensing.
Effect of Rosensweig instability in a ferrofluid layer on reflection loss of a high-frequency electromagnetic wave
Authors: Li Yan-Hom , Huang Kuo-Lung
Published: April 2022

A ferrofluid layer separates into numerous subscale crests, which is referred to as Rosensweig instability, whose shape and size depend on the field condition and the composition of the ferrofluid. A ferrofluid consisting of nanoscale magnetite particles is also used as an electromagnetic (EM) wave absorption and reflection material. For this study, oil-based and mixture ferrofluid layers that split into various shapes of crests in the presence of an external magnetic field are used to form a protruding structure to reflect and scatter the EM wave and decrease EM radiation energy. For an identical field strength, a mixture ferrofluid layer splits into more crests than an oil-based ferrofluid. A mixture crest shows a less uniform size and shape than the oil-based one. A high-power green laser light is used as a visual EM wave emitting to a crest, which has varying tip angles, and to demonstrate the reflection and scattering. The reflection loss increases as the field strength is increased to create a crest of a smaller tip angle. The reflection loss of an EM wave is significantly affected by the transmitting position on a crest and the shape of a crest. Inter-reflection arises if an EM wave is repeatedly reflected on the surfaces of crests, which contributes to a significant reflection loss. An EM wave incident at an angle of 45° on a crest resulting in a larger area of the inter-reflection zone without specular reflection in a trough gives the most significant reflection loss.
Strengths and risks of the Primary Health Network commissioning model
Authors: Bates Shona , Wright Michael , Harris-Roxas Ben
Published: April 2022

Objective To explain how the Primary Health Network commissioning model works, and factors likely to affect its success. Methods The study focuses on the delivery of primary healthcare services by one Primary Health Network (PHN) in Australia. The qualitative case study is informed by a desk top review, interviews (n = 49) and observations with key stakeholders involved in commissioning and delivering primary healthcare services in the region. Results The study provides several insights about the PHN model. First, conceptually, the PHN commissioning model is well suited to identifying and meeting local primary healthcare priorities, bringing together a range of stakeholders involved in healthcare provision. Second, although primary healthcare services are difficult to specify and measure, PHN staff use their content knowledge and experience, and relationships with providers and the community, to design services that meet the needs of consumers. Third, the success of this model may be undermined by short funding cycles and short lead-times, a focus on national rather than local priorities, and continual reductions in operational funding. This may result in more procedural forms of contract management, which may mean that changes in service need, provision and quality go unnoticed. Conclusions This study shows that although clever in design, the PHN model may not meet its full potential. Given continual changes to the model, including funding, further independent research should be undertaken to understand how PHNs adjust and whether services continue to meet the needs of the local community.
Comparison of fire-produced gases from wind tunnel and small field experimental burns
Authors: Weise David R. , Hao Wei Min , Baker Stephen , Princevac Marko , Aminfar Amir-Hessam , Palarea-Albaladejo Javier , Ottmar Roger D. , Hudak Andrew T. , Restaino Joseph , O’Brien Joseph J.
Published: April 2022

Composition of pyrolysis gases for wildland fuels is often determined using ground samples heated in non-oxidising environments. Results are applied to wildland fires where fuels change spatially and temporally, resulting in variable fire behaviour with variable heating. Though historically used, applicability of traditional pyrolysis results to the wildland fire setting is unknown. Pyrolytic and flaming combustion gases measured in wind tunnel fires and prescribed burns were compared using compositional data techniques. CO2 was dominant in both. Other dominant gases included CO, H2 and CH4. Relative amounts of CO, CO2 and CH4 were similar between fire phases (pyrolysis, flaming combustion); relatively more H2 was observed in pyrolysis samples. All gas log-ratios with CO2 in pyrolysis samples were larger than in flaming combustion samples. Presence of live plants significantly affected gas composition. A logistic regression model correctly classified 76% of the wind tunnel samples as pyrolysis or flaming combustion based on gas composition. The model predicted 60% of the field samples originated from pyrolysis. Fire location (wind tunnel, field) and fire phase affected gas composition. The compositional approach enabled analysis and modelling of gas compositions, producing results consistent with the basic characteristics of the data.
Evidence for lack of a fuel effect on forest and shrubland fire rates of spread under elevated fire danger conditions: implications for modelling and management
Authors: Cruz Miguel G. , Alexander Martin E. , Fernandes Paulo M.
Published: April 2022

The suggestion has been made within the wildland fire community that the rate of spread in the upper portion of the fire danger spectrum is largely independent of the physical fuel characteristics in certain forest ecosystem types. Our review and analysis of the relevant scientific literature on the subject suggest that fuel characteristics have a gradual diminishing effect on the rate of fire spread in forest and shrubland fuel types with increasing fire danger, with the effect not being observable under extreme fire danger conditions. Empirical-based fire spread models with multiplicative fuel functions generally do not capture this effect adequately. The implications of this outcome on fire spread modelling and fuels management are discussed.
Thoughts on how to think (and talk) about RNA structure
Authors: Vicens Quentin , Kieft Jeffrey S.
Published: April 2022

Recent events have pushed RNA research into the spotlight. Continued discoveries of RNA with unexpected diverse functions in healthy and diseased cells, such as the role of RNA as both the source and countermeasure to a severe acute respiratory syndrome coronavirus 2 infection, are igniting a new passion for understanding this functionally and structurally versatile molecule. Although RNA structure is key to function, many foundational characteristics of RNA structure are misunderstood, and the default state of RNA is often thought of and depicted as a single floppy strand. The purpose of this perspective is to help adjust mental models, equipping the community to better use the fundamental aspects of RNA structural information in new mechanistic models, enhance experimental design to test these models, and refine data interpretation. We discuss six core observations focused on the inherent nature of RNA structure and how to incorporate these characteristics to better understand RNA structure. We also offer some ideas for future efforts to make validated RNA structural information available and readily used by all researchers.
Texture-like representation of objects in human visual cortex
Authors: Jagadeesh Akshay V. , Gardner Justin L.
Published: April 2022

Significance

Humans are exquisitely sensitive to the spatial arrangement of visual features in objects and scenes, but not in visual textures. Category-selective regions in the visual cortex are widely believed to underlie object perception, suggesting such regions should distinguish natural images of objects from synthesized images containing similar visual features in scrambled arrangements. Contrarily, we demonstrate that representations in category-selective cortex do not discriminate natural images from feature-matched scrambles but can discriminate images of different categories, suggesting a texture-like encoding. We find similar insensitivity to feature arrangement in Imagenet-trained deep convolutional neural networks. This suggests the need to reconceptualize the role of category-selective cortex as representing a basis set of complex texture-like features, useful for a myriad of behaviors.
The gut microbiome influences host diet selection behavior
Authors: Trevelline Brian K. , Kohl Kevin D.
Published: April 2022

Significance

The behavior of diet selection or diet choice can have wide-reaching implications, scaling from individual animals to ecological and evolutionary processes. Previous work in this area has largely ignored the potential for intestinal microbiota to modulate host foraging decisions. The notion that the gut microbiome may influence host foraging behavior has been highly speculated for years but has not yet been explicitly tested. Here, we show that germ-free mice colonized by differential microbiomes from wild rodents with varying natural feeding strategies exhibited significant differences in their voluntary dietary selection. Specifically, colonized mice differed in voluntary carbohydrate selection, and divergent feeding preferences were associated with differences in circulating essential amino acids, bacterial tryptophan metabolism, and intestinal morphology. Together, these results demonstrate a role for the microbiome in host nutritional physiology and foraging behavior.
How chemical defects influence the charging of nanoporous carbon supercapacitors
Authors: Dupuis Romain , Valdenaire Pierre-Louis , Pellenq Roland J.-M. , Ioannidou Katerina
Published: April 2022

Significance

Nanoporous carbon texture makes fundamental understanding of the electrochemical processes challenging. Based on density functional theory (DFT) results, the proposed atomistic approach takes into account topological and chemical defects of the electrodes and attributes to them a partial charge that depends on the applied voltage. Using a realistic carbon nanotexture, a model is developed to simulate the ionic charge both at the surface and in the subnanometric pores of the electrodes of a supercapacitor. Before entering the smallest pores, ions dehydrate at the external surface of the electrodes, leading to asymmetric adsorption behavior. Ions in subnanometric pores are mostly fully dehydrated. The simulated capacitance is in qualitative agreement with experiments. Part of these ions remain irreversibly trapped upon discharge.
Collimation of fast electron beams by strong external magnetic field in laser–solid interaction using Monte Carlo simulation
Authors: Ghasemi Seyed Abolfazl , Moslehi Amir , Faghih Samira
Published: April 2022

In this paper, the effect of the external magnetic field on the fast electron beam angular spread and spatial divergence in laser–solid interaction were investigated and energy deposition of these electrons into the high-density fuel was evaluated using Monte Carlo simulation by Geant4 simulation toolkit. In our simulation, two types of the energy distribution function, exponential energy distribution, and quasi-two temperature energy distribution function, for electrons were considered. Our simulations in the presence of an external magnetic field

B

ext

=

0
−
10

kT 

show that the dynamics and spatial divergence of the high energy electrons are strongly affected by the external magnetic field. It was shown that in the case with the two-temperature energy distribution, the number of electrons (electron number density) with a large angular spread in the momentum space which were trapped by the magnetic fields lines and collimated toward the fuel were more populated than that of the exponential function. Comparison of the results indicate that the acceptable condition is obtained for the density

ρ

c

∼
300

g

c

m

−
3

in the presence of a magnetic field of about

B

ext

∼
1
−
2

 

kT

with a laser wavelength

λ

if

=
0.35
μ

m

and laser intensity

I
=

10

21

W

c

m

−
2

. It was presented that in the case with the sufficiently strong external fields,

B

ext

∼
1
−
2

 

kT

, it seems that the optimal results for suppression of electron spatial divergence, electron beam collimation, and energy deposition rate are obtained.
The Electromagnetic Characteristics of the Tianlai Cylindrical Pathfinder Array
Authors: Sun Shijie , Li Jixia , Wu Fengquan , Timbie Peter , Ansari Reza , Geng Jingchao , Shi Huli , Stebbins Albert , Wang Yougang , Zhang Juyong , Chen Xuelei
Published: April 2022

A great challenge for 21 cm intensity mapping experiments is the strong foreground radiation which is orders of magnitude brighter than the 21 cm signal. Removal of the foreground takes advantage of the fact that its frequency spectrum is smooth while the redshifted 21 cm signal spectrum is stochastic. However, a complication is the non-smoothness of the instrument response. This paper describes the electromagnetic simulation of the Tianlai cylinder array, a pathfinder for 21 cm intensity mapping experiments. Due to the vast scales involved, a direct simulation requires a large amount of computing resources. We have made the simulation practical by using a combination of methods: first simulate a single feed, then an array of feed units, finally with the feed array and a cylindrical reflector together, obtain the response for a single cylinder. We studied its radiation pattern, bandpass response and the effects of mutual coupling between feed units, and compared the results with observation. Many features seen in the measurement result are reproduced well in the simulation, especially the oscillatory features which are associated with the standing waves on the reflector. The mutual coupling between feed units is quantified with S-parameters, which decrease as the distance between the two feeds increases. Based on the simulated S-parameters, we estimate the correlated noise which has been seen in the visibility data, and the results show very good agreement with the data in both magnitude and frequency structures. These results provide useful insights on the problem of 21 cm signal extraction for real instruments.
Multicolor Optical Monitoring of the γ -Ray Emitting Narrow-line Seyfert 1 Galaxy PMN J0948+0022 from 2020 to 2021
Authors: Xin Yu-Xin , Xiong Ding-Rong , Bai Jin-Ming , Liu Hong-Tao , Lu Kai-Xing , Mao Ji-Rong
Published: April 2022

In order to study the physical properties of the γ-ray emitting narrow-line Seyfert 1 (NLS1) galaxy population, photometric and spectral observations of the γ-ray emitting NLS1 PMN J0948+0022 were made with the Lijiang 2.4 m optical telescope of Yunnan Observatories, Chinese Academy of Sciences. Photometric data in the B and R bands were collected for 50 nights from 2020 January to 2021 December. During the observation epoch, the variability amplitudes are 73.67% in the B band and 79.96% in the R band. Intra-day variability is found in two observation nights, and the duty cycle value is 29% with variability amplitude > 12.9% in the R band, which support the presence of the relativistic jets in the target. The redder-when-brighter (RWB) chromatic trend (or steeper-when-brighter trend) appears on intra-day and long timescales. The RWB trend is dominated by the radiation of accretion disk and jet, and resembles those in flat spectrum radio quasars. When PMN J0948+0022 is brighter than 17.ͫ5 in the R band, there is no color change trend. By analyzing the spectral data of PMN J0948+0022, we obtained the black hole mass of M
• = 1.61 × 107
M
⊙ and accretion rate of

M

̇

=
93

, and confirmed that PMN J0948+0022 is a super-Eddington accreting NLS1. The redshifts of reverberation mapped super-Eddington accreting active galactic nuclei can be expanded by PMN J0948+0022 up to above 0.5. Super-Eddington accreting NLS1 galaxies were chosen as a new type of cosmological candle in the literature. PMN J0948+0022 may be used as a target for the next step of reverberation mapping monitoring project of super-Eddington accreting massive black holes.
A Framework of High-precision State Estimation for Approaching, Orbiting, and Touching an Asteroid
Authors: Liu Z , Chen X , Li X , Jia F
Published: April 2022

High-precision state estimation lies at the core of asteroid exploration. This paper investigates the high-precision state estimation methods in asteroid approaching, orbiting, and touching phases. The system and measurement models are established, and state estimation strategies are designed respectively for each phase. In the approaching phase, the star image is used to directly determine the relative orbit of the spacecraft to the target asteroid. To improve the optical state estimation precision, a deceleration-orientation-deceleration strategy is developed. In the orbiting phase, coupled orbit-attitude estimation is realized based on the terrain features of the asteroid, and the effect of dynamic error on the accuracy of state estimation is analysed. Then, a decoupled orbit-attitude state estimation method is developed to avoid the affection of dynamic error. In the touching phase, lidar measurement is used to determine the relative orbit and attitude of the spacecraft with respect to the landing spot. Based on the triple-stage state estimation framework proposed in this paper, the relative state error of the spacecraft converges from 100km level to 1mm level.
Finite Element Analysis and Forming Test of Roll Forging of Thin - wall Inner and Outer Gear Cup
Authors: Huang Tao , Guo Yaming , Lu Bo , Xu Hengqiu , Wang Wendong , Cao Ming , Gai Chenxi , Guo Fenghong
Published: April 2022

In this paper, a new forming process method for cup-shaped parts with internal and external teeth structure is proposed, and the forming principle is expounded. The forming characteristics of cup-shaped parts with internal and external teeth are analyzed by finite element method. The stress and strain distribution in different regions of internal teeth, external teeth and side wall are studied. The most prone areas of defects are predicted. The process parameters are determined by simulation. The sample trial production is completed on GD 62-380 roll forging machine, and the comprehensive performance test is verified by carrying HPT330 hydraulic automatic gearbox bench.
Workspace Solution and Space Trajectory Planning of 5-DOF Manipulator
Authors: Xu Zhitian , Zhao Yuhang , Xian Liwei , Lv Bowei , Jiang Wei , Tan Guangdong
Published: April 2022

In this paper, a 5-DOF manipulator is designed to carry the pipeline robot. The joint coordinate system and connecting rod parameters of the manipulator are confirmed by D-H method, and the kinematics model of the manipulator is established. The position and direction of the end of the manipulator are deduced by using the homogeneous transformation method. Monte Carlo method is used to solve the workspace of manipulator, and MATLAB is used to draw the workspace cloud map. Set the motion trajectory of manipulator, using joint space trajectory planning, through MATLAB simulation of motion form, get the change of joint. It provides a foundation for trajectory planning, dynamics analysis, motion control and parameter optimization of manipulator.
Development of a Lever-type Calibration Device
Authors: Zhang Lili , Xie Hongzhen , Zhao Juan
Published: April 2022

This paper mainly introduces a lever-type calibration device to solve the measurement problem of body scale. The design method and design scheme are introduced to verify the feasibility of the device and realize the automatic calibration of the body scale.
Study on the Preparation and Properties of A High Energy Insensitive Narrow Pulse Impact Initiation Primary Explosive
Authors: Chen Likui , Sheng Dilun , Xu Dong , Zhang Shixin
Published: April 2022

Design nano TATB and submicron CL-20 compound compared to submarks and narrow pulses. Nano-stage TATB was prepared by low temperature solvent-non-solvent reverse crystal method; submicron CL-20 was prepared by spray recrystallization and high-energy grinding method. The main performance test and safety test of the compounding agent were carried out. The results show that the composite drug component TATB particle size reaches nanoscale, CL-20 reaches submicron; the composite agent burst is greater than 8000m / s, and the explosion energy is ⩽0.5j, and the pneumatic pills, hot wire, hit, friction, Vacuum stability and other safety experiments. It shows that the agent is a passive high-energy narrow pulse Primary explosive.
Study on the Preparation and Composition of Ultrafine CL-18/HNS
Authors: Wang Peiyong , Zhang Shixing , Xu Dong , Fan Longlong , Zhu Yahong
Published: April 2022

Using solvent-nonsolvent method, study on the preparation and composition of ultrafine CL-18/HNS. Scanning electron microscopy (SEM) was used to characterize the particle size and morphology. The FTIR spectra (IR), differential scanning calorimetry (DSC) and X-ray diffraction (XRD) were utilized to determine whether the cocrystal explosive was prepared. Furthermore, the impact sensitivity and short pulse slapper sensitivity of cocrystal explosive was tested. Results show that the prepared samples are the mix of CL-18 and HNS but rather changed cocrystal appearance of ultrafine CL-18/HNS. The average particle size of cocrystal explosives are 0.98μ. The peak temperatures of exothermic decomposition are 205.36 °C, The impact probability of CL-18/HNS cocrystal explosives is 56 percent, and minimum initiation energy is 0.12J.
Research on the Partition Method Based on the Observation Points of Voltage Distortion in Harmonic Optimization
Authors: Lin Lijuan , Xing Licheng , Jia Qingquan , Zhang Xuerui
Published: April 2022

With the use of a large number of power electronic equipment, the harmonics in the power grid are becoming more and more serious. There are many methods for harmonic mitigation and optimization such as Global network Optimization. When there are many nodes, the global network optimization method is more complicated. Considering the problem of large numbers of harmonic injection nodes in the power grid, this paper proposes a method of clustering the voltage distortion nodes according to correlation, and using the characteristic nodes to describe the harmonic voltage distortion in the region to mitigate harmonic voltage. This method is based on the observation data of the voltage distortion of the nodes for dynamic selection and grouping. The results show that this method meets the needs of Global network Optimization. The data processing methods used in this paper such as feature extraction methods and time series interpolation optimization can effectively reduce the data dimension, and get better optimization effect.
Research on fuzzy neural network for policy simulation of retired power battery
Authors: Yan Hu , Huang Bibin
Published: April 2022

With the acceleration of energy transformation, key mineral resources such as lithium, nickel, and cobalt that new energy development relies on are facing great challenges, and it is necessary to expand secondary supply through recycling. At present, our country has issued a series of policies to encourage the cascade utilization of power batteries, but the incentives still fall short of expectations. Focusing on the pre-simulation of the retired power battery policy, this paper proposes a knowledge-based expression method for the retired policy of retired power battery, and builds an intelligent simulation model based on fuzzy neural network for retired power battery policy, realized the automatic identification of the policy knowledge by the computer and the intelligent simulation of the decision-making behavior of the policy makers, which provides a new idea for the optimization of the retired power battery policy.
Firefly algorithm and ant colony algorithm to optimize the traveling salesman problem
Authors: Yu XiaoFei , Yu LinWen , Zheng MingQiao , Lu JunHui , Zhang Lü
Published: April 2022

Through the study of ACOTSP, it is found that the previous ant colony algorithm will fall into local optimal when increasing pheromone concentration factor. In order to solve the problem, we through the improved pheromone concentration factor to view your traveling salesman solving process, through the simulation experiments found that due to the pheromone concentration gradually increased with the number of iterations, pheromone concentration and pheromone concentration factor exponential relationship, lead to appear even if the distance is large move also can appear probability is very high. In this design, the ant colony algorithm is optimized by introducing firefly algorithm (FA): the ant colony movement deviation is avoided by adding disturbance factor; and the migration probability caused by excessive pheromone concentration is solved by adding function relation between moving distance and pheromone concentration. Simulation results show that the optimized algorithm has better results and is not easy to fall into local optimum.
Particle Swarm Optimization Based on Racing Factor and Mutation Mechanism
Authors: Jia-long Li , Wei Zhang , Lin-lin Ge , Hao Li
Published: April 2022

A hybrid modified Mutation Mechanism (MM) and Racing factor (RF)-based particle swarm optimization (MM-RF-PSO) are presented in this letter. RF and MM are proposed to determine the approximate location of the global optimal solution. Once the approximate position of the optimal solution is determined, a method to dynamically adjust the parameters of algorithm is proposed, so that the algorithm can approach the optimal solution faster. At the same time, when the algorithm falls into the local optimum, a scheme of jumping out of the local optimum is proposed. Compared with other three improved PSO, the simulation results indicate the effectiveness of MM-RF-PSO.
A Progressive and Joint Method for Micro and Macro Architecture Search
Authors: Chen Luoyu
Published: April 2022

Recently, neural architecture search (NAS) has achieved great success in design neural architectures automatically. Differentiable architecture search (DARTS) has succeeded in reducing computational cost and making the searching process efficient. Based on the cell-based search space in DARTS, we extend the search space by searching diverse cells at different stages and various connection between cells. We also use a progressive and joint method to search the micro and macro architecture together. Extensive experiments on CIFAR-10 demostrate that we can obtain a better result than the original search space.
Research of text visualization in 3D environment based on parameter study
Authors: Jing Yinggang , Zhang Fan , Fang Huajian , He Shuan
Published: April 2022

The text visualization in 3D environment is quite complex due to the characteristics of 3D scene. In this paper we propose to study a group of 3D text information visualization based on parameter study. The primary text information visualization position is set as an initial point. Then, several different level-of-details for the texts are designed as the Event LoDs. Firstly, the parameter study for different EventLoDs is conducted, followed by the parameter study for the different size value. Based on the two groups of parameter study result, a use case is applied to test the effect. Finally, the summary and future work is given.
An improved Criminisi method for image inpainting
Authors: Li C , Chen H , Han X , Pan X , Niu D
Published: April 2022

The Criminisi method is a classical image inpainting method, which has flaw of unreasonable priority calculation. To overcome this flaw, we propose an improved Criminisi method. To improve the accuracy of a repaired block’s priority, we propose a novel method by considering the continuity of structure and color information between the repaired block and its adjacent blocks. When searching the matching block for a repaired block, we compute the similar between two blocks as the sum of squared differences (SSD). Since different blocks within an image may contain different levels of information, we set block to different sizes to determine the best matching block. Experimental results demonstrate the effectiveness of the proposed method.
The correlation algorithm based on jittering structured light with multiple reflection imaging
Authors: Zheng Weixin , Huang Ming , Xu Xiao
Published: April 2022

As a three-dimensional reconstruction method, the structured light formed by multiple reflection of neutral beam splitter mirror can effectively solve the problem caused by high reflectivity. In order to obtain more stripes, the jittering mechanism is used in the system. In addition, the linear algorithm can not make full use of the information between different structured light, which will produce a large error and inaccurate result. To solve this problem, we propose a correlation algorithm. In this algorithm, we use two structured light as the independent variables to obtain spatial information, and a related items is calculated to take full advantage of the information between different structured light. Experimental results show that the overall measurement error is reduced by 20-30% and the repetition accuracy of the system reaches 0.02 mm.
Compact Scattering Features for Glaucoma Detection
Authors: Hussain Snawar , Guo Fan , Shi Xiangyu , Li Weiqing , Shen Ziqi
Published: April 2022

In the field of medical image diagnostics, automatic glaucoma classification is a daunting task that requires carefully crafted features (Machine Learning) or tuning hyperparameters over a huge search space (Deep Learning). In this paper, we proposed a wavelet scattering based approach that extracts features from fundus images at different sub-stages, reduces the feature space using principal component analysis (PCA) and represents the classifying features in terms of projection loss along the subspace for each class. This simple yet elegant approach yields fast-paced results with great interpretability, that deep learning-based approaches lack, and excels in most performance metrics when compared to other machine learning based methods.
Study on warpage of the AlSiC substrate in reflow soldering process of the IGBT module
Authors: Wang Wei , Kang Renke , Gao Shang , Wang Rongliang
Published: April 2022

Using the pre-warped substrate to pack IGBT modules can increase the contact area between the substrate and the radiator after the reflow soldering. There are many factors affecting the shape of the substrate’s back after soldering, and determining the effect of each factor by experiments would cost significantly. In this paper, a FEA model of the IGBT module’s reflow soldering process is established by ANSYS to predict the back surface of the pre-warped AlSiC substrate after soldering. Initially, in order to improve the accuracy of the FEA model, the material properties of AlSiC were determined at different temperatures. Subsequently, based on the result of DSC, the solder’s phase transition was simulated in the model. The calculated results showed that the proposed FEA model could predict the shape feature of the AlSiC pre-warped substrate’s back surface after the reflow soldering, and the prediction error of substrate’s residual warpage was 46.05%. The model provides a reliable reference for the design of pre-warped substrate in IGBT module, reducing the test cost and shortening the design period substantially.
Design of Data Acquisition Software for 128-channel μSR Spectrometer Prototype
Authors: Li X.J , Liang H
Published: April 2022

The muon is one of the 12 elementary particles in the standard model, it is a typical particle probes that can extract features such as microscopic magnetic or electronic environments in materials. The technique of injecting spin-polarized muons into a material as a probe and then detecting their spin interaction can be called the μSR technique. A high-intensity muon source experimental device is a prerequisite for the research of μSR technology, with the complettion of China Spallation Neutron Scoure, μSR research has become possible. The data acquisition software introduced in this paper is an experimental 128-channel μSR spectrometer prototype applied to the China Spallation Neutron Source, it is written in C++ based on Qt software, and realizes data acquisition and electronic system control in the form of underlying packet capture by using Winpcap. DAQ software includes data acquisition, command issuing, data format conversion and rough cumulative time spectrum display functions, Each feature will be shown accordingly in the experiment.
Cross-Temporal Snapshot Alignment for Dynamic Multi-Relational Networks
Authors: Chen Lvjia , Liang Shangsong
Published: April 2022

A dynamic network is often represented as a sequence of snapshots evolving over time. In certain real-world scenarios, the identities of nodes in snapshots of a dynamic network are unknown and need to be figured out. To deal with such a challenge, recently, the task of cross-temporal snapshot alignment for dynamic networks is proposed, which aims to match equivalent nodes across temporal snapshots of a dynamic network given a small set of identified nodes. However, in many dynamic multi-relational networks like temporal knowledge graphs, the relation type information of edges, which can be useful for the alignment task, is neglected by existing methods. In this paper, we focus on a similar task but pay special attention to dynamic multi-relational networks. We propose a Relation-Aware Cross-Temporal Snapshot Alignment model (RCTSA) that incorporates time-dependent topological structure information into temporal node embeddings and temporal relation embeddings. To disentangle time-dependent information and time-independent information of the dynamic multi-relational network, RCTSA maintains a time embedding for each snapshot to preserve the temporal information which is incorporated into entity embeddings and relation embeddings to get the temporal embeddings. After training, the learned entity embeddings of unidentified nodes together with time embeddings can be used for the alignment task. Experimental results on real-world dynamic multi-relational networks demonstrate the effectiveness of our model.
A novel concept for a fully digital particle detector
Authors: Casse G. , Massari N. , Franks M. , Parmesan L.
Published: April 2022

Silicon sensors are the most diffuse position sensitive
device in particle physics experiments and in countless applications
in science and technology. They had a spectacular progress in
performance over almost 40 years since their first introduction, but
their evolution is now slowing down. The position resolution for
single particle hits is larger than a few microns in the most
advanced sensors. This value was reached already over 30 years
ago [1]. The minimum ionising path length a sensor can detect
is several tens of microns. There are fundamental reasons why these
limits will not be substantially improved by further refinements of
the current technology. This makes silicon sensors unsuitable to
applications where the physics signature is the short path of a
recoiling atom and constrains the layout of physics experiments
where they represent by far the best option like high energy physics
collider experiments. In perspective, the availability of sensors
with sub-micron spatial resolution, in the order of a few tens of
nanometres, would be a disruptive change for the sensor technology
with a foreseeable huge impact on experiment layout and various
applications of these devices. For providing such a leap in
resolution, we propose a novel design based on a purely digital
circuit. This disruptive concept potentially enables pixel sizes
much smaller than 1 μm2 and a number of advantages in
terms of power consumption, readout speed and reduced thickness (for
low mass sensors).
Any colour you like: fish interacting with bioinspired robots unravel mechanisms promoting mixed phenotype aggregations
Authors: Romano Donato , Stefanini Cesare
Published: April 2022

Collective behaviours in homogeneous shoals provide several benefits to conspecifics, although mixed-species aggregations have been reported to often occur. Mixed aggregations may confer several beneficial effects such as antipredator and foraging advantages. However, the mechanisms promoting phenotypically heterogeneous fish aggregations have been poorly explored so far. Herein, the neon tetra Paracheirodon innesi was selected as the ideal model organism to test the role of visible phenotypic traits in promoting fish shoaling. Robotic fish replicas of different colours, but with a morphology inspired by P. innesi, were developed to test the affiliation behaviour of neon tetra individuals towards fish replicas with different phenotypic traits. P. innesi individuals showed a decreasing preference in shoaling with the biomimetic, the blue, the red, and the grey replicas. This could be due to the greater visibility of the blue colour even in dark conditions. Furthermore, an increased reddening of the livery is often caused by physiological processes related to a nonoptimal behavioural status. The time spent in shoaling with each fish replica was strongly influenced by different ecological contexts. The longest shoaling duration was observed when a biomimetic predator was present, while the shortest shoaling duration was recorded in the presence of food. This confirms the hypothesis that heterogeneous shoals are promoted by the antipredator benefits, and reduced by competition. This study allowed us to understand basic features of the behavioural ecology favouring heterogeneous aggregations in shoaling fish, and provided a novel paradigm for biohybrid robotics.
Widening inequities in clean cooking fuel use and food security: compounding effects of COVID-19 restrictions and VAT on LPG in a Kenyan informal urban settlement
Authors: Shupler Matthew , Menya Diana , Sang Edna , Anderson de Cuevas Rachel , Mang’eni Judith , Lorenzetti Federico , Saligari Serena , Nix Emily , Mwitari James , Gohole Arthur , Pope Daniel , Puzzolo Elisa
Published: April 2022

Universal access to cleaner cooking fuels (including liquefied petroleum gas (LPG)) is a key target of Sustainable Development Goal 7. Currently, approximately 40 million Kenyans rely on polluting cooking fuels (e.g. charcoal, wood). While the Kenyan government aims to rapidly scale up use of LPG for cooking by 2030, COVID-19 restrictions and a 16% value added tax (VAT) re-introduced on LPG in 2021 have likely hampered progress in LPG uptake. We aimed to quantify the effect of these economic shocks on food and energy security in Langas informal urban settlement in western Kenya. We further evaluated whether households most adversely affected by COVID-19 restrictions were more likely to be socioeconomically impacted by the VAT re-imposition. A cross-sectional survey (n = 1542) assessed changes in cooking fuel patterns, food security and livelihoods of primary cooks due to these two economic shocks. While under COVID-19 restrictions, 75% (n = 1147) of participants reported income declines and 18% (n = 164) of participants using LPG (n = 922) switched their primary cooking fuel to charcoal, wood or kerosene. Households reporting lower income while under COVID-19 restrictions had 5.3 times (95% CI:[3.8,7.4]) the odds of experiencing food insecurity as those with no change in income. Unemployment and food insecurity under COVID-19 restrictions were substantially higher among informal sector workers (70% and 60%, respectively) compared with business/government employees (45% and 37%, respectively). Following the VAT re-introduction, 44% (n = 356) of households using LPG consumed less, and 34% (n = 276) cooked more frequently with polluting fuels. Individuals switching away from LPG under COVID-19 restrictions had 3.0 times (95% CI:[2.1,4.3]) the odds of reducing their LPG consumption due to the VAT re-introduction as those maintaining use of LPG. COVID-19 restrictions and the VAT re-introduction disproportionately negatively affected informal sector workers’ livelihoods. A zero-rating of VAT on LPG can help alleviate deepened inequities in LPG access in Kenya.
Social cost of carbon under a carbon-neutral pathway
Authors: Liu Aobo , Chen Yating , Cheng Xiao
Published: April 2022

Climate change is the challenge of the century, and achieving the goals of the Paris Agreement will require worldwide cooperation and mutual effort. Over 120 countries have made their net-zero commitments, and quantifying the social cost of carbon (SCC), i.e. the climate damage caused by an additional ton of CO2 emissions, under a carbon-neutral pathway would provide a carbon price benchmark for policymakers. Here, we set in detail the emission trajectories of different jurisdictions under a carbon-neutral pathway based on the submitted nationally determined contributions. We then assess global and regional warming, climate change damages, and the SCC with the Policy Analysis of Greenhouse Effect integrated assessment model. We find a peak warming of about 2.1 °C relatives to pre-industrial levels in this century under our carbon-neutral emission pathway. And even if all countries meet their carbon-neutral commitments, this would not be sufficient to limit global warming to 1.5 °C relative to pre-industrial levels. We compare the SCC using fixed discount rates, dynamic discounting, and an equity weighting approach. Notably, the introduction of equity weights would increase the estimated SCC from 79 (11–186) to 291 (83–592) US$ per tCO2. Climate change damages will be borne primarily by warmer and poorer countries, and this profound inequality would likely undermine efforts to eradicate extreme poverty. Statistics on current carbon taxes and carbon trading prices show that they are notably lower than global or even regional SCCs, suggesting that the current system does not adequately reflect the global externalities of CO2 emissions. More studies are needed to assess the equity aspects of climate change impacts, to help refine mechanisms to align domestic interests with global interests, and to facilitate the implementation of national carbon-neutral commitments in place.