Imaging characteristics and treatment strategies for carotid artery occlusion caused by skull base fracture:Three case reports

BACKGROUND Traumatic internal carotid artery(ICA)occlusion is a rare complication of skull base fractures,characterized by high mortality and disability rates,and poor prognosis.Therefore,timely discovery and correct management are crucial for saving the lives of such patients and improving their prognosis.This article retrospectively analyzed the imaging and clinical data of three patients,to explore the imaging characteristics and treatment strategies for carotid artery occlusion,combined with severe skull base fractures.CASE SUMMARY This case included three patients,all male,aged 21,63,and 16 years.They underwent plain film skull computed tomography(CT)examination at the onset of their illnesses,which revealed fractures at the bases of their skulls.Ultimately,these cases were definitively diagnosed through CT angiography(CTA)examinations.The first patient did not receive surgical treatment,only anticoagulation therapy,and recovered smoothly with no residual limb dysfunction(Case 1).The other two patients both developed intracranial hypertension and underwent decompressive craniectomy.One of these patients had high intracranial pressure and significant brain swelling postoperatively,leading the family to choose to take him home(Case 2).The other patient also underwent decompressive craniectomy and recovered well postoperatively with only mild limb motor dysfunction(Case 3).We retrieved literature from PubMed on skull base fractures causing ICA occlusion to determine the imaging characteristics and treatment strategies for this type of disease.CONCLUSION For patients with cranial trauma combined with skull base fractures,it is essential to complete a CTA examination as soon as possible,to screen for blunt cerebrovascular injury.

Base Pressure Control with Semi-Circular Ribs at Critical Mach Number

When better fuel-air mixing in the combustion chamber or a reduction in base drag are required in vehicles,rockets,and aeroplanes,the base pressure control is activated.Controlling the base pressure and drag is necessary in both scenarios.In this work,semi-circular ribs with varying diameters(2,4,and 6 mm)positioned at six distinct positions(0.5D,1D,1.5D,2D,3D,and 4D)inside a square duct with a side of 15 mm are proposed as an efficient way to apply the passive control technique.In-depth research is done on optimising rib size for various rib sites.According to this study,the base pressure rises as rib height increases.Furthermore,the optimal location for the semi-circular ribs with a diameter of 2 mm is at 0.5D.The 1D location appears to be optimal for the 4 mm size as well.For the 6 mm size,however,the 4D position fills this function.

Flexible,thermal processable,self-healing,and fully bio-based starch plastics by constructing dynamic imine network

The serious environmental threat caused by petroleum-based plastics has spurred more researches in developing substitutes from renewable sources.Starch is desirable for fabricating bioplastic due to its abundance and renewable nature.However,limitations such as brittleness,hydrophilicity,and thermal properties restrict its widespread application.To overcome these issues,covalent adaptable network was constructed to fabricate a fully bio-based starch plastic with multiple advantages via Schiff base reactions.This strategy endowed starch plastic with excellent thermal processability,as evidenced by a low glass transition temperature(T_(g)=20.15℃).Through introducing Priamine with long carbon chains,the starch plastic demonstrated superior flexibility(elongation at break=45.2%)and waterproof capability(water contact angle=109.2°).Besides,it possessed a good thermal stability and self-adaptability,as well as solvent resistance and chemical degradability.This work provides a promising method to fabricate fully bio-based plastics as alternative to petroleum-based plastics.

Atomically dispersed calcium as solid strong base catalyst with high activity and stability

Solid strong base catalysts are highly attractive for diverse reactions owing to their advantages of neglectable corrosion,facile separation,and environmental friendliness.However,their widespread applications are impeded by basic components aggregation and low stability.In this work,we fabricate single calcium atoms on graphene(denoted as Ca1/G)by use of a redox strategy for the first time,producing solid strong base catalyst with high activity and stability.The precursor Ca(NO_(3))_(2)is first reduced to CaO at 400℃ by the support graphene,forming CaO/G with conventional basic sites,and the subsequent reduction at 850℃results in the generation of Ca1/G with atomically dispersed Ca.Various characterizations reveal that Ca single atoms are anchored on graphene in tetra-coordination(Ca-C_(2)-N_(2))where N is in situ doped from Ca(NO_(3))_(2).The atomically dispersed Ca,along with their anchoring on the support,endow Ca1/G with high activity and stability toward the transesterification reaction of ethylene carbonate with methanol.The turnover frequency value reaches 128.0 h^(-1)on Ca1/G,which is much higher than the traditional counterpart CaO/G and various reported solid strong bases(2.9-46.2 h^(-1)).Moreover,the activity of Ca1/G is well maintained during 5 cycles,while 60%of activity is lost for the conventional analogue CaO/G due to the leaching of Ca.

Elastic wave insulation and propagation control based on the programmable curved-beam periodic structure

Curved-beams can be used to design modular multistable metamaterials(MMMs)with reprogrammable material properties,i.e.,programmable curved-beam periodic structure(PCBPS),which is promising for controlling the elastic wave propagation.The PCBPS is theoretically equivalent to a spring-oscillator system to investigate the mechanism of bandgap,analyze the wave propagation mechanisms,and further form its geometrical and physical criteria for tuning the elastic wave propagation.With the equivalent model,we calculate the analytical solutions of the dispersion relations to demonstrate its adjustability,and investigate the wave propagation characteristics through the PCBPS.To validate the equivalent system,the finite element method(FEM)is employed.It is revealed that the bandgaps of the PCBPS can be turned on-and-off and shifted by varying its physical and geometrical characteristics.The findings are highly promising for advancing the practical application of periodic structures in wave insulation and propagation control.

New construction of mutually unbiased bases for odd-dimensional state space

We study the construction of mutually unbiased bases in Hilbert space for composite dimensions d which are not prime powers.We explore the results for composite dimensions which are true for prime power dimensions.We then provide a method for selecting mutually unbiased vectors from the eigenvectors of generalized Pauli matrices to construct mutually unbiased bases.In particular,we present four mutually unbiased bases in C^(15).

Prediction of Damping Capacity Demand in Seismic Base Isolators via Machine Learning

Base isolators used in buildings provide both a good acceleration reduction and structural vibration control structures.The base isolators may lose their damping capacity over time due to environmental or dynamic effects.This deterioration of them requires the determination of the maintenance and repair needs and is important for the long-termisolator life.In this study,an artificial intelligence prediction model has been developed to determine the damage and maintenance-repair requirements of isolators as a result of environmental effects and dynamic factors over time.With the developed model,the required damping capacity of the isolator structure was estimated and compared with the previously placed isolator capacity,and the decrease in the damping property was tried to be determined.For this purpose,a data set was created by collecting the behavior of structures with single degrees of freedom(SDOF),different stiffness,damping ratio and natural period isolated from the foundation under far fault earthquakes.The data is divided into 5 different damping classes varying between 10%and 50%.Machine learning model was trained in damping classes with the data on the structure’s response to random seismic vibrations.As a result of the isolator behavior under randomly selected earthquakes,the recorded motion and structural acceleration of the structure against any seismic vibration were examined,and the decrease in the damping capacity was estimated on a class basis.The performance loss of the isolators,which are separated according to their damping properties,has been tried to be determined,and the reductions in the amounts to be taken into account have been determined by class.In the developed prediction model,using various supervised machine learning classification algorithms,the classification algorithm providing the highest precision for the model has been decided.When the results are examined,it has been determined that the damping of the isolator structure with the machine learning method is predicted successfully at a level exceeding 96%,and it is an effective method in deciding whether there is a decrease in the damping capacity.

Improving Satellite-Retrieved Cloud Base Height with Ground-Based Cloud Radar Measurements

Cloud base height(CBH) is a crucial parameter for cloud radiative effect estimates, climate change simulations, and aviation guidance. However, due to the limited information on cloud vertical structures included in passive satellite radiometer observations, few operational satellite CBH products are currently available. This study presents a new method for retrieving CBH from satellite radiometers. The method first uses the combined measurements of satellite radiometers and ground-based cloud radars to develop a lookup table(LUT) of effective cloud water content(ECWC), representing the vertically varying cloud water content. This LUT allows for the conversion of cloud water path to cloud geometric thickness(CGT), enabling the estimation of CBH as the difference between cloud top height and CGT. Detailed comparative analysis of CBH estimates from the state-of-the-art ECWC LUT are conducted against four ground-based millimeter-wave cloud radar(MMCR) measurements, and results show that the mean bias(correlation coefficient) is0.18±1.79 km(0.73), which is lower(higher) than 0.23±2.11 km(0.67) as derived from the combined measurements of satellite radiometers and satellite radar-lidar(i.e., Cloud Sat and CALIPSO). Furthermore, the percentages of the CBH biases within 250 m increase by 5% to 10%, which varies by location. This indicates that the CBH estimates from our algorithm are more consistent with ground-based MMCR measurements. Therefore, this algorithm shows great potential for further improvement of the CBH retrievals as ground-based MMCR are being increasingly included in global surface meteorological observing networks, and the improved CBH retrievals will contribute to better cloud radiative effect estimates.

Role of micro-Ca/In alloying in tailoring the microstructural characteristics and discharge performance of dilute Mg-Bi-Sn-based alloys as anodes for Mg-air batteries

The influence of micro-Ca/In alloying on the microstructural charac teristics,electrochemical behaviors and discharge properties of extruded dilute Mg-0.5Bi-0.5Sn-based(wt.%)alloys as anodes for Mg-air batteries are evaluated.The grain size and texture intensity of the Mg-Bi-Sn-based alloys are significantly decreased after the Ca/In alloying,particularly for the In-containing alloy.Note that,in addition to nanoscale Mg_(3)Bi_(2)phase,a new microscale Mg_(2)Bi_(2)Ca phase forms in the Ca-containing alloy.The electrochemical test results demonstrate that Ca/In micro-alloying can enhance the electrochemical activity.Using In to alloy the Mg-Bi-Sn-based alloy is effective in restricting the cathodic hydrogen evolution(CHE)kinetics,leading to a low self-corrosion rate,while severe CHE occurred after Ca alloying.The micro-alloying of Ca/In to Mg-Bi-Sn-based alloy strongly deteriorates the compactness of discharge products film and mitigates the"chunk effect"(CE),hence the cell voltage,anodic efficiency as well as discharge capacity are greatly improved.The In-containing alloy exhibits outstanding discharge performance under the combined effect of the modified microstructure and discharge products,thus making it a potential anode material for primary Mg-air battery.

RoBGP:A Chinese Nested Biomedical Named Entity Recognition Model Based on RoBERTa and Global Pointer

Named Entity Recognition(NER)stands as a fundamental task within the field of biomedical text mining,aiming to extract specific types of entities such as genes,proteins,and diseases from complex biomedical texts and categorize them into predefined entity types.This process can provide basic support for the automatic construction of knowledge bases.In contrast to general texts,biomedical texts frequently contain numerous nested entities and local dependencies among these entities,presenting significant challenges to prevailing NER models.To address these issues,we propose a novel Chinese nested biomedical NER model based on RoBERTa and Global Pointer(RoBGP).Our model initially utilizes the RoBERTa-wwm-ext-large pretrained language model to dynamically generate word-level initial vectors.It then incorporates a Bidirectional Long Short-Term Memory network for capturing bidirectional semantic information,effectively addressing the issue of long-distance dependencies.Furthermore,the Global Pointer model is employed to comprehensively recognize all nested entities in the text.We conduct extensive experiments on the Chinese medical dataset CMeEE and the results demonstrate the superior performance of RoBGP over several baseline models.This research confirms the effectiveness of RoBGP in Chinese biomedical NER,providing reliable technical support for biomedical information extraction and knowledge base construction.

Laboratory Evaluation of Performance Recovery of Aged SBS-modified Asphalt Using Regenerants with Different Base Oil Components

In this study,the regenerative effects of different regenerants on aged SBS-modified asphalt from different perspectives were investigated,including their conventional properties,viscoelastic behavior,creep-related properties,and micromorphology.Base oils composed of different proportions of aromatic and saturated hydrocarbons as well as the styrene-butadiene-styrene(SBS)restorer were used to prepare the regenerants.The results showed that the components of the base oil of the regenerant played a crucial role in determining the characteristics and performance of the recycled SBSmodified asphalt.Regenerants containing a high proportion of aromatics dissolved the hard segment in the SBS restorer,thereby delaying the effect of a reduction in the regenerants on the performance of the aged asphalts at a high temperature.Regenerants containing a high proportion of saturates dissolved the soft segment in the SBS restorer to enhance the lowtemperature performance of the recycled asphalts.In addition,the stress sensitivity of the recycled asphalts increased with the fraction of aromatics in the regenerant.As the aromatic content of the base oil components of the regenerants increased and their saturate content decreased,the state of dispersion of the SBS phase in the recycled SBS-modified asphalts improved.The optimal content of aromatics in the base oil of the regenerants should be set in the range of 33%to 47%to ensure the adequate performance of the recycled asphalts and a high efficiency of the SBS restorer.

Prediction of Lubricant Physicochemical Properties Based on Gaussian Copula Data Expansion

The composition of base oils affects the performance of lubricants made from them.This paper proposes a hybrid model based on gradient-boosted decision tree(GBDT)to analyze the effect of different ratios of KN4010,PAO40,and PriEco3000 component in a composite base oil system on the performance of lubricants.The study was conducted under small laboratory sample conditions,and a data expansion method using the Gaussian Copula function was proposed to improve the prediction ability of the hybrid model.The study also compared four optimization algorithms,sticky mushroom algorithm(SMA),genetic algorithm(GA),whale optimization algorithm(WOA),and seagull optimization algorithm(SOA),to predict the kinematic viscosity at 40℃,kinematic viscosity at 100℃,viscosity index,and oxidation induction time performance of the lubricant.The results showed that the Gaussian Copula function data expansion method improved the prediction ability of the hybrid model in the case of small samples.The SOA-GBDT hybrid model had the fastest convergence speed for the samples and the best prediction effect,with determination coefficients(R^(2))for the four indicators of lubricants reaching 0.98,0.99,0.96 and 0.96,respectively.Thus,this model can significantly reduce the model’s prediction error and has good prediction ability.

A comprehensive review of lunar lava tube base construction and field research on a potential Earth test site

The Moon,as the closest celestial body to the Earth,plays a pivotal role in the progression of deep space exploration,and the establishment of research outposts on its surface represents a crucial step in this mission.Lunar lava tubes are special underground caves formed by volcanic eruptions and are considered as ideal natural shelters and scientific laboratories for lunar base construction.This paper begins with an in-depth overview of the geological origins,exploration history,and distribution locations of lunar lava tubes.Subsequently,it delves into the presentation of four distinctive advantages and typical concepts for constructing bases within lava tubes,summarizing the ground-based attempts made thus far in lunar lava tube base construction.Field studies conducted on a lava tube in Hainan revealed rock compositions similar to those found during the Apollo missions and clear lava tube structures,making it a promising analog site.Lastly,the challenges and opportunities encountered in the field of geotechnical engineering regarding the establishment of lunar lava tube bases are discussed,encompassing cave exploration technologies,in-situ testing methods,geomechanical properties under lunar extreme environments,base design and structural stability assessment,excavation and reinforcement techniques,and simulated Earth-based lava tube base.

Influence of external nitrogen-containing donors on polymerization behavior of neodymium-based cis-1,4-polybutadiene rubber

Neodymium(Nd)-based catalyst in butadiene(Bd)polymerization has drawn interests due to its availability in affording higher cis-1,4-unit selectivity than transition metal(Ti,Co,Ni,etc.)-based catalysts[1-2].Such outstanding high cis-1,4-unit selecti-vity is hypothetically originated from the presence of 4 f orbitals,that can participate in monomer coordination and thereby govern subsequent enchainment manners.This unique characteristic also renders the active species highly susceptible to Lewis bases,and may impact the overall selectivity as well as polyme-rization behavior after coordination.Nevertheless,it is still a virgin area in such a field,and the influence of Lewis bases on Nd-based diene polymerizations is still a black box.Based on this consideration,how nitrogen-containing donors(D)impacts the overall behaviors of Nd-mediated Bd polymerizations is disclosed.

Buckling Optimization of Curved Grid Stiffeners through the Level Set Based Density Method

Stiffened structures have great potential for improvingmechanical performance,and the study of their stability is of great interest.In this paper,the optimization of the critical buckling load factor for curved grid stiffeners is solved by using the level set based density method,where the shape and cross section(including thickness and width)of the stiffeners can be optimized simultaneously.The grid stiffeners are a combination ofmany single stiffenerswhich are projected by the corresponding level set functions.The thickness and width of each stiffener are designed to be independent variables in the projection applied to each level set function.Besides,the path of each single stiffener is described by the zero iso-contour of the level set function.All the single stiffeners are combined together by using the p-norm method to obtain the stiffener grid.The proposed method is validated by several numerical examples to optimize the critical buckling load factor.

Solid-state NMR of the retinal protonated Schiff base in microbial rhodopsins

Rhodopsin is a seven-helical transmembrane protein with a retinal chromophore covalently bound to a conserved lysine in helix G via a retinal protonated Schiff base(RPSB).Microbial rhodopsins absorb light through chromophore and play a fundamental role in optogenetics.Numerous microbial rhodopsins have been discovered,contributing to diverse functions and colors.Solid-state NMR spectroscopy has been instrumental in elucidating the conformation of chromophores and the three-dimensional structure of microbial rhodopsins.This review focuses on the 15N chemical shift values of RPSB and summarizes recent progress in the field.We displayed the correlation between the 15N isotropic chemical shift values of RPSB and the maximum absorption wavelength of rhodopsin using solid-state NMR spectroscopy.

Layer by Layer Self-assembly Fiber-based Flexible Electrochemical Transistor

Poly(3,4-ethylenedioxyethiophene)-polystyrene sulfonic acid(PEDOT:PSS)/polyallyl dimethyl ammonium chloride modified reduced graphene oxide(PDDA-rGO)was layer by layer self-assembled on the cotton fiber.The surface morphology and electric property was investigated.The results confirmed the dense membrane of PEDOT:PSS and the lamellar structure of PDDA-rGO on the fibers.It has excellent electrical conductivity and mechanical properties.The fiber based electrochemical transistor(FECTs)prepared by the composite conductive fiber has a maximum output current of 8.7 mA,a transconductance peak of 10 mS,an on time of 1.37 s,an off time of 1.6 s and excellent switching stability.Most importantly,the devices by layer by layer self-assembly technology opens a path for the true integration of organic electronics with traditional textile technologies and materials,laying the foundation for their later widespread application.

Physics-Based Active Learning for Design Space Exploration and Surrogate Construction for Multiparametric Optimization

The sampling of the training data is a bottleneck in the development of artificial intelligence(AI)models due to the processing of huge amounts of data or to the difficulty of access to the data in industrial practices.Active learning(AL)approaches are useful in such a context since they maximize the performance of the trained model while minimizing the number of training samples.Such smart sampling methodologies iteratively sample the points that should be labeled and added to the training set based on their informativeness and pertinence.To judge the relevance of a data instance,query rules are defined.In this paper,we propose an AL methodology based on a physics-based query rule.Given some industrial objectives from the physical process where the AI model is implied in,the physics-based AL approach iteratively converges to the data instances fulfilling those objectives while sampling training points.Therefore,the trained surrogate model is accurate where the potentially interesting data instances from the industrial point of view are,while coarse everywhere else where the data instances are of no interest in the industrial context studied.

An Improved Bounded Conflict-Based Search for Multi-AGV Pathfinding in Automated Container Terminals

As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards.For larger terminalmaps and complex environments,the grid method is employed to model AGVs’road networks.An improved bounded conflict-based search(IBCBS)algorithmtailored to ACT is proposed,leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range.Comparative experiments involving 60 AGVs indicate a reduction in computing time by 37.397%to 64.06%while maintaining the over cost within 1.019%.Numerical experiments validate the proposed algorithm’s efficacy in enhancing efficiency and ensuring solution quality.

Preparation of palladium-based catalyst by plasma-assisted atomic layer deposition and its applications in CO_(2) hydrogenation reduction

Supported Pd catalyst is an important noble metal material in recent years due to its high catalytic performance in CO_(2)hydrogenation.A fluidized-bed plasma assisted atomic layer deposition(FP-ALD) process is reported to fabricate Pd nanoparticle catalyst over γ-Al_(2)O_(3)or Fe_(2)O_(3)/γ-Al_(2)O_(3)support,using palladium hexafluoroacetylacetonate as the Pd precursor and H_(2)plasma as counter-reactant.Scanning transmission electron microscopy exhibits that highdensity Pd nanoparticles are uniformly dispersed over Fe_(2)O_(3)/γ-Al_(2)O_(3)support with an average diameter of 4.4 nm.The deposited Pd-Fe_(2)O_(3)/γ-Al_(2)O_(3)shows excellent catalytic performance for CO_(2)hydrogenation in a dielectric barrier discharge reactor.Under a typical condition of H_(2)to CO_(2)ratio of 4 in the feed gas,the discharge power of 19.6 W,and gas hourly space velocity of10000 h^(-1),the conversion of CO_(2)is as high as 16.3% with CH_(3)OH and CH4selectivities of 26.5%and 3.9%,respectively.