Transforming Adolescent Smiles:Correcting Skeletal Mandibular Retrusion and Bimaxillary Protrusion with Clear Aligners

Maxillary protrusion combined with mandibular retraction is a highly prevalent but extremely complex maxillofacial deformity that can have a serious negative impact on patients’facial aesthetics and mental health.The traditional orthodontic treatment strategy often involves extracting 4 first premolars and conventional fixed techniques,combined with mini-implant screws,to retract the anterior teeth and improve facial protrusion.In recent years,an invisible orthodontic technique,without brackets,has become increasingly popular.However,while an invisible aligner has been used in some cases with reasonable results,there remain significant challenges in achieving a perfect outcome.This case report presents an adolescent patient with bimaxillary protrusion and mandibular retrognathia.Based on the characteristics of the invisible aligners and the growth characteristics of the adolescent’s teeth and jawbone,we designed precise three-dimensional tooth movement and corresponding resistance/over-correction for each tooth,while utilizing the patient’s jawbone growth potential to promote rapid development of the mandible,accurately and efficiently correcting bimaxillary protrusion and skeletal mandibular retrognathia.The patient’s facial aesthetics,especially the lateral morphology,have been greatly improved,and various aesthetic indicators have also shown significant changes,and to the patient’s great benefit,invasive mini-implant screws were not used during the treatment.This case highlights the advantages of using invisible aligners in adolescent maxillary protrusion combined with mandibular retraction patients.Furthermore,comprehensive and accurate design combined with good application of growth potential can also enable invisible orthodontic technology to achieve perfect treatment effects in tooth extractions,providing clinical guidance for orthodontists.

Highly Aligned Graphene Aerogels for Multifunctional Composites

Stemming from the unique in-plane honeycomb lattice structure and the sp^(2)hybridized carbon atoms bonded by exceptionally strong carbon–carbon bonds,graphene exhibits remarkable anisotropic electrical,mechanical,and thermal properties.To maximize the utilization of graphene’s in-plane properties,pre-constructed and aligned structures,such as oriented aerogels,films,and fibers,have been designed.The unique combination of aligned structure,high surface area,excellent electrical conductivity,mechanical stability,thermal conductivity,and porous nature of highly aligned graphene aerogels allows for tailored and enhanced performance in specific directions,enabling advancements in diverse fields.This review provides a comprehensive overview of recent advances in highly aligned graphene aerogels and their composites.It highlights the fabrication methods of aligned graphene aerogels and the optimization of alignment which can be estimated both qualitatively and quantitatively.The oriented scaffolds endow graphene aerogels and their composites with anisotropic properties,showing enhanced electrical,mechanical,and thermal properties along the alignment at the sacrifice of the perpendicular direction.This review showcases remarkable properties and applications of aligned graphene aerogels and their composites,such as their suitability for electronics,environmental applications,thermal management,and energy storage.Challenges and potential opportunities are proposed to offer new insights into prospects of this material.

Alignment Techniques in Total Knee Arthroplasty:Where do We Stand Today?

Achieving optimal alignment in total knee arthroplasty(TKA) is a critical factor in ensuring optimal outcomes and long-term implant survival. Traditionally, mechanical alignment has been favored to achieve neutral postoperative joint alignment. However, contemporary approaches, such as kinematic alignments and hybrid techniques including adjusted mechanical, restricted kinematic, inverse kinematic, and functional alignments, are gaining attention for their ability to restore native joint kinematics and anatomical alignment, potentially leading to enhanced functional outcomes and greater patient satisfaction. The ongoing debate on optimal alignment strategies considers the following factors: long-term implant durability, functional improvement, and resolution of individual anatomical variations. Furthermore, advancements of computer-navigated and robotic-assisted surgery have augmented the precision in implant positioning and objective measurements of soft tissue balance. Despite ongoing debates on balancing implant longevity and functional outcomes, there is an increasing advocacy for personalized alignment strategies that are tailored to individual anatomical variations. This review evaluates the spectrum of various alignment techniques in TKA, including mechanical alignment, patient-specific kinematic approaches, and emerging hybrid methods. Each technique is scrutinized based on its fundamental principles, procedural techniques, inherent advantages, and potential limitations, while identifying significant clinical gaps that underscore the need for further investigation.

Joint alignment and steering to manage interference

In wireless communication networks,mobile users in overlapping areas may experience severe interference,therefore,designing effective Interference Management(IM)methods is crucial to improving network performance.However,when managing multiple disturbances from the same source,it may not be feasible to use existing IM methods such as Interference Alignment(IA)and Interference Steering(IS)exclusively.It is because with IA,the aligned interference becomes indistinguishable at its desired Receiver(Rx)under the cost constraint of Degrees-of-Freedom(DoF),while with IS,more transmit power will be consumed in the direct and repeated application of IS to each interference.To remedy these deficiencies,Interference Alignment Steering(IAS)is proposed by incorporating IA and IS and exploiting their advantages in IM.With IAS,the interfering Transmitter(Tx)first aligns one interference incurred by the transmission of one data stream to a one-dimensional subspace orthogonal to the desired transmission at the interfered Rx,and then the remaining interferences are treated as a whole and steered to the same subspace as the aligned interference.Moreover,two improved versions of IAS,i.e.,IAS with Full Adjustment at the Interfering Tx(IAS-FAIT)and Interference Steering and Alignment(ISA),are presented.The former considers the influence of IA on the interfering user-pair's performance.The orthogonality between the desired signals at the interfered Rx can be maintained by adjusting the spatial characteristics of all interferences and the aligned interference components,thus ensuring the Spectral Efficiency(SE)of the interfering communication pairs.Under ISA,the power cost for IS at the interfered Tx is minimized,hence improving SE performance of the interfered communication-pairs.Since the proposed methods are realized at the interfering and interfered Txs cooperatively,the expenses of IM are shared by both communication-pairs.Our in-depth simulation results show that joint use of IA and IS can effectively manage multiple disturbances from the same source and improve the system's SE.

Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

Beam based alignment using a neural network

Beams typically do not travel through the magnet centers because of errors in storage rings.The beam deviating from the quadrupole centers is affected by additional dipole fields due to magnetic field feed-down.Beam-based alignment(BBA)is often performed to determine a golden orbit where the beam circulates around the quadrupole center axes.For storage rings with many quadrupoles,the conventional BBA procedure is time-consuming,particularly in the commissioning phase,because of the necessary iterative process.In addition,the conventional BBA method can be affected by strong coupling and the nonlinearity of the storage ring optics.In this study,a novel method based on a neural network was proposed to determine the golden orbit in a much shorter time with reasonable accuracy.This golden orbit can be used directly for operation or adopted as a starting point for conventional BBA.The method was demonstrated in the HLS-II storage ring for the first time through simulations and online experiments.The results of the experiments showed that the golden orbit obtained using this new method was consistent with that obtained using the conventional BBA.The development of this new method and the corresponding experiments are reported in this paper.

A Time Series Short-Term Prediction Method Based on Multi-Granularity Event Matching and Alignment

Accurate forecasting of time series is crucial across various domains.Many prediction tasks rely on effectively segmenting,matching,and time series data alignment.For instance,regardless of time series with the same granularity,segmenting them into different granularity events can effectively mitigate the impact of varying time scales on prediction accuracy.However,these events of varying granularity frequently intersect with each other,which may possess unequal durations.Even minor differences can result in significant errors when matching time series with future trends.Besides,directly using matched events but unaligned events as state vectors in machine learning-based prediction models can lead to insufficient prediction accuracy.Therefore,this paper proposes a short-term forecasting method for time series based on a multi-granularity event,MGE-SP(multi-granularity event-based short-termprediction).First,amethodological framework for MGE-SP established guides the implementation steps.The framework consists of three key steps,including multi-granularity event matching based on the LTF(latest time first)strategy,multi-granularity event alignment using a piecewise aggregate approximation based on the compression ratio,and a short-term prediction model based on XGBoost.The data from a nationwide online car-hailing service in China ensures the method’s reliability.The average RMSE(root mean square error)and MAE(mean absolute error)of the proposed method are 3.204 and 2.360,lower than the respective values of 4.056 and 3.101 obtained using theARIMA(autoregressive integratedmoving average)method,as well as the values of 4.278 and 2.994 obtained using k-means-SVR(support vector regression)method.The other experiment is conducted on stock data froma public data set.The proposed method achieved an average RMSE and MAE of 0.836 and 0.696,lower than the respective values of 1.019 and 0.844 obtained using the ARIMA method,as well as the values of 1.350 and 1.172 obtained using the k-means-SVR method.

Hierarchical Optimization Method for Federated Learning with Feature Alignment and Decision Fusion

In the realm of data privacy protection,federated learning aims to collaboratively train a global model.However,heterogeneous data between clients presents challenges,often resulting in slow convergence and inadequate accuracy of the global model.Utilizing shared feature representations alongside customized classifiers for individual clients emerges as a promising personalized solution.Nonetheless,previous research has frequently neglected the integration of global knowledge into local representation learning and the synergy between global and local classifiers,thereby limiting model performance.To tackle these issues,this study proposes a hierarchical optimization method for federated learning with feature alignment and the fusion of classification decisions(FedFCD).FedFCD regularizes the relationship between global and local feature representations to achieve alignment and incorporates decision information from the global classifier,facilitating the late fusion of decision outputs from both global and local classifiers.Additionally,FedFCD employs a hierarchical optimization strategy to flexibly optimize model parameters.Through experiments on the Fashion-MNIST,CIFAR-10 and CIFAR-100 datasets,we demonstrate the effectiveness and superiority of FedFCD.For instance,on the CIFAR-100 dataset,FedFCD exhibited a significant improvement in average test accuracy by 6.83%compared to four outstanding personalized federated learning approaches.Furthermore,extended experiments confirm the robustness of FedFCD across various hyperparameter values.

Paving continuous heat dissipation pathways for quantum dots in polymer with orangeinspired radially aligned UHMWPE fibers

Thermal management of nanoscale quantum dots(QDs)in light-emitting devices is a long-lasting challenge.The existing heat transfer reinforcement solutions for QDs-polymer composite mainly rely on thermal-conductive fillers.However,this strategy failed to deliver the QDs’heat generation across a long distance,and the accumulated heat still causes considerable temperature rise of QDs-polymer composite,which eventually menaces the performance and reliability of lightemitting devices.Inspired by the radially aligned fruit fibers in oranges,we proposed to eliminate this heat dissipation challenge by establishing long-range ordered heat transfer pathways within the QDs-polymer composite.Ultrahigh molecular weight polyethylene fibers(UPEF)were radially aligned throughout the polymer matrix,thus facilitating massive efficient heat dissipation of the QDs.Under a UPEF filling fraction of 24.46 vol%,the in-plane thermal conductivity of QDs-radially aligned UPEF composite(QDs-RAPE)could reach 10.45 W m^(−1) K^(−1),which is the highest value of QDs-polymer composite reported so far.As a proof of concept,the QDs’working temperature can be reduced by 342.5℃ when illuminated by a highly concentrated laser diode(LD)under driving current of 1000 mA,thus improving their optical performance.This work may pave a new way for next generation high-power QDs lighting applications.

P-and SV-wave dispersion and attenuation in saturated microcracked porous rock with aligned penny-shaped fractures

P-and SV-wave dispersion and attenuation have been extensively investigated in saturated poroelastic media with aligned fractures.However,there are few existing models that incorporate the multiple wave attenuation mechanisms from the microscopic scale to the macroscopic scale.Hence,in this work,we developed a unified model to incorporate the wave attenuation mechanisms at different scales,which includes the microscopic squirt flow between the microcracks and pores,the mesoscopic wave-induced fluid flow between fractures and background(FB-WIFF),and the macroscopic Biot's global flow and elastic scattering(ES)from the fractures.Using Tang's modified Biot's theory and the mixed-boundary conditions,we derived the exact frequency-dependent solutions of the scattering problem for a single penny-shaped fracture with oblique incident P-and SV-waves.We then developed theoretical models for a set of aligned fractures and randomly oriented fractures using the Foldy approximation.The results indicated that microcrack squirt flow considerably influences the dispersion and attenuation of P-and SV-wave velocities.The coupling effects of microcrack squirt flow with the FB-WIFF and ES of fractures cause much higher velocity dispersion and attenuation for P waves than for SV waves.Randomly oriented fractures substantially reduce the attenuation caused by the FB-WIFF and ES,particularly for the ES attenuation of SV waves.Through a comparison with existing models in the limiting cases and previous experimental measurements,we validated our model.

A Study on Aligning Nursing Curriculum with Hospital Clinical Competency Requirements

The purpose of this study is to coordinate the alignment between the nursing curriculum and hospital clinical competencies,identify the reasons for the gaps,evaluate the impact of these gaps on the nursing profession,and propose strategies to bridge these gaps.This study will help strengthen nursing education,improve nursing students’skills,and help students adapt to complex clinical environments.

On The Cauchy Problem for A 1D Euler-Alignment System in Besov Spaces

In this paper, we investigate a 1D pressureless Euler-alignment system with a non-local alignment term, describing a kind of self-organizing problem for flocking. As a result, by the transport equation theory and Lagrange coordinate transformation, the local well-posedness of the solutions for the 1D pressureless Euler-alignment in Besov spaces with 1≤p∞ is established. Next, the ill-posedness of the solutions for this model in Besov spaces with 1≤p and is also deduced. Finally, the precise blow-up criteria of the solutions for this system is presented in Besov spaces with 1≤p .

Colour stabilities of three types of orthodontic clear aligners exposed to staining agents

The aim of this study was to evaluate and compare the colour stabilities of three types of orthodontic clear aligners exposed to staining agents in vitro. Sixty clear orthodontic aligners produced by three manufacturers （Invisalign, Angelalign, and Smartee） were immersed in three staining solutions （coffee, black tea, and red wine） and one control solution （distilled water）. After 12-h and 7-day immersions, the aligners were washed in an ultrasonic cleaner and measured with a colourimeter. The colour changes （△E＊） were calculated on the basis of the Commission Internationale de I＇Eclairage L＊a＊b＊ colour system （CIE L＊a＊b＊）, and the results were then converted into National Bureau of Standards （NBS） units. Fourier transformation infrared （FT-IR） spectroscopy and scanning electron microscopy （SEM） were conducted to observe the molecular and morphologic alterations to the aligner surfaces, respectively. The three types of aligners exhibited slight colour changes after 12 h of staining, with the exception of the Invisalign aligners stained with coffee. The Invisalign aligners exhibited significantly higher AE＊ values （ranging from 0.30 to 27.81） than those of the Angelalign and Smartee aligners （AE＊ values ranging from 0.33 to 1.89 and 0.32 to 1.61, respectively, P〈O.05）. IFT-IR analysis confirmed that the polymer-based structure of aligners did not exhibit significant chemical differences before and after the immersions. The SEM results revealed different surface alterations to the three types of aligner materials after the 7-day staining. The three types of aesthetic orthodontic appliances exhibited colour stability after the 12-h immersion, with the exception of the Invisalign aligners stained by coffee. The Invisalign aligners were more prone than the Angelalign and Smartee aligners to pigmentation. Aligner materials may be improved by considering aesthetic colour stability properties.

ABBYY Aligner和Tmxmall对齐工具主要功能探究对比

计算机辅助翻译软件大大提高了翻译效率。本文试从用户角度,以对齐工具中的ABBYY Aligner独立式对齐工具和Tmxmall在线对齐工具为例,对这两种对齐工具的主要特性和功能进行对比和研究,以期帮助译员找到适合自己的、能满足用户个性化需求的对齐工具,从而提高翻译效率和准确率。

Vector meson spin alignment by the strong force field

Observation of unexpectedly large global spin alignment of φ vector mesons in non-central heavy-ion collisions by STAR experiment may reveal the non-perturbative nature of quark interaction in hot matter through fluctuating strong force field with short correlation length.

Functionalized alginate-based bioinks for microscale electrohydrodynamic bioprinting of living tissue constructs with improved cellular spreading and alignment

Bioprinting has been widely investigated for tissue engineering and regenerative medicine applications.However,it is still difficult to reconstruct the complex native cell arrangement due to the limited printing resolution of conventional bioprinting techniques such as extrusion-and inkjet-based printing.Recently,an electrohydrodynamic(EHD)bioprinting strategy was reported for the precise deposition of well-organized cell-laden constructs with microscale filament size,whereas few studies have been devoted to developing bioinks that can be applied for EHD bioprinting and simultaneously support cell spreading.This study describes functionalized alginate-based bioinks for microscale EHD bioprinting using peptide grafting and fibrin incorporation,which leads to high cell viability(>90%)and cell spreading.The printed filaments can be further refined to as small as 30μm by incorporating polyoxyethylene and remained stable over one week when exposed to an aqueous environment.By utilizing the presented alginate-based bioinks,layer-specific cell alignment along the printing struts could be observed inside the EHD-printed microscale filaments,which allows fabricating living constructs with cell-scale filament resolution for guided cellular orientation.

Photo-induced flexible semiconductor CdSe/CdS quantum rods alignment

The anisotropic absorption and emission from semiconductor CdSe/CdS quantum rods(QRs)provide extra benefits among other photoluminescence nanocrystals.Using photo-induced alignment technique,the QRs can be oriented in liquid crystal polymer matrix at a large scale.In this article,a 2D Dammann grating pattern,within“SKL”characters domains aligned QRs in composite film,was fabricated by multi-step photo exposure using several photo masks,and a continuous geometric lens profile pattern aligned QRs was realized by the single step polarization converting holographic irradiation method.Both polarized optical microscope and fluorescence microscope are employed to determine the liquid crystal director profiles and QRs anisotropic excitation properties.We have been able to orient the QRs in fine binary and continuous patterns that confirms the strong quantum rod aligning ability of the proposed method.Thus,the proposed approach paves a way for photoinduced flexible QRs alignments to provide a highly specific and difficult-to-replicate security application at a large scale.

MPC-based Torque Distribution for Planar Motion of Four-wheel Independently Driven Electric Vehicles:Considering Motor Models and Iron Losses

The most critical obstacle for four-wheel independently driven electric vehicles(4WID-EVs)is the driving range.Being the actuators of 4WID-EVs,motors account for its major power consumption.In this sense,by properly distributing torques to minimize the power consumption,the driving range of 4WID-EV can be effectively improved.This paper proposes a model predictive control(MPC)-based torque distribution scheme,which minimizes the power consumption of 4WID-EVs while guaranteeing its tracking performance of planar motions.By incorporating the motor model considering iron losses,the optimal torque distribution can be achieved without an additional torque controller.Also,for this reason,the proposed control scheme is computationally efficient,since the power consumption term to be optimized,which is expressed as the product of the motor voltages and currents,is much simpler than that derived from the efficiency map.With reasonable simplification and linearization,the MPC problem is converted to a quadratic programming problem,which can be solved efficiently.The simulation results in MATLAB and CarSim co-simulation environments demonstrate that the proposed scheme effectively reduces power consumption with guaranteed tracking performance.

Deep learning for estimation of Kirkpatrick-Baez mirror alignment errors

A deep learning-based automated Kirkpatrick-Baez mirror alignment method is proposed for synchrotron radiation.We trained a convolutional neural network(CNN)on simulated and experimental imaging data of a focusing system.Instead of learning directly from bypass images,we use a scatterer for X-ray modulation and speckle generation for image feature enhancement.The smallest normalized root-mean-square error on the validation set was 4%.Compared with conventional alignment methods based on motor scanning and analyzer setups,the present method simplified the optical layout and estimated alignment errors using a single-exposure experiment.Single-shot misalignment error estimation only took 0.13 s,significantly outperforming conventional methods.We also demonstrated the effects of the beam quality and pretraining using experimental data.The proposed method exhibited strong robustness,can handle high-precision focusing systems with complex or dynamic wavefront errors,and provides an important basis for intelligent control of future synchrotron radiation beamlines.

Precision measurement and suppression of low-frequency noise in a current source with double-resonance alignment magnetometers

Low-noise high-stability current sources have essential applications such as neutron electric dipole moment measurement and high-stability magnetometers. Previous studies mainly focused on frequency noise above 0.1 Hz while less on the low-frequency noise/drift. We use double resonance alignment magnetometers(DRAMs) to measure and suppress the low-frequency noise of a homemade current source(CS) board. The CS board noise level is suppressed by about 10 times in the range of 0.001-0.1 Hz and is reduced to 100 n A/√Hz at 0.001 Hz. The relative stability of CS board can reach2.2 × 10^(-8). In addition, the DRAM shows a better resolution and accuracy than a commercial 7.5-digit multimeter when measuring our homemade CS board. Further, by combining the DRAM with a double resonance orientation magnetometer,we may realize a low-noise CS in the 0.001-1000 Hz range.