Vein visualization enhancement by dual-wavelength phase-locked denoising technology

Visual near-infrared imaging equipment has broad applications in various fields such as venipuncture,facial injections,and safety verification due to its noncontact,compact,and portable design.Currently,most studies utilize near-infrared single-wavelength for image acquisition of veins.However,many substances in the skin,including water,protein,and melanin can create significant background noise,which hinders accurate detection.In this paper,we developed a dual-wavelength imaging system with phase-locked denoising technology to acquire vein image.The signals in the effective region are compared by using the absorption valley and peak of hemoglobin at 700nm and 940nm,respectively.The phase-locked denoising algorithm is applied to decrease the noise and interference of complex surroundings from the images.The imaging results of the vein are successfully extracted in complex noise environment.It is demonstrated that the denoising effect on hand veins imaging can be improved with 57.3%by using our dual-wavelength phase-locked denoising technology.Consequently,this work proposes a novel approach for venous imaging with dual-wavelengths and phase-locked denoising algorithm to extract venous imaging results in complex noisy environment better.

Traffic prediction enabled dynamic access points switching for energy saving in dense networks

To meet the ever-increasing traffic demand and enhance the coverage of cellular networks,network densification is one of the crucial paradigms of 5G and beyond mobile networks,which can improve system capacity by deploying a large number of Access Points(APs)in the service area.However,since the energy consumption of APs generally accounts for a substantial part of the communication system,how to deal with the consequent energy issue is a challenging task for a mobile network with densely deployed APs.In this paper,we propose an intelligent AP switching on/off scheme to reduce the system energy consumption with the prerequisite of guaranteeing the quality of service,where the signaling overhead is also taken into consideration to ensure the stability of the network.First,based on historical traffic data,a long short-term memory method is introduced to predict the future traffic distribution,by which we can roughly determine when the AP switching operation should be triggered;second,we present an efficient three-step AP selection strategy to determine which of the APs would be switched on or off;third,an AP switching scheme with a threshold is proposed to adjust the switching frequency so as to improve the stability of the system.Experiment results indicate that our proposed traffic forecasting method performs well in practical scenarios,where the normalized root mean square error is within 10%.Furthermore,the achieved energy-saving is more than 28% on average with a reasonable outage probability and switching frequency for an area served by 40 APs in a commercial mobile network.

EGFR突变影响非小细胞肺癌PD-L1表达的研究进展

近年来,有关程序性死亡受体1 (programmed death-1,PD-1)及其配体(programmed death-1 ligand,PD-L1)抑制剂的研究取得突破性进展,迅速改变着非小细胞肺癌(non-small cell lung cancer,NSCLC)的治疗模式。但表皮生长因子受体(epidermalgrowthfactorreceptor,EGFR)突变患者应用PD-1/PD-L1抑制剂的治疗效果并不理想。既往研究显示,肿瘤细胞PD-L1表达率与免疫抑制剂治疗效果存在相关性。但目前EGFR突变对PD-L1表达的影响并不能达成一致。我们将对相关研究进行总结,以期对基础研究或临床治疗有所帮助。

Machine Learning for 5G and Beyond:From ModelBased to Data-Driven Mobile Wireless Networks

During the past few decades,mobile wireless communications have experienced four generations of technological revolution,namely from 1 G to 4 G,and the deployment of the latest 5 G networks is expected to take place in 2019.One fundamental question is how we can push forward the development of mobile wireless communications while it has become an extremely complex and sophisticated system.We believe that the answer lies in the huge volumes of data produced by the network itself,and machine learning may become a key to exploit such information.In this paper,we elaborate why the conventional model-based paradigm,which has been widely proved useful in pre-5 G networks,can be less efficient or even less practical in the future 5 G and beyond mobile networks.Then,we explain how the data-driven paradigm,using state-of-the-art machine learning techniques,can become a promising solution.At last,we provide a typical use case of the data-driven paradigm,i.e.,proactive load balancing,in which online learning is utilized to adjust cell configurations in advance to avoid burst congestion caused by rapid traffic changes.

Numerical solution of oscillatory flow of Maxwell fluid in a rectangular straight duct

A numerical analysis is presented for the oscillatory flow of Maxwell fluid in a rectangular straight duct subjected to a simple harmonic periodic pressure gradient.The numerical solutions are obtained by a finite difference scheme method.The stability of this finite difference scheme method is discussed.The distributions of the velocity and phase difference are given numerically and graphically.The effects of the Reynolds number,relaxation time,and aspect ratio of the cross section on the oscillatory flow are investigated.The results show that when the relaxation time of the Maxwell model and the Reynolds number increase,the resonance phenomena for the distributions of the velocity and phase difference enhance.

An Approach for Quantifying the Influence of Seepage Dissolution on Seismic Performance of Concrete Dams

Many concrete dams seriously suffer from long-term seepage dissolution,and the induced mechanical property deterioration of concrete may significantly affect the structural performance,especially the seismic safety.An approach is presented in this paper to quantify the influence of seepage dissolution on seismic performance of concrete dams.To connect laboratory test with numerical simulation,dissolution tests are conducted for concrete specimens and using the cumulative relative leached calcium as an aging index,a deterioration model is established to predict the mechanical property of leached concrete in the first step.A coupled seepage-calcium dissolutionmigrationmodel containing two calculation modes is proposed to simulate the spatially non-uniformdeterioration of concrete dams.Based on the simulated state of a roller compacted concrete dam subjected to 100 years of seepage dissolution,seismic responses of the damare subsequently analyzed.During which the nonlinear cracking of concrete,the radiation damping of the far-field foundation is considered.Research results show that seepage dissolution will seriously weaken the seismic safety of concrete dams because of the dissolution-induced decrease of effective thickness of the dam body.The upstream surface,dam toe and gallery wall suffer from a large degree of dissolution,whereas it is minimal and basically the same inside the dam body,at a degree of 0.19%within 100 years.The horizontal displacements of dam crest under the design static load and fortification against earthquake increase by 6.9%and 21.9%,respectively,and the dissolution-induced seismic cracking leads to the failure of dam anti-seepage system.This study can provide engineers with a reference basis for reinforcement decision of old concrete dams.

Toward intelligent wireless communications:Deep learning-based physical layer technologies

Advanced technologies are required in future mobile wireless networks to support services with highly diverse requirements in terms of high data rate and reliability,low latency,and massive access.Deep Learning(DL),one of the most exciting developments in machine learning and big data,has recently shown great potential in the study of wireless communications.In this article,we provide a literature review on the applications of DL in the physical layer.First,we analyze the limitations of existing signal processing techniques in terms of model accuracy,global optimality,and computational scalability.Next,we provide a brief review of classical DL frameworks.Subsequently,we discuss recent DL-based physical layer technologies,including both DL-based signal processing modules and end-to-end systems.Deep neural networks are used to replace a single or several conventional functional modules,whereas the objective of the latter is to replace the entire transceiver structure.Lastly,we discuss the open issues and research directions of the DL-based physical layer in terms of model complexity,data quality,data representation,and algorithm reliability.

Clustering-based interference management in densely deployed femtocell networks

Deploying femtoceUs underlaying macrocells is a promising way to improve the capacity and enhance the coverage of a cellular system. However, densely deployed femtocells in urban area also give rise to intra-tier interference and cross-tier issue that should be addressed properly in order to acquire the expected performance gain. In this paper, we propose an interference management scheme based on joint clustering and resource allocation for two-tier Orthogonal Frequency Division Multiplexing （OFDM）-based femtoeeU networks. We formulate an optimization task with the objective of maximizing the sum throughput of the femtocell users （FUs） under the consideration of intra-tier interference mitigation, while controlling the interference to the maeroeell user （MU） under its bearable threshold. The formulation problem is addressed by a two-stage procedure： femtoeells clustering and resource allocation. First, disjoint femtocell clusters with dynamic sizes and numbers are generated to minimize intra-tier interference. Then each cluster is taken as a resource allocation unit to share all subehannels, followed by a fast algorithm to distribute power among these subchannels. Simulation results show that our proposed schemes can improve the throughput of the FUs with acceptable complexity.

Thermal instability of a viscoelastic fluid in a fluid-porous system with a plane Poiseuille flow

The thermal convection of a Jeffreys fluid subjected to a plane Poiseuille flow in a fluid-porous system composed of a fluid layer and a porous layer is studied in the paper.A linear stability analysis and a Chebyshevτ-QZ algorithm are employed to solve the thermal mixed convection.Unlike the case in a single layer,the neutral curves of the two-layer system may be bi-modal in the proper depth ratio of the two layers.We find that the longitudinal rolls(LRs)only depend on the depth ratio.With the existence of the shear flow,the effects of the depth ratio,the Reynolds number,the Prandtl number,the stress relaxation,and strain retardation times on the transverse rolls(TRs)are also studied.Additionally,the thermal instability of the viscoelastic fluid is found to be more unstable than that of the Newtonian fluid in a two-layer system.In contrast to the case for Newtonian fluids,the TRs rather than the LRs may be the preferred mode for the viscoelastic fluids in some cases.

Numerical study on the hydrodynamics of agglomerates at intermediate Reynolds numbers

The flow pattern and hydrodynamics of a heterogeneous permeable agglomerate in a uniform upward flow at intermediate Reynolds numbers(1–40)are analyzed from three-dimensional(3 D)computational fluid dynamics simulations.Different from the homogeneous or stepwise-varying permeability models used in previous papers,a continuously radially varying permeability model is used in the present study.The effects of two dimensionless parameters,the Reynolds number and the permeability ratio,on the flow field and the hydrodynamics were investigated in detail.The results reveal that unlike the solid sphere,a small recirculating wake initially forms inside the agglomerate.The critical Reynolds number for the formation of the recirculating wake is lower than that of the solid sphere and it decreases with the increase of permeability ratio.A correlation of drag coefficient as a function of the Reynolds number and permeability ratio is proposed.Comparisons of drag coefficients obtained by different permeability models show that at intermediate Reynolds numbers(1–40),the effect of radially varying permeability on the drag coefficient must be considered.

Mobility-driven user-centric AP clustering in mobile edge computing-based ultra-dense networks

ultra-Dense Network(UDN)has been envisioned as a promising technology to provide high-quality wireless connectivity in dense urban areas,in which the density of Access Points(APs)is increased up to the point where it is comparable with or surpasses the density of active mobile users.In order to mitigate inter-AP interference and improve spectrum efficiency,APs in UDNs are usually clustered into multiple groups to serve different mobile users,respectively.However,as the number of APs increases,the computational capability within an AP group has become the bottleneck of AP clustering.In this paper,we first propose a novel UDN architecture based on Mobile Edge Computing(MEC),in which each MEC server is associated with a user-centric AP cluster to act as a mobile agent.In addition,in the context of MEC-based UDN,we leverage mobility prediction techniques to achieve a dynamic AP clustering scheme,in which the cluster structure can automatically adapt to the dynamic distribution of user traffic in a specific area.Simulation results show that the proposed scheme can highly increase the average user throughput compared with the baseline algorithm using max-SINR user association and equal bandwidth allocation,while it guarantees at the same time low transmission delay.

Manipulation of low-refractive-index particles using customized dark traps

Low-refractive-index particles play significant roles in physics,drug delivery,biomedical science,and other fields.However,they have not attained sufficient utilization in active manipulation due to the repulsive effect of light.In this work,the establishment of customized dark traps is demonstrated to fulfill the demands of versatile manipulation of low-refractive-index particles.The customized dark traps are generated by assembling generalized perfect optical vortices based on the free lens modulation method,by which the beams’shape,intensity,and position can be elaborately designed with size independent of topological charge.Using the customized dark traps with high quality and high efficiency,rotation along arbitrary trajectories with controllable speed,parallel manipulation,and sorting of low-refractive-index particles by size can be realized.With unprecedented flexibility and quality,the customized dark traps provide tremendous potential in optical trapping,lithography,and biomedicine.

Rapid,artifact-reduced,image reconstruction for super-resolution structured illumination microscopy

Super-resolution structured ilumination microscopy(SR-SIM)is finding increasing application in biomedical research due to its superior ability to visualize subcellular dynamics in living cells.However,during image reconstruction artifacts can be introduced and when coupled with time-consuming postprocessing procedures,limits this technique from becoming a routine imaging tool for biologists.To address these issues,an accelerated,artifact-reduced reconstruction algorithm termed joint space frequency reconstruction-based artifact reduction algorithm(JSFR-AR-SIM)was developed by integrating a high-speed reconstruc tion framework with a high-fidelity optimization approach designed to suppress the sidelobe artifact.Consequently,JSFR-AR-SIM produces high-quality,super-resolution images with minimal artifacts,and the reconstruction speed is increased.We anticipate this algorithm to facilitate SR-SIM becoming a routine tool in biomedical laboratories.

Generalized perfect optical vortices with free lens modulation

In this paper,we present an approach called the free lens modulation(FLM)method to generate high-perfection3D generalized perfect optical vortices(GPOVs)with topological charges of 1–80.In addition,2D and 3D GPOVs were produced by altering the parameters of the freely shaped lenses.To verify the quality of the GPOVs produced with the FLM method,we conducted optical trapping experiments and realized linear control of the rotation rate of the trapped particle.Due to the great advantages of high perfection and high power usage in generating arbitrarily shaped GPOVs,the FLM method is expected to be applied in optical manipulation,optical communications,and other fields.

High-speed image reconstruction for optically sectioned,super-resolution structured illumination microscopy

Super-resolution structured illumination microscopy(SR-SIM)is an outstanding method for visualizing the subcellular dynamics in living cells.To date,by using elaborately designed systems and algorithms,SR-SIM can achieve rapid,optically sectioned,SR observation with hundreds to thousands of time points.However,real-time observation is still out of reach for most SIM setups as conventional algorithms for image reconstruction involve a heavy computing burden.To address this limitation,an accelerated reconstruction algorithm was developed by implementing a simplified workflow for SR-SIM,termed joint space and frequency reconstruction.This algorithm results in an 80-fold improvement in reconstruction speed relative to the widely used Wiener-SIM.Critically,the increased processing speed does not come at the expense of spatial resolution or sectioning capability,as demonstrated by live imaging of microtubule dynamics and mitochondrial tubulation.

Tribological Behavior of In Situ TiC/Graphene/Graphite/Ti6Al4V Matrix Composite Through Laser Cladding

The TiC/graphene/graphite/Ti6 Al4 V composite coating was prepared by laser cladding.The microstructure and tribological behavior of the coating were studied.The in situ reaction between graphene and Ti occurred,and feathery TiC was formed.The feathery TiC was homogeneously distributed betweenα’acicular martensites which was refined with the addition of graphene.Some graphene was transformed into allotrope graphite under the laser irradiation.The TiC hard particles and the self-lubrication of graphene/graphite improved the wear resistance of composite coating.The wear rate and friction coefficient of TiC/graphene/graphite/Ti6 Al4 V composite coating decreased with the increase in sliding speed,a mechanical mixing layer(MML)was formed on the wear surface of the composite coating under the frictional heat,which protected the substrate and reduced the contact.Because of the self-lubricating properties of graphene/graphite,interlayer sliding occurred easily,which also effectively reduced friction.The wear rate of TiC/graphene/graphite/Ti6 Al4 V composite coating increased with the increase in load,but the friction coefficient decreased.The plastic deformation of subsurface layer was more serious under high load,and a stable self-lubricating MML with a protective effect was formed between the wear interfaces,which reduced the friction coefficient.With the increase in load,the wear mechanism changed from abrasive and oxidation wear to delamination,fatigue and oxidation wear.

Advances in biomaterials and regenerative medicine for primary ovarian insufficiency therapy

Primary ovarian insufficiency(POI)is an ovarian dysfunction that affects more than 1%of women and is characterized by hormone imbalances that afflict women before the age of 40.The typical perimenopausal symptoms result from abnormal levels of sex hormones,especially estrogen.The most prevalent treatment is hormone replacement therapy(HRT),which can relieve symptoms and improve quality of life.However,HRT cannot restore ovarian functions,including secretion,ovulation,and fertility.Recently,as part of a developing field of regenerative medicine,stem cell therapy has been proposed for the treatment of POI.Thus,we recapitulate the literature focusing on the use of stem cells and biomaterials for POI treatment,and sum up the underlying mechanisms of action.A thorough understanding of the work already done can aid in the development of guidelines for future translational applications and clinical trials that aim to cure POI by using regenerative medicine and biomedical engineering strategies.

On-chip short-wave infrared multispectral detector based on integrated Fabry–Perot microcavities array

We demonstrate an ultra-compact short-wave infrared[SWIR]multispectral detector chip by monolithically integrating the narrowband Fabry–Perot microcavities array with the In Ga As detector focal plane array.A 16-channel SWIR multispectral detector has been fabricated for demonstration.Sixteen different narrowband response spectra are acquired on a 64×64 pixels detector chip by four times combinatorial etching processes.The peak of the response spectra varies from1450 to 1666 nm with full width at half-maximum of 24 nm on average.The size of the SWIR multispectral detection system is remarkably reduced to a 2 mm^(2) detector chip.

Coupled Tamm plasmon polaritons induced narrow bandpass filter with ultra-wide stopband

Narrow bandpass filters(NBPFs)play important roles in optics,such as quantum communication,spectrometer,and wavelength division multiplexing.However,the stopband and restraint ability of traditional NBPFs is limited.In this article,a coupled Tamm plasmon polaritons(TPPs)induced transmission theory has been proposed to design high-efficiency NBPFs with ultra-wide deep stopbands.An NBPF at 1.55 μm has been experimentally demonstrated with full width at half maximum(FWHM)of 10 nm and stopband ranging from 0.2 to 25 μm which is 62 times wider than that of traditional ones.Furthermore,the restraint depth of the stopband reaches 0.03%,which is only 1/20 of a traditional filter with the same FWHM.Its advantage in restraining ambient light over traditional ones has also been demonstrated with an InGaAs infrared detector.It provides a very powerful way to capture specific narrowband optical signals from ultra-wide strong ambient light,especially useful for daytime quantum communications.

A trifunctional contraceptive gel enhances the safety and quality of sexual intercourse

Current contraceptive methods come with a number of drawbacks,including low efficacy,in the case of commercial contraceptive gels,and a reduction in the quality of sexual intercourse,in the case of condoms.Adding pharmacologically-active agents to contraceptive gels holds the potential to improve sexual experience,and hardbor safety and hygiene.In this study,we fabricated a carbomer-based contraceptive gel consisting of three agents:tenofovir,gossypol acetate,and nitroglycerin(TGN),with pH adjusted to 4.5(to be compatible with the vagina).In vitro,the gossypol component of the contraceptive gel proved to be an effective spermicide.When the concentration of gossypol acetate was 10 mg/ml,the spermicidal ability reached 100%after 30 s.In addition,tenofovir in the gel significantly inhibited lentiviral transfection efficiency in cell-containing media.In 6 pairs of rats,the gel successfully prevented all females from conceiving after successful mating.Moreover,increased sexual frequency and enhanced erection,which were promoted by the nitroglycerin in the components,were observed in male rats that had the gel applied to their penises.This novel TGN contraceptive gel yielded a higher contraceptive success rate than that of the commercial contraceptive gel(Contragel®).In addition,it has the added benefits to prevent sexually transmitted diseases and improve male libido and erectile function during sexual intercourse.Combining three FDA-approved and marketed agents together,our trifunctional TGN gel has a great potential for further translation and commercialization.