Heat and Mass Transfers in a Two-Phase Stratified Turbulent Fluid Flow in a Geothermal Pipe with Chemical Reaction

This research focused on the study of heat and mass transfers in a two-phase stratified turbulent fluid flow in a geothermal pipe with chemical reaction. The derived non-linear partial differential equations governing the flow were solved using the Finite Difference Method. The effects of various physical parameters on the concentration, skin friction, heat, and mass transfers have been determined. Analysis of the results obtained indicated that the coefficient of skin friction decreased with an increase in Reynolds number and solutal Grasholf number, the rate of heat transfer increased with an increase in Eckert number, Prandtl number, and angle of inclination, and the rate of mass transfer increased with increase in Reynolds number, Chemical reaction parameter and angle of inclination. The findings would be useful to engineers in designing and maintaining geothermal pipelines more effectively.

Generation of mitochondrial replacement monkeys by female pronucleus transfer

Mutations in mitochondrial DNA(mtDNA)are maternally inherited and have the potential to cause severe disorders.Mitochondrial replacement therapies,including spindle,polar body,and pronuclear transfers,are promising strategies for preventing the hereditary transmission of mtDNA diseases.While pronuclear transfer has been used to generate mitochondrial replacement mouse models and human embryos,its application in non-human primates has not been previously reported.In this study,we successfully generated four healthy cynomolgus monkeys(Macaca fascicularis)via female pronuclear transfer.These individuals all survived for more than two years and exhibited minimal mtDNA carryover(3.8%–6.7%),as well as relatively stable mtDNA heteroplasmy dynamics during development.The successful establishment of this nonhuman primate model highlights the considerable potential of pronuclear transfer in reducing the risk of inherited mtDNA diseases and provides a valuable preclinical research model for advancing mitochondrial replacement therapies in humans.

Coherent optical frequency transfer via 972-km fiber link

We demonstrate coherent optical frequency dissemination over a distance of 972 km by cascading two spans where the phase noise is passively compensated for.Instead of employing a phase discriminator and a phase locking loop in the conventional active phase control scheme,the passive phase noise cancellation is realized by feeding double-trip beat-note frequency to the driver of the acoustic optical modulator at the local site.This passive scheme exhibits fine robustness and reliability,making it suitable for long-distance and noisy fiber links.An optical regeneration station is used in the link for signal amplification and cascaded transmission.The phase noise cancellation and transfer instability of the 972-km link is investigated,and transfer instability of 1.1×10^(-19)at 10^(4)s is achieved.This work provides a promising method for realizing optical frequency distribution over thousands of kilometers by using fiber links.

High-fidelity topological quantum state transfers in a cavity-magnon system

We propose a scheme for realizing high-fidelity topological state transfer via the topological edge states in a onedimensional cavity-magnon system.It is found that the cavity-magnon system can be mapped analytically into the generalized Su-Schrieffer-Heeger model with tunable cavity-magnon coupling.It is shown that the edge state can be served as a quantum channel to realize the photonic and magnonic state transfers by adjusting the coupling strength between adjacent cavity modes.Further,our scheme can realize the quantum state transfer between photonic state and magnonic state by changing the cavity-magnon coupling strength.With the numerical simulation,we quantitatively show that the photonic,magnonic and magnon-to-photon state transfers can be achieved with high fidelity in the cavity-magnon system.Spectacularly,three different types of quantum state transfer schemes can be even transformed into each other in a controllable fashion.The Su-Schrieffer-Heeger model based on the cavity-magnon system provides us a tunable platform to engineer the transport of photon and magnon,which may have potential applications in topological quantum processing.

A Review of the Eco-Environmental Impacts of the South-to-North Water Diversion:Implications for Interbasin Water Transfers

Interbasin water-transfer schemes provide an engineering solution for reconciling the conflict between water demand and availability.In the context of climate change,which brings great uncertainties to water resource distribution,interbasin water transfer plays an increasingly important role in the global water–food–energy nexus.However,the transfer of water resources simultaneously changes the hydrological regime and the characteristics of local water bodies,affecting biotic communities accordingly.Compared with high economic and technical inputs water-transfer projects require,the environmental and ecological implications of water-transfer schemes have been inadequately addressed.This work selects the largest water-transfer project in China,the South-to-North Water Diversion(SNWD)Project,to critically review its eco-environmental impacts on donor and recipient basins,as well as on regions along the diversion route.The two operated routes of the SNWD Project represent two typical water diversion approaches:The Middle Route uses an excavated canal,while the East Route connects existent river channels.An overview of the eco-environmental implications of these two routes is valuable for the design and optimization of future water-transfer megaprojects.

Label Recovery and Trajectory Designable Network for Transfer Fault Diagnosis of Machines With Incorrect Annotation

The success of deep transfer learning in fault diagnosis is attributed to the collection of high-quality labeled data from the source domain.However,in engineering scenarios,achieving such high-quality label annotation is difficult and expensive.The incorrect label annotation produces two negative effects:1)the complex decision boundary of diagnosis models lowers the generalization performance on the target domain,and2)the distribution of target domain samples becomes misaligned with the false-labeled samples.To overcome these negative effects,this article proposes a solution called the label recovery and trajectory designable network(LRTDN).LRTDN consists of three parts.First,a residual network with dual classifiers is to learn features from cross-domain samples.Second,an annotation check module is constructed to generate a label anomaly indicator that could modify the abnormal labels of false-labeled samples in the source domain.With the training of relabeled samples,the complexity of diagnosis model is reduced via semi-supervised learning.Third,the adaptation trajectories are designed for sample distributions across domains.This ensures that the target domain samples are only adapted with the pure-labeled samples.The LRTDN is verified by two case studies,in which the diagnosis knowledge of bearings is transferred across different working conditions as well as different yet related machines.The results show that LRTDN offers a high diagnosis accuracy even in the presence of incorrect annotation.

The regulation of ferrocene-based catalysts on heat transfer in highpressure combustion of ammonium perchlorate/hydroxyl-terminated polybutadiene/aluminum composite propellants

The regulation of the burning rate pressure exponent for the ammonium perchlorate/hydroxylterminated polybutadiene/aluminum(AP/HTPB/Al)composite propellants under high pressures is a crucial step for its application in high-pressure solid rocket motors.In this work,the combustion characteristics of AP/HTPB/Al composite propellants containing ferrocene-based catalysts were investigated,including the burning rate,thermal behavior,the local heat transfer,and temperature profile in the range of 7-28 MPa.The results showed that the exponent breaks were still observed in the propellants after the addition of positive catalysts(Ce-Fc-MOF),the burning rate inhibitor((Ferrocenylmethyl)trimethylammonium bromide,Fc Br)and the mixture of Fc Br/catocene(GFP).However,the characteristic pressure has increased,and the exponent decreased from 1.14 to 0.66,0.55,and 0.48 when the addition of Ce-FcMOF,Fc Br and Fc Br/GFP in the propellants.In addition,the temperature in the first decomposition stage was increased by 7.50℃ and 11.40℃ for the AP/Fc Br mixture and the AP/Fc Br/GFP mixture,respectively,compared to the pure AP.On the other hand,the temperature in the second decomposition stage decreased by 48.30℃ and 81.70℃ for AP/Fc Br and AP/Fc Br/GFP mixtures,respectively.It was also found that Fc Br might generate ammonia to cover the AP surface.In this case,a reaction between the methyl in Fc Br and perchloric acid caused more ammonia to appear at the AP surface,resulting in the suppression of ammonia desorption.In addition,the coarse AP particles on the quenched surface were of a concave shape relative to the binder matrix under low and high pressures when the catalysts were added.In the process,the decline at the AP/HTPB interface was only exhibited in the propellant with the addition of Ce-Fc-MOF.The ratio of the gas-phase temperature gradient of the propellants containing catalysts was reduced significantly below and above the characteristic pressure,rather than 3.6 times of the difference in the blank propellant.Overall,the obtained results demonstrated that the pressure exponent could be effectively regulated and controlled by adjusting the propellant local heat and mass transfer under high and low pressures.

Transforming Molecules into Medicines: Role of CDMOS in Phase-Appropriate Technology Transfers in Advancing Pharmaceutical Innovation

CDMOs are emerging as critical drivers of innovation within the pharmaceutical and biotech industries. As the pharmaceutical industry continues to evolve, we can expect to see CDMOs play an increasingly important role in drug development and manufacturing. Many companies within these sectors are now leveraging the expertise of CDMOs through technology transfers to foster innovation and enhance the development of new drug products. In the extensive field of drug development, technology transfer plays a crucial role at multiple stages, ranging from preclinical phases to commercialization. By working closely with drug developers, CDMOs can ensure that technologies are transferred seamlessly between phases of drug development, allowing for a more efficient and cost-effective development process. CDMOs also bring a wealth of experience in various areas of drug development, including process development, analytical testing, quality control, and manufacturing. This expertise, combined with a focus on innovation, can help drug developers to overcome technical challenges and optimize their drug development programs. CDMOs can provide drug developers with various manufacturing capabilities, from small-scale clinical trials to large-scale commercial production. This flexibility allows drug developers to focus on their core competencies while relying on CDMOs to provide the necessary infrastructure and support for drug manufacturing. The critical role of CDMOs in advancing pharmaceutical innovation in phase-appropriate technology transfer where there will be a lot of effort and patience with strong technical expertise is required. This article explores the various types of Technology transfer from preclinical to commercial stages and successful strategies to foster innovation.

Embryo Transfer Strategies for Women with Recurrent Implantation Failure During the Frozen-thawed Embryo Transfer Cycles:Sequential Embryo Transfer or Double-blastocyst Transfer?

Objective Both sequential embryo transfer(SeET)and double-blastocyst transfer(DBT)can serve as embryo transfer strategies for women with recurrent implantation failure(RIF).This study aims to compare the effects of SeET and DBT on pregnancy outcomes.Methods Totally,261 frozen-thawed embryo transfer cycles of 243 RIF women were included in this multicenter retrospective analysis.According to different embryo quality and transfer strategies,they were divided into four groups:group A,good-quality SeET(GQ-SeET,n=38 cycles);group B,poor-quality or mixed-quality SeET(PQ/MQ-SeET,n=31 cycles);group C,good-quality DBT(GQ-DBT,n=121 cycles);and group D,poor-quality or mixed-quality DBT(PQ/MQ-DBT,n=71 cycles).The main outcome,clinical pregnancy rate,was compared,and the generalized estimating equation(GEE)model was used to correct potential confounders that might impact pregnancy outcomes.Results GQ-DBT achieved a significantly higher clinical pregnancy rate(aOR 2.588,95%CI 1.267–5.284,P=0.009)and live birth rate(aOR 3.082,95%CI 1.482–6.412,P=0.003)than PQ/MQ-DBT.Similarly,the clinical pregnancy rate was significantly higher in GQ-SeET than in PQ/MQ-SeET(aOR 4.047,95%CI 1.218–13.450,P=0.023).The pregnancy outcomes of GQ-SeET were not significantly different from those of GQ-DBT,and the same results were found between PQ/MQ-SeET and PQ/MQ-DBT.Conclusion SeET relative to DBT did not seem to improve pregnancy outcomes for RIF patients if the embryo quality was comparable between the two groups.Better clinical pregnancy outcomes could be obtained by transferring good-quality embryos,no matter whether in SeET or DBT.Embryo quality plays a more important role in pregnancy outcomes for RIF patients.

Selective and Adaptive Incremental Transfer Learning with Multiple Datasets for Machine Fault Diagnosis

The visions of Industry 4.0 and 5.0 have reinforced the industrial environment.They have also made artificial intelligence incorporated as a major facilitator.Diagnosing machine faults has become a solid foundation for automatically recognizing machine failure,and thus timely maintenance can ensure safe operations.Transfer learning is a promising solution that can enhance the machine fault diagnosis model by borrowing pre-trained knowledge from the source model and applying it to the target model,which typically involves two datasets.In response to the availability of multiple datasets,this paper proposes using selective and adaptive incremental transfer learning(SA-ITL),which fuses three algorithms,namely,the hybrid selective algorithm,the transferability enhancement algorithm,and the incremental transfer learning algorithm.It is a selective algorithm that enables selecting and ordering appropriate datasets for transfer learning and selecting useful knowledge to avoid negative transfer.The algorithm also adaptively adjusts the portion of training data to balance the learning rate and training time.The proposed algorithm is evaluated and analyzed using ten benchmark datasets.Compared with other algorithms from existing works,SA-ITL improves the accuracy of all datasets.Ablation studies present the accuracy enhancements of the SA-ITL,including the hybrid selective algorithm(1.22%-3.82%),transferability enhancement algorithm(1.91%-4.15%),and incremental transfer learning algorithm(0.605%-2.68%).These also show the benefits of enhancing the target model with heterogeneous image datasets that widen the range of domain selection between source and target domains.

Performance Analysis and Optimization of Energy Harvesting Modulation for Multi-User Integrated Data and Energy Transfer

Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)performance.The joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless channel.With the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)performance.Simulation results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.

Numerical Investigation of Heat and Mass Transfer in Nanofluid-Filled Porous Medium

In this work, we numerically study the laminar mixed convection of fluid flow in a vertical channel filled with porous media during the drying process. The porous medium, modeled as a vertical wall, consists of solid and nanofluid phase (Water-Al2O3 or Water-Cu), as well as a gas phase. The established model is developed based on Whitaker’s theory and resolved by our numerical code using Fortran. Results principally show the influence of various physical parameters, such as nanoparticle volume fraction, ambient temperature, and saturation on heat and mass transfer on the drying process. This study brings the effect of the presence of nanofluids in porous media. It contributes not only to our fundamental understanding of drying processes but also provides practical insights that can guide the development of more efficient and sustainable drying technologies. .

Fully polarized Compton scattering in plane waves and its polarization transfer

Fully polarized Compton scattering from a beam of spin-polarized electrons is investigated in plane-wave backgrounds in a broad intensity region from the perturbative to the nonperturbative regimes.In the perturbative regime,polarized linear Compton scattering is considered for investigating polarization transfer from a single laser photon to a scattered photon,and in the high-intensity region,the polarized locally monochromatic approximation and locally constant field approximation are established and are employed to study polarization transfer from an incoming electron to a scattered photon.The numerical results suggest an appreciable improvement of about 10%in the scattering probability in the intermediate-intensity region if the electron’s longitudinal spin is parallel to the laser rotation.The longitudinal spin of the incoming electron can be transferred to the scattered photon with an efficiency that increases with laser intensity and collisional energy.For collision between an optical laser with frequency1 eV and a 10 GeV electron,this polarization transfer efficiency can increase from about 20%in the perturbative regime to about 50%in the nonperturbative regime for scattered photons with relatively high energy.

Heat and Mass Transfer on Non-Newtonian Peristaltic Flow in a Channel in Presence of Magnetic Field: Analytical and Numerical Analysis

A study has been arranged to investigate the flow of non-Newtonian fluid in a vertical asymmetrical channel using peristalsis. The porous medium allows the electrically conductive fluid to flow in the channel, while a uniform magnetic field is applied perpendicular to the flow direction. The analysis takes into account the combined influence of heat and mass transfer, including the effects of Soret and Dufour. The flow’s non-Newtonian behavior is characterized using a Casson rheological model. The fluid flow equations are examined within a wave frame of reference that has a wave velocity. The analytic solution is examined using long wavelengths and a small Reynolds number assumption. The stream function, temperature, concentration and heat transfer coefficient expressions are derived. The bvp4c function from MATLAB has been used to numerically solve the transformed equations. The flow characteristics have been analyzed using graphs to demonstrate the impacts of different parameters.

Efficient energy transfer from self-trapped excitons to Mn^(2+) dopants in CsCdCl_(3):Mn^(2+) perovskite nanocrystals

Mn^(2+)doping has been adopted as an efficient approach to regulating the luminescence properties of halide perovskite nano-crystals(NCs).However,it is still difficult to understand the interplay of Mn^(2+)luminescence and the matrix self-trapped exciton(STE)emission therein.In this study,Mn^(2+)-doped CsCdCl_(3) NCs are prepared by hot injection,in which CsCdCl_(3) is selected because of its unique crystal structure suitable for STE emission.The blue emission at 441 nm of undoped CsCdCl_(3) NCs originates from the defect states in the NCs.Mn^(2+)doping promotes lattice distortion of CsCdCl_(3) and generates bright orange-red light emission at 656 nm.The en-ergy transfer from the STEs of CsCdCl_(3) to the excited levels of the Mn^(2+)ion is confirmed to be a significant factor in achieving efficient luminescence in CsCdCl_(3):Mn^(2+)NCs.This work highlights the crucial role of energy transfer from STEs to Mn^(2+)dopants in Mn^(2+)-doped halide NCs and lays the groundwork for modifying the luminescence of other metal halide perovskite NCs.

P-induced electron transfer interaction for enhanced selective hydrogenation rearrangement of furfural to cyclopentanone

Optimizing the intrinsic activity of non-noble metal by precisely tailoring electronic structure offers an appealing way to construct cost-effective catalysts for selective biomass valorization.Herein,we reported a P-doping bifunctional catalyst(Ni-P/mSiO_(2))that achieved 96.6%yield for the hydrogenation rearrangement of furfural to cyclopentanone at mild conditions(1 MPaH_(2),150°C).The turnover frequency of Ni-P/mSiO_(2)was 411.9 h^(-1),which was 3.2-fold than that of Ni/mSiO_(2)(127.2 h^(-1)).Detailed characterizations and differential charge density calculations revealed that the electron-deficient Niδ+species were generated by the electron transfer from Ni to P,which promoted the ring rearrangement reaction.Density functional theory calculations illustrated that the presence of P atoms endowed furfural tilted adsorb on the Ni surface by the C=O group and facilitated the desorption of cyclopentanone.This work unraveled the connection between the localized electronic structures and the catalytic properties,so as to provide a promising reference for designing advanced catalysts for biomass valorization.

Effect of surfactant frequently used in soil flushing on oxygen mass transfer in micro-nano-bubble aeration system

In-site soil flushing and aeration are the typical synergetic remediation technology for contaminated sites.The surfactant present in flushing solutions is bound to affect the aeration efficiency.The purpose of this study is to evaluate the effect of surfactant frequently used in soil flushing on the oxygen mass transfer in micro-nano-bubble(MNB)aeration system.Firstly,bio-surfactants and chemical surfactants were used to investigate their effects on Sauter mean diameter of bubble(dBS),gas holdup(ε),volumetric mass-transfer coefficient(kLa)and liquid-side mass-transfer coefficient(kL)in the MNB aeration system.Then,based upon the experimental results,the Sardeing's and Frossling's models were modified to describe the effect of surfactant on kL in the MNB aeration.The results showed that,for the twenty aqueous surfactant solutions,with the increase in surfactant concentration,the value of dBS,kLa and kL decreased,while the value ofεand gas-liquid interfacial area(a)increased.These phenomena were mainly attributed to the synergistic effects of immobile bubble surface and the suppression of coalescence in the surfactant solutions.In addition,with the presence of electric charge,MNBs in anionic surfactant solutions were smaller and higher in number than in non-ionic surfactant solutions.Furthermore,the accumulation of surfactant on the gas-liquid interface was more conspicuous for small MNB,so the reduction of kL in anionic surfactant solutions was larger than that in non-ionic surfactant solutions.Besides,the modified Frossling's model predicted the effect of surfactant on kL in MNB aeration system with reasonable accuracy.

Robust Information Hiding Based on Neural Style Transfer with Artificial Intelligence

This paper proposes an artificial intelligence-based robust information hiding algorithm to address the issue of confidential information being susceptible to noise attacks during transmission.The algorithm we designed aims to mitigate the impact of various noise attacks on the integrity of secret information during transmission.The method we propose involves encoding secret images into stylized encrypted images and applies adversarial transfer to both the style and content features of the original and embedded data.This process effectively enhances the concealment and imperceptibility of confidential information,thereby improving the security of such information during transmission and reducing security risks.Furthermore,we have designed a specialized attack layer to simulate real-world attacks and common noise scenarios encountered in practical environments.Through adversarial training,the algorithm is strengthened to enhance its resilience against attacks and overall robustness,ensuring better protection against potential threats.Experimental results demonstrate that our proposed algorithm successfully enhances the concealment and unknowability of secret information while maintaining embedding capacity.Additionally,it ensures the quality and fidelity of the stego image.The method we propose not only improves the security and robustness of information hiding technology but also holds practical application value in protecting sensitive data and ensuring the invisibility of confidential information.

Robust free-space optical frequency transfer in time-varying link distances conditions

Future inter-satellite clock comparison on high orbit will require optical time and frequency transmission technology between moving objects.Here,we demonstrate robust optical frequency transmission under the condition of variable link distance.This variable link is accomplished by the relative motion of a single telescope fixed on the experimental platform to a corner-cube reflector(CCR)installed on a sliding guide.Two acousto–optic modulators with different frequencies are used to separate forward signal from backward signal.With active phase noise suppression,when the CCR moves back and forth at a constant velocity of 20 cm/s and an acceleration of 20 cm/s^(2),we achieve the best frequency stability of 1.9×10^(-16) at 1 s and 7.9×10^(-19) at 1000 s indoors.This work paves the way for future studying optical frequency transfer between ultra-high-orbit satellites.

Numerical study of directional heat transfer in composite materials via controllable carbon fiber distribution

Carbon fiber reinforced polyamide 12(CF/PA12),a new material renowned for its excellent mechanical and thermal properties,has drawn significant industry attention.Using the steady-state research to heat transfer,a series of simulations to investigate the heat transfer properties of CF/PA12 were conducted in this study.Firstly,by building two-and three-dimensional models,the effects of the porosity,carbon fiber content,and arrangement on the heat transfer of CF/PA12 were examined.A validation of the simulation model was carried out and the findings were consistent with those of the experiment.Then,the simulation results using the above models showed that within the volume fraction from 0% to 28%,the thermal conductivity of CF/PA12 increased greatly from 0.0242 W/(m·K)to 10.8848 W/(m·K).The increasing porosity had little influence on heat transfer characteristic of CF/PA12.The direction of the carbon fiber arrangement affects the heat transfer impact,and optimal outcomes were achieved when the heat flow direction was parallel to the carbon fiber.This research contributes to improving the production methods and broadening the application scenarios of composite materials.