高等教育数字化转型的推进逻辑、问题透视与实践进路

高等教育数字化转型是推动高等教育高质量发展的关键举措,也是我国实现从高等教育大国向高等教育强国系统性跃迁的必然选择。然而实践表明,由于高等教育场景的复杂性和数字技术的不确定性,导致数字技术融入高等教育变革时,存在技术基础视域下智能服务一体化效能低、价值创造视域下“人机融合”力度不足、制度体系视域下文化机制不健全等诸多问题。围绕不同视域出现的转型问题,应在遵循高等教育规律和人才发展规律的基础上,回溯分析转型的价值意蕴,强化以技术为物质实现基础、以行动为价值创造过程、以制度为文化体系的复合式推进逻辑。进而根据该逻辑框架,针对性地提出深入推进高等教育数字化转型的实践进路:注重技术赋能,全方位优化升级智能化基础设施;强化场景驱动,全过程推动数字技术与高等教育各要素深度融合;优化制度规范,全维度构建高等教育数字化转型的文化生成机制。

沉积策略对电弧增材制造5356铝合金显微组织、缺陷和力学性能的影响

基于电弧增材制造技术(WAAM)研究往复扫描(RS)、振荡扫描(OS)和垂直扫描(VS)3种沉积策略对5356铝合金(AA5356)构件的影响,探讨5356铝合金构件的显微组织、缺陷和力学性能。结果表明:相比于RS和OS策略,VS策略使得构件的热量分布均匀。VS策略的显微组织主要由等轴晶组成,使得显微硬度最高值达到HV 77.25。VS策略使得构件的气孔率和微孔尺寸分别下降了45.52%和19.81%,从而改善了拉伸性能。因此,VS策略为获得显微组织均匀、力学性能优异的AA5356构件提供了一种新的解决方案。

Efficient stochastic parallel gradient descent training for on-chip optical processor

In recent years,space-division multiplexing(SDM)technology,which involves transmitting data information on multiple parallel channels for efficient capacity scaling,has been widely used in fiber and free-space optical communication sys-tems.To enable flexible data management and cope with the mixing between different channels,the integrated reconfig-urable optical processor is used for optical switching and mitigating the channel crosstalk.However,efficient online train-ing becomes intricate and challenging,particularly when dealing with a significant number of channels.Here we use the stochastic parallel gradient descent(SPGD)algorithm to configure the integrated optical processor,which has less com-putation than the traditional gradient descent(GD)algorithm.We design and fabricate a 6×6 on-chip optical processor on silicon platform to implement optical switching and descrambling assisted by the online training with the SPDG algorithm.Moreover,we apply the on-chip processor configured by the SPGD algorithm to optical communications for optical switching and efficiently mitigating the channel crosstalk in SDM systems.In comparison with the traditional GD al-gorithm,it is found that the SPGD algorithm features better performance especially when the scale of matrix is large,which means it has the potential to optimize large-scale optical matrix computation acceleration chips.

Corrosion and in vitro cytocompatibility investigation on the designed Mg-Zn-Ag metallic glasses for biomedical application

In the present work,seven Mg-Zn-Ag alloys with the nominal composition of Mg_(96-x)Zn_(x)Ag_(4)(x=17,20,23,26,29,32,35 in at.%)were prepared by induction melting and single-roller melt-spinning.The X-ray diffraction(XRD)analyses indicate the metallic glasses with three composition of Mg_(73)Zn_(23)Ag_(4),Mg_(70)Zn_(26)Ag_(4),and Mg_(67)Zn_(29)Ag_(4)were obtained successfully.The differential scanning calorimetry(DSC)measurement was used to obtain the characteristic temperature of Mg-Zn-Ag metallic glasses for the glass-forming ability analysis.The maximum glass transition temperature(Trg)was found to be 0.525 with a composition close to Mg_(67)Zn_(29)Ag_(4),which results in the best glass-forming ability.Moreover,the immersion test in simulated body fluid(SBF)demonstrate the relative homogeneous corrosion behavior of the Mg-Zn-Ag metallic glasses.The corrosion rate of Mg-Zn-Ag metallic glasses in SBF solution decreases with the increase of Zn content.The sample Mg_(67)Zn_(29)Ag_(4)has the lowest corrosion rate of 0.19mm/yr,which could meet the clinical application requirement well.The in vitro cell experiments show that the Madin-Darby canine kidney(MDCK)cells cultured in sample Mg_(67)Zn_(29)Ag_(4)and its extraction medium have higher activity.However,the Mg-Zn-Ag metallic glasses exhibit obvious inhibitory effect on human rhabdomyosarcoma(RD)tumor cells.The present investigations on the glass-forming ability,corrosion behavior,cytocompatibility and tumor inhibition function of the Mg-Zn-Ag based metallic glass could reveal their biomedical application possibility.

Enhancing layered perovskite ferrites with ultra-high-density nanoparticles via cobalt doping for ceramic fuel cell anode

Nanoparticles anchored on the perovskite surface have gained considerable attention for their wide-ranging applications in heterogeneous catalysis and energy conversion due to their robust and integrated structural configuration.Herein,we employ controlled Co doping to effectively enhance the nanoparticle exsolution process in layered perovskite ferrites materials.CoFe alloy nanoparticles with ultra-high-density are exsolved on the(PrBa)_(0.95)(Fe_(0.8)Co_(0.1)Nb_(0.1))2O_(5+δ)(PBFCN_(0.1))surface under reducing atmosphere,providing significant amounts of reaction sites and good durability for hydrocarbon catalysis.Under a reducing atmosphere,cobalt facilitates the reduction of iron cations within PBFCN_(0.1),leading to the formation of CoFe alloy nanoparticles.This formation is accompanied by a cation exchange process,wherein,with the increase in temperature,partial cobalt ions are substituted by iron.Meanwhile,Co doping significantly enhance the electrical conductivity due to the stronger covalency of the Cosingle bondO bond compared with Fesingle bondO bond.A single cell with the configuration of PBFCN_(0.1)-Sm_(0.2)Ce_(0.8)O_(1.9)(SDC)|SDC|Ba_(0.5)Sr_(0.5)Co_(0.8)Fe_(0.2)O_(3−δ)(BSCF)-SDC achieves an extremely low polarization resistance of 0.0163Ωcm^(2)and a high peak power density of 740 mW cm^(−2)at 800℃.The cell also shows stable operation for 120 h in H_(2)with a constant current density of 285 mA cm^(−2).Furthermore,employing wet C_(2)H_(6)as fuel,the cell demonstrates remarkable performance,achieving peak power densities of 455 mW cm^(−2)at 800℃and 320 mW cm^(−2)at 750℃,marking improvements of 36%and 70%over the cell with(PrBa)_(0.95)(Fe_(0.9)Nb_(0.1))_(2)O_(5+δ)(PBFN)-SDC at these respective temperatures.This discovery emphasizes how temperature influences alloy nanoparticles exsolution within doped layered perovskite ferrites materials,paving the way for the development of high-performance ceramic fuel cell anodes.

Recent progress in the applications of presynaptic dopaminergic positron emission tomography imaging in parkinsonism

Nowadays,presynaptic dopaminergic positron emission tomography,which assesses deficiencies in dopamine synthesis,storage,and transport,is widely utilized for early diagnosis and differential diagnosis of parkinsonism.This review provides a comprehensive summary of the latest developments in the application of presynaptic dopaminergic positron emission tomography imaging in disorders that manifest parkinsonism.We conducted a thorough literature search using reputable databases such as PubMed and Web of Science.Selection criteria involved identifying peer-reviewed articles published within the last 5 years,with emphasis on their relevance to clinical applications.The findings from these studies highlight that presynaptic dopaminergic positron emission tomography has demonstrated potential not only in diagnosing and differentiating various Parkinsonian conditions but also in assessing disease severity and predicting prognosis.Moreover,when employed in conjunction with other imaging modalities and advanced analytical methods,presynaptic dopaminergic positron emission tomography has been validated as a reliable in vivo biomarker.This validation extends to screening and exploring potential neuropathological mechanisms associated with dopaminergic depletion.In summary,the insights gained from interpreting these studies are crucial for enhancing the effectiveness of preclinical investigations and clinical trials,ultimately advancing toward the goals of neuroregeneration in parkinsonian disorders.

Insights into genetic diversity and phenotypic variations in domestic geese through comprehensive population and pan-genome analysis

Background Domestic goose breeds are descended from either the Swan goose(Anser cygnoides)or the Greylag goose(Anser anser),exhibiting variations in body size,reproductive performance,egg production,feather color,and other phenotypic traits.Constructing a pan-genome facilitates a thorough identification of genetic variations,thereby deepening our comprehension of the molecular mechanisms underlying genetic diversity and phenotypic variability.Results To comprehensively facilitate population genomic and pan-genomic analyses in geese,we embarked on the task of 659 geese whole genome resequencing data and compiling a database of 155 RNA-seq samples.By constructing the pan-genome for geese,we generated non-reference contigs totaling 612 Mb,unveiling a collection of 2,813 novel genes and pinpointing 15,567 core genes,1,324 softcore genes,2,734 shell genes,and 878 cloud genes in goose genomes.Furthermore,we detected an 81.97 Mb genomic region showing signs of genome selection,encompassing the TGFBR2 gene correlated with variations in body weight among geese.Genome-wide association studies utilizing single nucleotide polymorphisms(SNPs)and presence-absence variation revealed significant genomic associations with various goose meat quality,reproductive,and body composition traits.For instance,a gene encoding the SVEP1 protein was linked to carcass oblique length,and a distinct gene-CDS haplotype of the SVEP1 gene exhibited an association with carcass oblique length.Notably,the pan-genome analysis revealed enrichment of variable genes in the“hair follicle maturation”Gene Ontology term,potentially linked to the selection of feather-related traits in geese.A gene presence-absence variation analysis suggested a reduced frequency of genes associated with“regulation of heart contraction”in domesticated geese compared to their wild counterparts.Our study provided novel insights into gene expression features and functions by integrating gene expression patterns across multiple organs and tissues in geese and analyzing population variation.Conclusion This accomplishment originates from the discernment of a multitude of selection signals and candidate genes associated with a wide array of traits,thereby markedly enhancing our understanding of the processes underlying domestication and breeding in geese.Moreover,assembling the pan-genome for geese has yielded a comprehensive apprehension of the goose genome,establishing it as an indispensable asset poised to offer innovative viewpoints and make substantial contributions to future geese breeding initiatives.

Multi-surrogate framework with an adaptive selection mechanism for production optimization

Data-driven surrogate models that assist with efficient evolutionary algorithms to find the optimal development scheme have been widely used to solve reservoir production optimization problems.However,existing research suggests that the effectiveness of a surrogate model can vary depending on the complexity of the design problem.A surrogate model that has demonstrated success in one scenario may not perform as well in others.In the absence of prior knowledge,finding a promising surrogate model that performs well for an unknown reservoir is challenging.Moreover,the optimization process often relies on a single evolutionary algorithm,which can yield varying results across different cases.To address these limitations,this paper introduces a novel approach called the multi-surrogate framework with an adaptive selection mechanism(MSFASM)to tackle production optimization problems.MSFASM consists of two stages.In the first stage,a reduced-dimensional broad learning system(BLS)is used to adaptively select the evolutionary algorithm with the best performance during the current optimization period.In the second stage,the multi-objective algorithm,non-dominated sorting genetic algorithm II(NSGA-II),is used as an optimizer to find a set of Pareto solutions with good performance on multiple surrogate models.A novel optimal point criterion is utilized in this stage to select the Pareto solutions,thereby obtaining the desired development schemes without increasing the computational load of the numerical simulator.The two stages are combined using sequential transfer learning.From the two most important perspectives of an evolutionary algorithm and a surrogate model,the proposed method improves adaptability to optimization problems of various reservoir types.To verify the effectiveness of the proposed method,four 100-dimensional benchmark functions and two reservoir models are tested,and the results are compared with those obtained by six other surrogate-model-based methods.The results demonstrate that our approach can obtain the maximum net present value(NPV)of the target production optimization problems.

Natural forests exhibit higher organic carbon concentrations and recalcitrant carbon proportions in soil than plantations:a global data synthesis

Different chemical compositions of soil organic carbon(SOC)affect its persistence and whether it signifi-cantly differs between natural forests and plantations remains unclear.By synthesizing 234 observations of SOC chemical compositions,we evaluated global patterns of concentra-tion,individual chemical composition(alkyl C,O-alkyl C,aromatic C,and carbonyl C),and their distribution even-ness.Our results indicate a notably higher SOC,a markedly larger proportion of recalcitrant alkyl C,and lower easily decomposed carbonyl C proportion in natural forests.How-ever,SOC chemical compositions were appreciably more evenly distributed in plantations.Based on the assumed con-ceptual index of SOC chemical composition evenness,we deduced that,compared to natural forests,plantations may have higher possible resistance to SOC decomposition under disturbances.In tropical regions,SOC levels,recalcitrant SOC chemical composition,and their distributed evenness were significantly higher in natural forests,indicating that SOC has higher chemical stability and possible resistance to decomposition.Climate factors had minor effects on alkyl C in forests globally,while they notably affected SOC chemi-cal composition in tropical forests.This could contribute to the differences in chemical compositions and their distrib-uted evenness between plantations and natural stands.

Exploring pore-scale production characteristics of oil shale after CO_(2) huff‘n’puff in fractured shale with varied permeability

Recent studies have indicated that the injection of carbon dioxide(CO_(2))can lead to increased oil recovery in fractured shale reservoirs following natural depletion.Despite advancements in understanding mass exchange processes in subsurface formations,there remains a knowledge gap concerning the disparities in these processes between the matrix and fractures at the pore scale in formations with varying permeability.This study aims to experimentally investigate the CO_(2) diffusion behaviors and in situ oil recovery through a CO_(2) huff‘n’puff process in the Jimsar shale oil reservoir.To achieve this,we designed three matrix-fracture models with different permeabilities(0.074 mD,0.170 mD,and 0.466 mD)and experimented at 30 MPa and 91℃.The oil concentration in both the matrix and fracture was monitored using a low-field nuclear magnetic resonance(LF-NMR)technique to quantify in situ oil recovery and elucidate mass-exchange behaviors.The results showed that after three cycles of CO_(2) huff‘n’puff,the total recovery degree increased from 30.28%to 34.95%as the matrix permeability of the core samples increased from 0.074 to 0.466 mD,indicating a positive correlation between CO_(2) extraction efficiency and matrix permeability.Under similar fracture conditions,the increase in matrix permeability further promoted CO_(2) extraction efficiency during CO_(2) huff‘n’puff.Specifically,the increase in matrix permeability of the core had the greatest effect on the extraction of the first-cycle injection in large pores,which increased from 16.42%to 36.64%.The findings from our research provide valuable insights into the CO_(2) huff‘n’puff effects in different pore sizes following fracturing under varying permeability conditions,shedding light on the mechanisms of CO_(2)-enhanced oil recovery in fractured shale oil reservoirs.

Concerns arise: wheat allergy risk in pre-packaged food products from China

Understanding and monitoring the cross-contamination of food allergens is crucial for safeguarding public health and ensuring food safety.Food allergen risk assessment,derived from classical toxicological principles,can identify and quantify the risk of allergies.This study aimed to investigate the risk of wheat allergic reactions to prepackaged foods from China through the utilization of food allergen risk assessment.A total of 575 products have been surveyed,wheat/gluten,milk and egg were major allergens labelled on products.According to voluntary incidental trace allergen labelling 3.0(VITAL®3.0)program,the number of products belonged to Action Level 2 were 303.Integration of precautionary allergen labeling(PAL)analysis indicated that 9.57%products would pose a potential risk to wheat allergic individuals.The probabilistic risk assessment results suggest that 7984 allergic reactions may arise among wheat-allergic consumers during 10000 eating occasions due to the consumption of pre-packaged food products with incorrect wheat-related allergen labelling.This study demonstrated that a risk assessment-based approach can support the guidance of allergen labelling and management of food allergen for pre-packaged food products,providing protection for allergic individuals in food consumption and for food manufacturers in food production and trade.

Strong evidence for latitudinal diversity gradient in mosses across the world

Species richness generally decreases with increasing latitude,a biodiversity gradient that has long been considered as one of the few laws in ecology.This latitudinal diversity gradient has been observed in many major groups of organisms.In plants,the latitudinal diversity gradient has been observed in vascular plants,angiosperms,ferns,and liverworts.However,a conspicuous latitudinal diversity gradient in mosses at a global or continental scale has not been observed until now.Here,we analyze a comprehensive data set including moss species in each band of 20° in latitude worldwide.Our results show that moss species richness decreases strongly with increasing latitude,regardless of whether the globe is considered as a whole or different longitudinal segments(e.g.,Old World versus New World) are considered separately.This result holds when variation in area size among latitudinal bands is taken into account.Pearson's correlation coefficient between latitude and species richness is-0.99 for both the Northern and Southern Hemispheres.Because bryophytes are an extant lineage of early land plants and because mosses not only include most of extant species of bryophytes but also are important constituents of most terrestrial ecosystems,understanding geographic patterns of mosses is particularly important The finding of our study fills a critical knowledge gap.

Advances in neuromorphic computing:Expanding horizons for AI development through novel artificial neurons and in-sensor computing

AI development has brought great success to upgrading the information age.At the same time,the large-scale artificial neural network for building AI systems is thirsty for computing power,which is barely satisfied by the conventional computing hardware.In the post-Moore era,the increase in computing power brought about by the size reduction of CMOS in very large-scale integrated circuits(VLSIC)is challenging to meet the growing demand for AI computing power.To address the issue,technical approaches like neuromorphic computing attract great attention because of their feature of breaking Von-Neumann architecture,and dealing with AI algorithms much more parallelly and energy efficiently.Inspired by the human neural network architecture,neuromorphic computing hardware is brought to life based on novel artificial neurons constructed by new materials or devices.Although it is relatively difficult to deploy a training process in the neuromorphic architecture like spiking neural network(SNN),the development in this field has incubated promising technologies like in-sensor computing,which brings new opportunities for multidisciplinary research,including the field of optoelectronic materials and devices,artificial neural networks,and microelectronics integration technology.The vision chips based on the architectures could reduce unnecessary data transfer and realize fast and energy-efficient visual cognitive processing.This paper reviews firstly the architectures and algorithms of SNN,and artificial neuron devices supporting neuromorphic computing,then the recent progress of in-sensor computing vision chips,which all will promote the development of AI.

Atomic layer deposition in advanced display technologies:from photoluminescence to encapsulation

Driven by the growing demand for next-generation displays,the development of advanced luminescent materials with exceptional photoelectric properties is rapidly accelerating,with such materials including quantum dots and phosphors,etc.Nevertheless,the primary challenge preventing the practical application of these luminescent materials lies in meeting the required durability standards.Atomic layer deposition(ALD)has,therefore,been employed to stabilize luminescent materials,and as a result,flexible display devices have been fabricated through material modification,surface and interface engineering,encapsulation,cross-scale manufacturing,and simulations.In addition,the appropriate equipment has been developed for both spatial ALD and fluidized ALD to satisfy the low-cost,high-efficiency,and high-reliability manufacturing requirements.This strategic approach establishes the groundwork for the development of ultra-stable luminescent materials,highly efficient light-emitting diodes(LEDs),and thin-film packaging.Ultimately,this significantly enhances their potential applicability in LED illumination and backlighted displays,marking a notable advancement in the display industry.

Preliminary geological interpretation of long-wavelength magnetic anomalies over China and surrounding regions

Long-wavelength(>500 km)magnetic anomalies originating in the lithosphere were first found in satellite magnetic surveys.Compared to the striking magnetic anomalies around the world,the long-wavelength magnetic anomalies in China and surrounding regions are relatively weak.Specialized research on each of these anomalies has been quite inadequate;their geological origins remain unclear,in particular their connection to tectonic activity in the Chinese and surrounding regions.We focus on six magnetic high anomalies over the(1)Tarim Basin,(2)Sichuan Basin(3)Great Xing’an Range,(4)Barmer Basin,(5)Central Myanmar Basin,and(6)Sunda and Banda Arcs,and a striking magnetic low anomaly along the southern part of the Himalayan-Tibetan Plateau.We have analyzed their geological origins by reviewing related research and by detailed comparison with geological results.The tectonic backgrounds for these anomalies belong to two cases:either ancient basin basement,or subduction-collision zone.However,the geological origins of large-scale regional magnetic anomalies are always subject to dispute,mainly because of limited surface exposure of sources,later tectonic destruction,and superposition of multi-phase events.

LKMT:Linguistics Knowledge-Driven Multi-Task Neural Machine Translation for Urdu and English

Thanks to the strong representation capability of pre-trained language models,supervised machine translation models have achieved outstanding performance.However,the performances of these models drop sharply when the scale of the parallel training corpus is limited.Considering the pre-trained language model has a strong ability for monolingual representation,it is the key challenge for machine translation to construct the in-depth relationship between the source and target language by injecting the lexical and syntactic information into pre-trained language models.To alleviate the dependence on the parallel corpus,we propose a Linguistics Knowledge-Driven MultiTask(LKMT)approach to inject part-of-speech and syntactic knowledge into pre-trained models,thus enhancing the machine translation performance.On the one hand,we integrate part-of-speech and dependency labels into the embedding layer and exploit large-scale monolingual corpus to update all parameters of pre-trained language models,thus ensuring the updated language model contains potential lexical and syntactic information.On the other hand,we leverage an extra self-attention layer to explicitly inject linguistic knowledge into the pre-trained language model-enhanced machine translation model.Experiments on the benchmark dataset show that our proposed LKMT approach improves the Urdu-English translation accuracy by 1.97 points and the English-Urdu translation accuracy by 2.42 points,highlighting the effectiveness of our LKMT framework.Detailed ablation experiments confirm the positive impact of part-of-speech and dependency parsing on machine translation.

Design and characterization of biodegradable Mg-Zn-Ag metallic glasses

In order to develop the Mg-Zn-Ag metallic glasses(MGs)for biodegradable implant applications,the glass formation ability(GFA)and biocompatibility of Mg-Zn-Ag alloys were investigated using a combination of the calculation of phase diagrams(CALPHAD)and experimental measurements.High GFA potentiality of two alloy series,specifically Mg_(96-x)Zn_xAg_(4)and Mg_(94-x)Zn_xAg_6(x=17,20,23,26,29,32,35),was predicted theoretically and then substantiated through experimental testing.X-ray diffraction(XRD)and differential scanning calorimetry(DSC)techniques were used to evaluate the crystallinity,GFA,and crystallization characteristics of these alloys.The results showed that compositions between Mg_(73)Zn_(23)Ag_(4)and Mg_(64)Zn_(32)Ag_(4)for Mg_(96-x)Zn_xAg_4,Mg_(66)Zn_(28)Ag_(6)and Mg_(63)Zn_(31)Ag_(6for)Mg_(94-x)Zn_xAg_(6)displayed a superior GFA.Notably,the GFA of the Mg_(96-x)Zn_xAg_(4)series was better than that of the Mg_(94-x)Zn_xAg_(6)series.Furthermore,the Mg_(70)Zn_(26)Ag_4,Mg_(74)Zn_(20)Ag_6,and Mg_(71)Zn_(23)Ag_(6)alloys showed acceptable corrosion rates,good cytocompatibility,and positive effects on cell proliferation.These characteristics make them suitable for applications in medical settings,potentially materials as biodegradable implants.

Construct a 3D microsphere of HMX/B/Al/PTFE to obtain the high energy and combustion reactivity

Metal(aluminum and boron)based energetic materials have been wildly applied in various fields including aerospace,explosives and micro-devices due to their high energy density.Unfortunately,the low combustion efficiency and reactivity of metal fuels,especially boron(B),severely limit their practical applications.Herein,multi-component 3D microspheres of HMX/B/Al/PTFE(HBA)have been designed and successfully prepared by emulsion and solvent evaporation method to achieve superior energy and combustion reactivity.The reactivity and energy output of HBA are systematically measured by ignitionburning test,constant-volume explosion vessel system and bomb calorimetry.Due to the increased interfacial contact and reaction area,HBA shows higher flame propagation rate,faster pressurization rate and larger combustion heat of 29.95 cm/s,1077 kPa/s,and 6164.43 J/g,which is 1.5 times,3.5 times,and 1.03 times of the physical mixed counterpart(HBA-P).Meanwhile,HBA also shows enhanced energy output and reactivity than 3D microspheres of HMX/B/PTFE(HB)resulting from the high reactivity of Al.The reaction mechanism of 3D microspheres is comprehensively investigated through combustion emission spectral and thermal analysis(TG-DSC-MS).The superior reactivity and energy of HBA originate from the surface etching of fluorine to the inert shell(Al_(2)O_(3) and B_(2)O_(3))and the initiation effect of Al to B.This work offers a promising approach to design and prepare high-performance energetic materials for the practical applications.

A New Species of the Genus Boulenophrys(Anura,Megophryidae)from Eastern Guangdong,China

A new horned toad species,Boulenophrys elongata sp.nov.,is described from Mt.Lianhua,Huidong County,eastern Guangdong,China.The new species is phylogenetically closest to B.brachykolos,which is restricted to the east of the Pearl River Estuary(i.e.,Shenzhen City and Hong Kong SAR).The new species can be distinguished from all recognized congeners by a combination of morphological characters and genetic divergences in the combined mitochondrial 16S,12S and CO1 genes.We recommend the new species be listed as Data Deficient(DD)in the IUCN categorization,pending further investigation.

Skin care efficacy study of recombinant humanized collagen based on in vitro level

Studying the skin care efficacy of recombinant humanized collagen based on in vitro level.The stability of the recombinant humanized collagen was first analyzed by treating at different temperatures,then its skincare efficacy based on in vitro level was evaluated by detecting the inhibition rate of elastase,the inhibition rate of collagenase,the protein content of type I collagen in human fibroblasts,the inhibition of reactive oxygen species(ROS)with human keratinocytes,and the effects of the recombinant humanized collagen on the expression of hyaluronic acid(HA),filaggrin(FLG)and transglutaminase 1(TGM1)in keratinocytes.The results showed that recombinant humanized collagen was able to maintain stability at temperatures below 70℃.With regard to its skincare efficacy,recombinant humanized collagen could inhibit elastase and collagenase activities and promote the increase of type I collagen content in human fibroblasts.It also showed good inhibition of ROS in keratinocytes in vitro and could increase the expression of HA,FLG,and TGM1 in keratinocytes.In short,the recombinant humanized collagen exhibited a favourable skin care effect in vitro level.This study proved that it has potential firming,anti-wrinkle,moisturizing,and repairing efficacy,and is a valuable cosmetic raw material.