In Vitro Propagation and Artificial Seed Production of Fritillaria cirrhosa D. Don, an Endangered Medicinal Plant

Fritillaria cirrhosa D.Don(Liliaceae)is an endangered perennial bulbous plant and its dry bulb is a valuable med-icinal material with antitussive and expectorant effects.Nevertheless,lack of resources and expensive prices make it difficult to meet clinical needs.This study presents a regeneration system aimed at overcoming the challenge of inadequate supply in F.cirrhosa,focusing on:(1)callus induction,(2)bulblets and adventitious bud induction,and(3)artificial seed production.Callus development was achieved in 84.93%on Murashige and Skoog(MS)medium fortified with 1.0 mg·L^(-1) picloram.The optimal medium for callus differentiation into regenerated bulb-lets was MS medium supplemented with 1.0 mg·L^(-1)6-benzyladenine(6-BA)and 0.2 mg·L^(-1)α-naphthaleneacetic acid(NAA).Subsequently,bulblets and adventitious buds were induced from regenerated bulblet sections cul-tured on MS medium fortified with 0.3 mg·L^(-1)6-BA+1.0 mg·L^(-1)2,4-dichlorophenoxyacetic acid(2,4-D),2.0 mg·L^(-1)6-BA+0.5 mg·L^(-1),and the induction rates were 88.17%and 84.24%,respectively.The regenerated bulblets were transplanted into a substrate of humus soil,river sand,and pearlite(1:1:1)after low-temperature treatment.The germination rate was 42.80%after culture for 30 days.Regenerated bulblets were used for encap-sulations in liquid MS medium containing 3%sucrose(w/v)+0.5 mg·L^(-1) NAA+2.0 mg·L^(-1)6-BA+3%sodium alginate(w/v)with a 10 min exposure to 2%CaCl_(2).Under non-aseptic conditions,the germination rate reached 81.67%,while the rooting rate was 20.56%after 45 days.The capsule added 1.0 g·L^(-1) carbendazim and 1.0 g·L^(-1) activated carbon was the best component of artificial seeds.This study successfully established an efficient regen-eration system for the rapid propagation of F.cirrhosa,involving in vitro bulblet regeneration and artificial seed production.This method introduces a novel approach for efficient breeding and germplasm preservation,making it suitable for large-scale industrial resource production.

Artificial Intelligence for Maximizing Agricultural Input Use Efficiency: Exploring Nutrient, Water and Weed Management Strategies

Agriculture plays a crucial role in the economy,and there is an increasing global emphasis on automating agri-cultural processes.With the tremendous increase in population,the demand for food and employment has also increased significantly.Agricultural methods traditionally used to meet these requirements are no longer ade-quate,requiring solutions to issues such as excessive herbicide use and the use of chemical fertilizers.Integration of technologies such as the Internet of Things,wireless communication,machine learning,artificial intelligence(AI),and deep learning shows promise in addressing these challenges.However,there is a lack of comprehensive documentation on the application and potential of AI in improving agricultural input efficiency.To address this gap,a desk research approach was used by utilizing peer-reviewed electronic databases like PubMed,Scopus,Goo-gle Scholar,Web of Science,and Science Direct for relevant articles.Out of 327 initially identified articles,180 were deemed pertinent,focusing primarily on AI’s potential in enhancing yield through better management of nutrients,water,and weeds.Taking into account researchfindings worldwide,we found that AI technologies could assist farmers by providing recommendations on the optimal nutrients to enhance soil quality and deter-mine the best time for irrigation or herbicide application.The present status of AI-driven automation in agricul-ture holds significant promise for optimizing agricultural input utilization and reducing resource waste,particularly in the context of three pillars of crop management,i.e.,nutrient,irrigation,and weed management.

Face Mask and Social Distance Monitoring via Computer Vision and Deployable System Architecture

The coronavirus(COVID-19)is a lethal virus causing a rapidly infec-tious disease throughout the globe.Spreading awareness,taking preventive mea-sures,imposing strict restrictions on public gatherings,wearing facial masks,and maintaining safe social distancing have become crucial factors in keeping the virus at bay.Even though the world has spent a whole year preventing and curing the disease caused by the COVID-19 virus,the statistics show that the virus can cause an outbreak at any time on a large scale if thorough preventive measures are not maintained accordingly.Tofight the spread of this virus,technologically developed systems have become very useful.However,the implementation of an automatic,robust,continuous,and lightweight monitoring system that can be efficiently deployed on an embedded device still has not become prevalent in the mass community.This paper aims to develop an automatic system to simul-taneously detect social distance and face mask violation in real-time that has been deployed in an embedded system.A modified version of a convolutional neural network,the ResNet50 model,has been utilized to identify masked faces in peo-ple.You Only Look Once(YOLOv3)approach is applied for object detection and the DeepSORT technique is used to measure the social distance.The efficiency of the proposed model is tested on real-time video sequences taken from a video streaming source from an embedded system,Jetson Nano edge computing device,and smartphones,Android and iOS applications.Empirical results show that the implemented model can efficiently detect facial masks and social distance viola-tions with acceptable accuracy and precision scores.

Prediction of impedance responses of protonic ceramic cells using artificial neural network tuned with the distribution of relaxation times

A deep-learning-based framework is proposed to predict the impedance response and underlying electrochemical behavior of the reversible protonic ceramic cell(PCC) across a wide variety of different operating conditions.Electrochemical impedance spectra(EIS) of PCCs were first acquired under a variety of opera ting conditions to provide a dataset containing 36 sets of EIS spectra for the model.An artificial neural network(ANN) was then trained to model the relationship between the cell operating condition and EIS response.Finally,ANN model-predicted EIS spectra were analyzed by the distribution of relaxation times(DRT) and compared to DRT spectra obtained from the experimental EIS data,enabling an assessment of the accumulative errors from the predicted EIS data vs the predicted DRT.We show that in certain cases,although the R^(2)of the predicted EIS curve may be> 0.98,the R^(2)of the predicted DRT may be as low as~0.3.This can lead to an inaccurate ANN prediction of the underlying time-resolved electrochemical response,although the apparent accuracy as evaluated from the EIS prediction may seem acceptable.After adjustment of the parameters of the ANN framework,the average R^(2)of the DRTs derived from the predicted EIS can be improved to 0.9667.Thus,we demonstrate that a properly tuned ANN model can be used as an effective tool to predict not only the EIS,but also the DRT of complex electrochemical systems.

An Artificial Neural Network-Based Model for Effective Software Development Effort Estimation

In project management,effective cost estimation is one of the most cru-cial activities to efficiently manage resources by predicting the required cost to fulfill a given task.However,finding the best estimation results in software devel-opment is challenging.Thus,accurate estimation of software development efforts is always a concern for many companies.In this paper,we proposed a novel soft-ware development effort estimation model based both on constructive cost model II(COCOMO II)and the artificial neural network(ANN).An artificial neural net-work enhances the COCOMO model,and the value of the baseline effort constant A is calibrated to use it in the proposed model equation.Three state-of-the-art publicly available datasets are used for experiments.The backpropagation feed-forward procedure used a training set by iteratively processing and training a neural network.The proposed model is tested on the test set.The estimated effort is compared with the actual effort value.Experimental results show that the effort estimated by the proposed model is very close to the real effort,thus enhanced the reliability and improving the software effort estimation accuracy.

Artificial Bee Colony with Cuckoo Search for Solving Service Composition

In recent years,cloud computing has provided a Software As A Service(SaaS)platform where the software can be reused and applied to fulfill compli-cated user demands according to specific Quality of Services(QoS)constraints.The user requirements are formulated as a workflow consisting of a set of tasks.However,many services may satisfy the functionality of each task;thus,searching for the composition of the optimal service while maximizing the QoS is formulated as an NP-hard problem.This work will introduce a hybrid Artificial Bee Colony(ABC)with a Cuckoo Search(CS)algorithm to untangle service composition problem.The ABC is a well-known metaheuristic algorithm that can be applied when dealing with different NP-hard problems with an outstanding record of performance.However,the ABC suffers from a slow convergence problem.Therefore,the CS is used to overcome the ABC’s limitations by allowing the abandoned bees to enhance their search and override the local optimum.The proposed hybrid algorithm has been tested on 19 datasets and then compared with two standard algorithms(ABC and CS)and three state-of-the-art swarm-based composition algorithms.In addition,extensive parameter study experiments were conducted to set up the proposed algorithm’s parameters.The results indicate that the proposed algorithm outperforms the standard algorithms in the three comparison criteria(bestfitness value,averagefitness value,and average execution time)overall datasets in 30 different runs.Furthermore,the proposed algorithm also exhibits better performance than the state–of–the–art algorithms in the three comparison criteria over 30 different runs.

Seismic wave input method for three-dimensional soil-structure dynamic interaction analysis based on the substructure of artificial boundaries

The method of inputting the seismic wave determines the accuracy of the simulation of soil-structure dynamic interaction. The wave method is a commonly used approach for seismic wave input, which converts the incident wave into equivalent loads on the cutoff boundaries. The wave method has high precision, but the implementation is complicated, especially for three-dimensional models. By deducing another form of equivalent input seismic loads in the fi nite element model, a new seismic wave input method is proposed. In the new method, by imposing the displacements of the free wave fi eld on the nodes of the substructure composed of elements that contain artifi cial boundaries, the equivalent input seismic loads are obtained through dynamic analysis of the substructure. Subsequently, the equivalent input seismic loads are imposed on the artifi cial boundary nodes to complete the seismic wave input and perform seismic analysis of the soil-structure dynamic interaction model. Compared with the wave method, the new method is simplifi ed by avoiding the complex processes of calculating the equivalent input seismic loads. The validity of the new method is verifi ed by the dynamic analysis numerical examples of the homogeneous and layered half space under vertical and oblique incident seismic waves.

Artifi cial liver support system in treatment of liverfailure after acute poisoning

BACKGROUND： Acute poisoning （AP） may cause failure of the liver and kidney, and evendeath. This study aimed to investigate the efficacy of artificial liver support system （ALSS） on thetreatment of liver failure after acute poisoning.METHODS： A total of 31 patients with liver failure caused by AP were admitted to emergency ICU,central ICU, and Department of Gastroenterology from 2005 to 2009 in Zhongshan Hospital Affi liatedto Xiamen University, China. Among them, 13 patients served as a treatment group, and used ALSS inaddition to detoxifi cation treatment and protective treatment of liver function, and the other 18 patientsserved as a control group receiving detoxifi cation treatment and protective treatment of liver function.RESULTS： In the treatment group, 10 patients （76.9%） were cured or improved, 2 died, and1 was discharged against advice. In the 18 patients in the control group, 7 （38.9%） were cured orimproved, 3 died, and 8 were discharged against advice. There was a significant difference in therates of improvement between the two groups （P〈0.05）.CONCLUSION： ALSS is a safe and effective clinical method for the treatment of acute toxicliver failure.

Theoretical Study of Similar Experimental Method for Durability of Concrete under Artifi cial Climate Environment

Based on the similarity theory,a new experimentalmethod named Similar ExperimentalMethod for Durability of Concrete（SEMDC）was established.The existing experimentalmethods for durability of concrete were summarized,and the merits and demerits of these experimentalmethods were analyzed.Major factors affecting the durability of concrete were found through literature review.These factors were analyzed and the similarity criteria were established according to the similarity theory,and then the SEMDC was established according to the rules of these criteria.The various influentialfactors of the experimentalmethod were analyzed and the merits and demerits of this new experimentalmethod were discussed.According to SEMDC,changing the geometry shrinkage ratio was the only way to accelerate the test in order to keep the experiment similar to the reality.There were few other parameters which need to be changed in SEMDC,making the test easy to be achieved.According to SEMDC,time shrinkage ratio was the square of geometric shrinkage ratio,so an appropriate increase of the geometric shrinkage ratio could accelerate the test.Finally,an example of experimentaldesign for durability of concrete was devised theoretically base on SEMDC theory.

Numerical Investigation on Vibration Performance of Flexible Plates Actuated by Pneumatic Artificial Muscle

This paper theoretically introduced the feasibility of changing the vibration characteristics offlexible plates by using bio-inspired,extremely light,and powerful Pneumatic Artificial Muscle(PAM)actuators.Many structural plates or shells are typicallyflexible and show highvibration sensitivity.For this reason,this paper provides a way toachieve active vibrationcontrolfor suppressing the oscillations ofthese structuresto meet strict stability,safety,and comfort requirements.The dynamic behaviors of the designed plates are modeled by using thefinite element(FE)method.As is known,the output force vs.contraction curve of PAM is nonlinear generally.In this presentfinite element model,the maximum forces provided by PAM in different air pressure are adopted as controlling forces for applying for the plate.The non-linearity between the output force and displacement of PAM is avoided in this study.The dynamic behaviors of plates with several independent groups of controlling forces are observed and studied.The results show that the natural frequencies of the plate can be varying and the max amplitude decreases significantly if the controlling forces are applied.The present work also demonstrates the potential of the PAM actuators as valid means for damping out the vibration offlexible systems.

The Effect of Cycling and Arm Ergometer Exercises on Physical and Psychosocial Functions: Application in Patients Undergoing Coronary Artery Bypass Surgery

Aim: The aim of this study was to compare the effects of bicycle and arm ergometer exercises on physical and psychosocial functions in patients who underwent Coronary Artery Bypass Surgery. Methods: A total of 39 cases (35 males, 4 females) were included in the study, with 23 participants aged between 52 and 65 using bicycle ergometers and a group of 16 people who performed arm ergometers opposite. After the demographic data were recorded, physical functions of all individuals participating in the study were evaluated with a 6-minute walk test, bioimpedance analysis, HDL, LDL, Triglyceride and Total cholesterol values, and psychosocial functions were evaluated with the Beck depression scale, modified borg scale and SF 36 questionnaires before and after the training. All participants were given bicycle or arm ergometer exercises for 6 weeks, 5 sessions per week, for a total of 30 sessions. Result: When the results were examined, it was observed that there was a statistically significant increase in walking distance of the people in the bicycle ergometer group compared to the arm ergometer group (p < 0.05). In addition, it was revealed that there was a statistically significant difference in the general health parameter, which is one of the sub-parameters of SF 36, in the arm ergometer group compared to the bicycle ergometer group (p Conclusion: When we look at the results of this study, it is important in terms of revealing that bicycle and arm ergometer exercises similarly improve the physical and psychosocial functions of patients who have undergone Coronary Artery Bypass Surgery. However, it has been shown that cycling exercises are much more advantageous in improving functional capacity. Summary Statement: What is already known about this topic? 1) Walking and arm exercises are good for heart diseases. What this paper adds? 2) Demonstrated that cycling and arm ergometer exercises have curative aspects for patients undergoing Coronary Artery Bypass Surgery. The implications of this paper: 3) As a result, it has been revealed that cycling and arm ergometry techniques are good indicators in patients who have undergone Coronary Artery Bypass Surgery.

Diagnostic utility of narrow-band imaging endoscopy for pharyngeal superfi cial carcinoma

AIM: To investigate the endoscopic features of pharyngeal superfi cial carcinoma and evaluate the utility of narrow-band imaging (NBI) for this disease. METHODS: In the present prospective study, 335 patients underwent conventional white light (CWL) en-doscopy and non-magnifi ed/magnifi ed NBI endoscopy, followed by an endoscopic biopsy, for 445 superfi cial lesions in the oropharynx and hypopharynx. The macroscopic appearance of superfi cial lesions was categorized as either elevated (< 5 mm in height), flat, or depressed (not ulcerous). Superficial carcinoma (SC) was defi ned as a superfi cial lesion showing high-grade dysplasia or squamous cell carcinoma on histology. The color, delineation, and macroscopic appearances of the lesions were evaluated by CWL endoscopy. The ratio of the brownish area/intervascular brownish epithelium (IBE), as well as microvascular proliferation, dilation, and irregularities, was determined by non-magnifi ed/ magnifi ed NBI endoscopy. An experienced pathologist who was unaware of the endoscopic fi ndings made the histological diagnoses. By comparing endoscopic fi ndings with histology, we determined the endoscopic features of SC and evaluated the diagnostic utility of NBI. RESULTS: The 445 lesions were divided histologically into two groups: a non-SC group, including non-neoplasia and low-grade dysplasia cases, and an SC group. Of the 445 lesions examined, 333 were classified as non-SC and 112 were classif ied as SC. There were no significant differences in age, gender, or the location of the lesions between the patients in the two groups. The mean diameter of the SC lesions was signif icantly greater than that of non-SC lesions (11.0 ± 7.6 mm vs 4.6 ± 3.6 mm, respectively, P < 0.001). Comparisons of CWL endoscopy fi ndings for SC and non-SC lesions by univariate analysis revealed that the incidence of redness (72% vs 41%, respectively, P < 0.001) and a flat or depressed type of lesion (58% vs 44%, respectively, P = 0.013) was significantly higher in the SC group. Using non-magnifi ed NBI endoscopy, the incidence of a brownish area was signifi cantly higher for SC lesions (79% vs 57%, respectively, P < 0.001). On magnifi ed NBI endoscopy, the incidence of IBE (68% vs 33%, P < 0.001) and microvascular proliferation (82% vs 51%, P < 0.001), dilation (90% vs 76%, P =0.002), and irregularity (82% vs 31%, P < 0.001) was also signifi cantly higher for the SC compared with the non-SC lesions. Multivariate analysis revealed that the incidence of redness (P = 0.022) on CWL endoscopy and IBE (P < 0.001) and microvascular irregularities (P < 0.001) on magnif ied NBI endoscopy was signif icantly higher in SC than non-SC lesions. Redness alone exhibited signifi cantly higher sensitivity and signifi cantly lower specifi city for the diagnosis of SC compared with redness plus IBE and microvascular irregularities (72% vs 52%, P = 0.002; and 59% vs 92%, P < 0.001, respectively). The accuracy of redness plus IBE and irregularities for the diagnosis of SC was signifi cantly greater than using redness alone (82% vs 62%, respectively, P < 0.001). CONCLUSION: Redness, IBE, and microvascular irregularities appear to be closely related to SC lesions. Magnifi ed NBI endoscopy may increase the diagnostic accuracy of CWL endoscopy for SC.

Treating defective damage of facial nerve with great au-ricular nerve grafting covered by pediculated fascial tube

Objective To study the curative effect of grafting great auricul ar nerve with pedic ulated fascial tube in defective dam age of facial nerve.Met hod All the patients in the study were tre ated by grafting great auricular nerv e which was covered by pediculated f ascial tube near facial nerve trunk.Resul t The 3otogenic fascial paralysis pat ients had grade III recovery of facia l n erve function(30%～38%)2.0to 2.5years after the nerve grafting ope ra tion;2post-traumatic facial paral ysis patients had grade II recovery o f facial nerve function(69%～71%)2.5to 3.5years after the nerve graf ting operation.Conclusion The grafting of pediculated fascial tube surrounded great auricular nerve can provide a biological environment wi th excellent blood supply for the ple rosis and regeneration of nerves and can accelerate the func tional recovery of nerves after the nerve grafting.

Bridging the Gap:Integration of Artificial Intelligence with Organ-on-Chip(AI-OoC)

.Organ-on-Chip(OoC)has emerged as a revolutionary approach to emulate human organ function-ality in vitro,offering unparalleled insights into physiological processes and disease modeling.The integration of artificial intelligence(AI)with OoC platforms presents a transformative synergy,combining the precision of microscale organ replication with the analytical prowess of intelligent algorithms,is emerging as a transforma-tive force in harnessing the full potential of OoC.This perspective investigates the multifaceted implications of integrating AI with OoC,examining its impact on biomedical research,acknowledging the synergistic po-tential that arises from combining the precision of microscale organ replication with the analytical capabilities of intelligent algorithms,and fostering a future where the intricate workings of the technology and biology.

共享平台的生存空间和社会价值

基于互联网的共享经济迅猛发展,满足了越来越多的社会需求.基于这一背景,首先分析了共享经济的业态、发展阶段以及共享经济的优势和劣势.然后从平台的视角,以“相对综合优势”指标为出发点定义了“市场份额增量指标”,研究共享平台与专业平台同时进入市场竞争和平台分别作为领导者与追随者等不同情形下的竞争情况与均衡状态.最后考察共享平台在市场上的生存空间和社会价值.研究发现:1)若共享平台和专业平台同时进入市场竞争,只有当专业平台相对综合优势足够显著时,共享平台将可能退出市场;否则即使面对专业平台的相对综合优势,共享平台仍然能够生存,出现两类平台相互竞争的局面;而且闲置资源的低回报要求,使得共享平台将专业平台挤出市场变得可能.2)相比同时进入市场竞争,共享平台作为追随者参与竞争的优势更明显,平台具有后发优势.3)从共享平台的社会价值来看,共享平台进入市场不一定增加社会福利,只有当共享平台从社会福利角度出发,达到最优的产出水平时,其进入市场能够补偿专业平台的多样化损失,实现最优补偿.

人工智能技术在法医学中的应用研究进展

人工智能(artifi cial intelligence, AI)是基于大数据、机器学习等技术的一种智能化解决方案,能够提升形态学识别能力、诊断效率及质量。随着科学技术的迅猛发展,AI技术突飞猛进,成果应用日益广泛,为解决各类现实问题提供了新的方案和参考。“AI+”被广泛用于各行各业,取得了优异的成绩,其中法医学领域近年来涌现出了一批优秀的研究成果。本文对近三年来国内外法医学者发表的有关论文进行综述,希望能够为全国法医同行在病理学、临床学、人类学、毒物学等方面的研究提供新的思路。

Microbial Fertilizer: A Sustainable Strategy for Medicinal Plants Production

Medicinal plants have aroused considerable interest as an alternative to chemical drugs due to the beneficial effects of their active secondary metabolites.However,the extensive use of chemical fertilizers and pesticides in pursuit of yield has caused serious pollution to the environment,which is not conducive to sustainable devel-opment in thefield of medicinal plants.Microbial fertilizers are a type of“green fertilizer”containing specific microorganisms that can improve the soil microbial structure,enhance plant resistance to biological and abiotic stresses,and increase the yield of medicinal plants.The root exudates of medicinal plants attract different micro-organisms to the rhizosphere,which then migrate further to the plant tissues.These microbes can increase the levels of soil nutrients,and improve the physical and chemical properties of soil through nitrogenfixation,and phosphorus and potassium solubilization.In addition,soil microbes can promote the synthesis of hormones that increase plant growth and the accumulation of active compounds,eventually improving the quality of med-icinal plants.In 2022,the total value of the global microbial fertilizer market was$4.6 billion and is estimated to reach$10.36 billion by 2030.In this review,we have summarized the types of microbial fertilizers,the coloniza-tion and migration of microorganisms to plant tissues,and the beneficial effects of microbial fertilizers.In addi-tion,the prospects of developing microbial fertilizers and their application for medicinal plants have also been discussed.It aims to provide a reference for the rational application of microbial fertilizers in thefield of med-icinal plants and the green and sustainable development of medicinal plant resources.

新时代年轻干部成长研究:现状与展望

建设一支贯彻习近平新时代中国特色社会主义思想、符合新时期好干部标准、忠诚干净担当、数量充足、充满活力的高素质专业化年轻干部队伍,事关党的事业发展后继有人和国家长治久安。文章以年轻干部的相关政策文件和文献为基础,梳理了促进年轻干部成长的相关政策举措,并对年轻干部的成长规律进行了总结:干部能力素质必须符合中国特色社会主义伟大事业的发展需要;干部能力素质的提升是一个由量变到质变的发展过程,个人和组织都负有重要责任;理论学习是基础,实践锻炼是关键。从激励机制来看,应坚持激励与约束并重。然而,部分年轻干部的发展存在以下四点困境:佛系心态,为官不为;眼高手低,期望过高;价值观念偏差,公共服务动机缺失;培养机制缺位,干事创业热情不足。因此,要建立一个涵盖培养主体、选任理念、培养体系、管理机制的培养系统。未来要进一步推进对年轻干部的概念指向、成长规律、能力素质、方法论、战略需求导向这五方面的研究。

生成式人工智能商业秘密保护困境及对策

生成式人工智能以大语言模型为基础,与传统的人工智能相比可以执行更加多样化的任务,其作为商业秘密进行保护具有保护范围广、保护成本低、保护期限更长等优势。但也存在缺乏商业秘密客体保护范围规定,合理保密措施认定标准不明确、例外规定不完善等困境。为了更好地发挥商业秘密保护的作用,需要进一步完善相关法律法规,明确商业秘密保护客体范围、合理保密措施认定标准和例外规定,更好地保护生成式人工智能权利人的商业秘密。