当代东北民族萨满神服造型艺术概述

东北地域各少数民族历史上普遍具有萨满教信仰,在其萨满教艺术品中,萨满神服的形态最为丰富。因生存条件、制服传统的不同,各族神服呈现出独特的造型、装饰特征。本文对东北民族遗存的萨满神服资料加以介绍。

大小兴安岭地区鄂伦春族萨满神服异同比较

大小兴安岭地区的鄂伦春族,虽然长期分居在这两个地区,但是由于他们笃信的萨满诸神相同,活动的方式也大致相同,加之他们间不断地迁徙往来,因此两地萨满所穿戴的服饰没有大的差异,无论其外形,还是结构,大体相同。如神帽,帽顶中央都立有一只神鹰,帽子的前脸垂有遮眼的串珠,帽顶的支架上都固定有铜铃,并系有各色飘带,披于四周等。再如神衣,都是用犴、鹿皮缝制而成,无领、紧袖、前开襟,前胸后背挂有大小不等的铜镜,

满族萨满神话载体——神服、神器探析

满族萨满神话载体存在于满族生活的方方面面,只要与萨满信仰有关的事物都可能成为萨满神话的载体。神服、神器是萨满信仰中最直观、最常见的器物,萨满们依靠这些器物的辅助完成神事活动,其神圣性不言而喻。这神圣性正是依附着神服、神器中所蕴含的神话或神话元素而存在的,而人的阐释使器物与神话之间真正建立了神圣关联,最终神服、神器成为萨满神话重要的载体形式。

略论萨满骨服的神话内涵

萨满神服是许多北方民族神话得以保存的重要载体,它所蕴含的神话再现了先民丰富的想象与思维形态,具有较高的文化价值。长春师范学院萨满文化研究所收藏的满族萨满骨服,以其丰富的神话内涵向我们展示了远古时代深邃而形象的萨满文化。

心脑神力口服液对小鼠抗氧化损伤作用的实验研究

目的研究心脑神力口服液对小鼠的抗氧化损伤作用。方法将50只昆明种小鼠随机分为对照组,新药低、中、高剂量组和旧药组,对照组给予蒸馏水,各给药组分别给予不同剂量的心脑神力口服液,给药途径均为灌胃,给药4周后,测定其血清SOD活力和MDA含量。结果与对照组相比,各给药组SOD活力增加;新药中、高剂量组MDA的含量低于对照组,差异有显著性。结论心脑神力口服液对小鼠具有抗氧化损伤作用,能增加SOD活力,降低MDA含量。

神曲消食口服液辅助治疗小儿功能性消化不良脾胃虚弱证的临床疗效及对胃泌素、胃动素的影响

目的观察神曲消食口服液辅助治疗小儿功能性消化不良(FD)脾胃虚弱证的临床疗效及对胃泌素(GAS)、胃动素(MOT)水平的影响。方法选取2020年1月至2021年10月在温岭市中医院儿科门诊就诊的FD脾胃虚弱证患儿80例,按照随机数字表法分为对照组和治疗组,各40例。对照组给予枸橼酸莫沙必利治疗,治疗组在对照组治疗方法的基础上给予神曲消食口服液治疗,2组均连续治疗14 d后统计疗效。结果治疗组总有效率为97.50%(39/40),显著高于对照组的82.50%(33/40),2组比较,差异有统计学意义(P<0.05)。治疗组腹胀腹痛、恶心呕吐及食欲不振缓解时间显著短于对照组,2组比较,差异均有统计学意义(P<0.05)。治疗前2组的中医证候积分比较,差异无统计学意义(P>0.05),具有可比性;治疗后2组的中医证候积分均较同组治疗前明显降低,差异均有统计学意义(P<0.05),且治疗组降低更显著(P<0.05)。治疗前2组血清GAS、MOT水平比较,差异无统计学意义(P>0.05),具有可比性;治疗后2组的血清GAS、MOT水平均较同组治疗前显著升高,差异均有统计学意义(P<0.05),且治疗组升高更显著(P<0.05)。结论神曲消食口服液辅助治疗小儿FD脾胃虚弱证,疗效确切,可有效缓解临床症状及体征,改善胃肠激素水平,值得临床推广应用。

A Self-organization Mapping Neural Network Algorithm and Its Application to Identify Ecosystem Service Zones

The self-organization mapping （SOM） neural network algorithm is a new method used to identify the ecosystem service zones at regional extent. According to the ecosystem assessment framework of Millennium Ecosystem Assessment （ MA）, this paper develops an indicator system and conducts a spatial cluster analysis at the 1km by I km grid pixel scale with the SOM neural network algorithm to sort the core ecosystem services over the vertical and horizontal dimensions. A case study was carried out in Xilingol League. The ecosystem services in Xilingol League could be divided to six different ecological zones. The SOM neural network algorithm was capable of identifying the similarities among the input data automatically. The research provides both spatially and temporally valuable information targeted sustainable ecosystem management for decision-makers.

Effect of Batroxobin on Expression of Neural Cell Adhesion Molecule in Temporal Infarction Rats and Spatial Learning and Memory Disorder

The effect of Batroxobin expression of neural cell adhesion molecule (NCAM) in left temporal ischemic rats with spatial memory disorder was investigated by means of Morri's water maze and immunohistochemical methods. The results showed that the mean reaction time and distance of temporal ischemic rats for searching a goal were significantly longer than those of sham-operated rats and at the same time NCAM expression of left temporal ischemic region was significantly increased. However, the mean reaction time and distance of Batroxobin-treated rats were shorter and they used normal strategies more often and earlier than those of ischemic rats. The number of NCAM immune reactive cells of Batroxobin-treated rats was more than that of ischemic group. In conclusion, Batroxobin can improve spatial memory disorder of temporal ischemic rats and the regulation of the expression of NCAM is probably related to the neuroprotective mechanism.

Application of FAHP and Artificial Neural Network on Clothing Plant Location

Clothing manufacturers＇ direct investment and joint ventures in developing regions have seen to grow rapidly in the past few decades. Non-optimized selection can contribute to adverse effects affecting the performance of the plants on aspects of productivity, manufacturing and logistics cost. Selection of proper plant location is thus crucial. The conventional approaches to sites location are based on the factors and their weights. However, determining the weight of each factor is very difficult and time consuming. While the situation is changed, all the work must be redone again. This study aims to develop a decision-making system on clothing plant location for Hoog Kong clothing manufacturer. The proposed system utilizes artificial neural network to study the relationship between the factors and the suitability index of candidate sites. Firstly, the factors are stratified using the fuzzy analytical hierarchy process （FAHP） by review the related references and interviewing the experts. Secondly, the corresponding data are collected from the experts by questionnaire and the related government publication. Finally, the feedforward neural network with error backpropagation（EBP） learning algorithm is trained and applied to make decision. The results show that the proposed system performs well and has the characteristic of adaptability and plasticity.

Prediction of the Performance of the Fabrics in Garment Manufacturing by Artificial Neural Network

An artificial neural network is used to predict the performance of fabrics in clothing manufacturing. The predictions are based on fabric mechanical properties measured on the FAST system. The influences of the different ANNs construct on the convergence speed and the prediction accuracy are investigated. The result indicates that the BP neural network is an efficiency technique and has a wide prospect in the application to garment processing.

A Web-based Intelligent Fashion Design System

A web-based fashion design system-FashDesn was developed for non-professionals to make their own style-based design by choosing and combining fashion parts. We use genetic algorithm to find the optimal satisfied style, while the fitness function of GA is approached by artificial neural network. The users’ style intention can be reached through the learning process of the artificial neural network. The system architecture and some realization details of the system are given in the paper. An output contrast for elegant style women’s before and after user’s interaction is used to illustrate its usefulness in the end.

Data-driven intelligent monitoring system for key variables in wastewater treatment process

In wastewater treatment process(WWTP), the accurate and real-time monitoring values of key variables are crucial for the operational strategies. However, most of the existing methods have difficulty in obtaining the real-time values of some key variables in the process. In order to handle this issue, a data-driven intelligent monitoring system, using the soft sensor technique and data distribution service, is developed to monitor the concentrations of effluent total phosphorous(TP) and ammonia nitrogen(NH_4-N). In this intelligent monitoring system, a fuzzy neural network(FNN) is applied for designing the soft sensor model, and a principal component analysis(PCA) method is used to select the input variables of the soft sensor model. Moreover, data transfer software is exploited to insert the soft sensor technique to the supervisory control and data acquisition(SCADA) system. Finally, this proposed intelligent monitoring system is tested in several real plants to demonstrate the reliability and effectiveness of the monitoring performance.

Color Perception of the Textile and Clothing

The color perception is related to color objects, vision system and central nervous system. The methods of evaluation, classification and prediction of the color perception are investigated and analyzed in this paper. The artificial neural networks are used for color perception, clustering and predicting based on the given data obtained from both objective measurement and subjective evaluation.

The Introduction of Pharmaceutical Care in Psychiatric Outpatients in Community Pharmacy of the Northeast Region of Argentina

The purpose of this paper is to implement a pharmaceutical care program in psychiatric outpatients in a community pharmacy. Outpatients （536） with psychiatric treatment requiring the dispensing of medication prescribed by a psychiatrist were followed up in a community pharmacy, where different medicines were prescribed as PS （pharmaceutical specialties）, PC （pharmaceutical compounding） or both PS and PC. Each prescription was registered with details on a patient level. Also, three reporting sheets were designed： patients profile, patients monitoring and patients counseling. The total study population in the community pharmacy consisted of 536 outpatients： 357 （66.6%） females and 179 （33.4%） males. Most of the outpatients （78.5%） have health insurance, 50% correspond to public and 28.5% to private institution. The other patients （21.5%） do not have medical insurance. We also observed that the education level of these patients was： primary school 19.1%; high school 45.9%; college 15.3% and university 20.7%. Many patients had more than one psychiatric diagnosis, to whom were prescribed different medicines. All the medication studies on the charts were screened for prescriptions with antidepressants and other psychotropic drugs, starting on the date of first diagnosis made by a psychiatrist. The counseling to the patients was also registered. The possibility of the follow-up of these outpatients in the community pharmacy promoted the development of the psychiatric pharmacy and all advances in care for patients with mental health needs, working in closer collaboration with psychiatrists.

Autonomic QoS Management Mechanism in Software Defined Network

With the increase of network complexity,the flexibility of network control and management becomes a nontrivial problem.Both Software Defined Network(SDN) and Autonomic Network technologies are sophisticated technologies for the network control and management.These two technologies could be combined together to construct a software defined self-managing solution for the future network.An autonomic QoS management mechanism in Software Defined Network(AQSDN) is proposed in this paper.In AQSDN,the various QoS features can be configured autonomically in an OpenFlow switch through extending the OpenFlow and OF-Config protocols.Based on AQSDN,a novel packet context-aware QoS model(PCaQoS) is also introduced for improving the network QoS.PCaQoS takes packet context into account when packet is marked and managed into forwarding queues.The implementation of a video application's prototype which evaluates the self-configuration feature of the AQSDN and the enhancement ability of the PCaQoS is presented in order to validate this design.

Secure Mobile Crowdsensing Based on Deep Learning

To improve the quality of multimedia services and stimulate secure sensing in Internet of Things applications, such as healthcare and traffic monitoring, mobile crowdsensing(MCS) systems must address security threats such as jamming, spoofing and faked sensing attacks during both sensing and information exchange processes in large-scale dynamic and heterogeneous networks. In this article, we investigate secure mobile crowdsensing and present ways to use deep learning(DL) methods, such as stacked autoencoder, deep neural networks, convolutional neural networks, and deep reinforcement learning, to improve approaches to MCS security, including authentication, privacy protection, faked sensing countermeasures, intrusion detection and anti-jamming transmissions in MCS. We discuss the performance gain of these DLbased approaches compared to traditional security schemes and identify the challenges that must be addressed to implement these approaches in practical MCS systems.

A Strategy of Density-Based Partitioning for Scalability Problem in Network Self-management

A density-based partitioning strategy is proposed for large domain networks in order to deal with the scalability issue found in autonomic networks considering, as a scenario, the autonomic Quality of Service （QoS） management context. The approach adopted focus as on obtaining dense network partitions having more paths for a given vertices set in the domain. It is demonstrated that dense partitions improve autonomic processing scalability, for instance, reducing routing process complexity. The solution looks for a significant trade-off between partition autonomic algorithm execution time and path selection quality in large domains. Simulation scenarios for path selection execution time are presented and discussed. Authors argue that autonomic networks may benefit from the dense partition approach proposed by achieving scalable, efficient and near real-time support for autonomic management systems.

呼伦贝尔巴尔虎蒙古博“希图根·塔嘿乎”仪式音乐考察

'希图根·塔嘿乎'(神灵祭祀)仪式是直接体现巴尔虎蒙古族博教(俗称'萨满教')信仰体系的重要祭祀仪式之一。本文试图将巴尔虎蒙古博祭祀仪式音乐置于巴尔虎蒙古博教信仰体系之中进行研究,分析巴尔虎蒙古博教灵魂观念下形成的'博——翁古——神灵'之间的互动关系在巴尔虎蒙古博祭祀仪式及仪式音乐中的展现形式,以及由此形成的巴尔虎蒙古博祭祀音乐与祭祀仪式的同型同构文化构成现象。

Finite-Time Neural Funnel Control for Motor Servo Systems with Unknown Input Constraint

In this paper, a finite-time neural funnel control(FTNFC) scheme is proposed for motor servo systems with unknown input constraint. To deal with the non-smooth input saturation constraint problem, a smooth non-affine function of the control input signal is employed to approximate the saturation constraint, which is further transformed into an affine form according to the mean-value theorem. A fast terminal sliding mode manifold is constructed by using a novel funnel error variable to force the tracking error falling into a prescribe boundary within a finite time. Then, a simple sigmoid neural network is utilized to approximate the unknown system nonlinearity including the saturation.Different from the prescribed performance control(PPC), the proposed finite-time neural funnel control avoids using the inverse transformed function in the controller design, and could guarantee the prescribed tracking performance without knowing the saturation bounds in prior. The effectiveness and superior performance of the proposed method are verified by comparative simulation results.

Iptakalim,an ATP-sensitive potassium channel opener,confers neuroprotection against cerebral ischemia/reperfusion injury in rats by protecting neurovascular unit cells

Objective:To investigate the role of iptakalim,an ATP-sensitive potassium channel opener,in transient cerebral ischemia/reperfusion (I/R) injury and its involved mechanisms.Methods:Intraluminal occlusion of middle cerebral artery (MCAO) in a rat model was used to investigate the effect of iptakalim at different time points.Infarct volume was measured by staining with 2,3,5-triphenyltetrazolium chloride,and immunohistochemistry was used to evaluate the expressions of Bcl-2 and Bax.In vitro,neurovascular unit (NVU) cells,including rat primary cortical neurons,astrocytes,and cerebral microvascular endothelial cells,were cultured and underwent oxygen-glucose deprivation (OGD).The protective effect of iptakalim on NVU cells was investigated by cell viability and injury assessments,which were measured by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide and release of lactate dehydrogenase.Caspase-3,Bcl-2 and Bax mRNA expressions were evaluated by real-time polymerase chain reaction (PCR).Results:Administration of iptakalim 0 or 1 h after reperfusion significantly reduced infarct volumes,improved neurological scores,and attenuated brain edema after cerebral I/R injury.Iptakalim treatment (0 h after reperfusion) also reduced caspase-3 expression and increased the ratio of Bcl-2 to Bax by immunohistochemistry.Iptakalim inhibited OGD-induced cell death in cultured neurons and astrocytes,and lactate dehydrogenase release from cerebral microvascular endothelial cells.Iptakalim reduced mRNA expression of caspase-3 and increased the ratio of Bcl-2 to Bax in NVU cells.Conclusions:Iptakalim confers neuroprotection against cerebral I/R injury by protecting NVU cells via inhibiting of apoptosis.