Integrating Generative and Aspect-Oriented Technologies
UiráKulesza,Alessandro Garcia,Carlos Lucena,Arndt von Staa Software Engineering Laboratory,SoC+Agents Group,Computer Science Department
Pontifícal Catholic University of Rio de Janeiro - PUC-Rio
e-mail:[uira,afgarcia,lucena,arndt]@inf.puc-rio.br
Abstract
Over the last years, two new software engineering approaches have been proposed: generative programming and aspect-oriented software development. Generative programming addresses the study and definition of methods and tools that enable the automatic production of system families from a high-level specification. Aspect-oriented software development has been proposed as a technique for improving separation of concerns in the construction of OO software and supporting improved reusability and ease of evolution. The use of aspect-oriented techniques in a definition of a generative approach can bring benefits to the modeling and generation of crosscutting features since early development stages. This paper presents our experience in the definition of an aspect-oriented generative approach. The proposed approach explores the multi-agent systems domain to enable the code generation of agent architectures.
1. Introduction
Over the last years, generative programming and aspect-oriented software development have been proposed aiming at increasing maintainability and reusability of software systems. While several research works have focused on the investigation of the individual use of each of these software engineering approaches, less attention has been paid to the integration of these two techniques. Generative Programming (GP) [8] has been proposed recently as an approach based on domain engineering [21, 27, 28]. It addresses the study and definition of methods and tools to enable the automatic production of software from a high-level specification. GP promotes the separation of problem and solution spaces, giving flexibility to evolve both independently. Problem space models concepts and features existent in a specific domain. Solution space consists of the components that are used to build particular software systems. Code generators represent the configuration knowledge in a generative model. They define how specific feature combinations in the problem space are mapped to a set of software components in the solution space.
Aspect-Oriented Software Development (AOSD) [23, 33] is an evolving approach to modularize crosscutting concerns that existing paradigms (e.g.: object-oriented) are not able to capture explicitly. Crosscutting concerns are concerns that often crosscut several modules in a software system. AOSD encourages modular descriptions of complex software by providing support for cleanly separating the basic system functionality from its crosscutting concerns. Aspect is the abstraction used to modularize the crosscutting concerns.
The use of aspect-oriented techniques in the definition of a generative approach can bring additional benefits for the development of system families, such as: (i) clear separation of orthogonal and crosscutting features in the problem and solution space; and (ii) direct mapping of crosscutting features in aspects. Despite these advantages, we believe that the integration of GP and AOS D techniques is not a trivial task. Interesting questions arise and need to be considered when
developing an aspect-oriented generative approach, including: How to model crosscutting features in the problem space? How to design aspect-oriented architectures that address the crosscuting and non-crosscutting features modeled? Which technologies (domain-specific languages, frameworks) are appropriate to implement these aspect-oriented generative approaches?
Recent work explored the use of GP and AOS D together [18,26,31]. However, these reports neither cover nor describe in detail the typical phases (domain analysis, domain design and domain implementation) found in the definition of a generative approach.
In this context, this paper describes systematically how we have developed an aspect-oriented generative approach to the context of families of multi-agent systems. Following the guidelines presented by Czarnecki and Eisenecker [8], we have organized the development of the generative approach into three phases: (i) domain analysis; (ii) domain design; and (iii) domain implementation. The use of aspect-oriented technologies required the adaptation of modeling notations used in domain analysis and design, such as: (i) the extension of feature models to represent crosscutting features; and (ii) the extension of a current aspect-oriented modeling notation [6] to represent aspect-oriented architectures. In the domain implementation, we illustrate the use of different mainstream technologies to implement the central components of a generative approach, such as: (i) XML-S chema [34] to specify domain-specific languages; (ii) Java and AspectJ [9] programming languages to implement the agent architecture and components; and (iii) Eclipse technologies [11, 30] to build the code generator.
The remainder of this paper is organized as follows. S ection 2 introduces the basic concepts of generative programming and aspect-oriented software development. Section 3 presents an overview of our aspect-oriented generative approach and details the process of domain analysis and design. Section 4 describes the steps to implement the generative approach. Section 5 synthesizes some of the lessons learned during the definition of the aspect-oriented generative approach. S ection 6 discusses some related work. Finally, section 7 provides some conclusions and directions for future work.
2. Background
2.1 Generative Programming
Generative Programming (GP) [8] addresses the study and definition of methods and tools that enable the automatic generation of software from a given high-level specification language. It has been proposed as an approach based on domain engineering [21, 27, 28].
GP promotes the separation of problem and solution spaces, giving flexibility to evolve both independently. To provide this separation, Czarnecki and Eisenecker [8] propose the concept of a generative domain model. A generative domain model is composed of three basic elements: (i) problem space – which represents the concepts and features existent in a specific domain; (ii) solution space – which consists of the software architecture and components used to build members of a software family; and (iii) configuration knowledge – which defines how specific feature combinations in the problem space are mapped to a set of software components in the solution space. GP advocates the implementation of the configuration knowledge by means of code generators.
The fact that GP is based on domain engineering enables us to use domain engineering methods [1, 8] in the definition of a generative domain model. Common activities encountered in domain engineering methods are: (i)domain analysis – which is concerned with the definition of a domain
for a specific software family and the identification of common and variable features within this domain; (ii) domain design – which concentrates on the definition of a common architecture and components for this domain; and (iii) domain implementation – which involves the implementation of architecture and components previously specified during domain design.
According to Czarnecki and Eisenecker, two new activities need to be introduced to domain engineering methods in order to address the goals of GP:
?development of a proper means to specify specific members of the software family. Domain-specific languages (DSLs) must be developed to deal with this requirement;
?modeling of the configuration knowledge in detail in order to automate it by means of a code generator.
In this work, we have adopted the common activities – domain analysis, domain design and domain implementation – encountered in a domain engineering method to define the generative approach (such as described in [8]). However, we have also considered the other two activities presented above by implementing a domain-specific language and a code generator.
2.2 Aspect-Oriented Software Development
Aspect-oriented software development (AOS D) [23,33] is an evolving approach aiming at modularizing concerns, which existing paradigms are not able to capture explicitly. It encourages modular descriptions of complex software by providing support for cleanly separating the basic system functionality from its crosscutting concerns. Crosscutting concerns are concerns that often crosscut several modules in a software system.
AOS D has been proposed as a technique for improving the separation of concerns in the construction of OO software, supporting improved reusability and ease of evolution. When developing OO software one faces an architectural dilemma: no matter how the OO system is factored, frequently there will be concerns that are handled in different classes. Hence, such concerns crosscut these classes. AOS D supports the modularization of crosscutting concerns by providing abstractions to extract these concerns and later compose them back when producing the overall system.
AOS D proposes the notion of aspect as a new abstraction and provides new mechanisms for composing aspects and components(classes, methods, etc.) together at specific join points. AspectJ [22] is an aspect-oriented extension to the Java programming language.The aspect abstraction in AspectJ is composed of inter-type declarations,pointcuts and advices.Pointcuts have a name and are collections of join points. Join points are well-defined points in the dynamic execution of system components. Examples of join points are method calls and method executions. Advice is a special method-like construct attached to pointcuts. Advices are dynamic crosscutting features since they affect the dynamic behavior of components. Inter-type declarations specify new attributes or methods to be introduced in specific classes.
As already mentioned, in this work we will focus on aspect-oriented abstractions to capture crosscutting concerns encountered in multi-agent system implementations. Examples of such concerns are interaction, autonomy, adaptation and collaboration [17].
3. An Aspect-Oriented Generative Approach
The aspect-oriented (AO) generative approach aims at exploring the horizontal domain [8]of multi-agent systems (MAS s)to improve their quality and productivity. The purpose of the generative approach is threefold: (i) to uniformly support crosscutting and orthogonal (non-crosscutting) features
of software agents starting at early development stages [9,29]; (ii) to abstract the common and variable features; and (iii) to enable the code generation of AO agent architectures.
Figure 1 depicts our generative approach that is composed of:
(i) a domain-specific language (DSL), called Agent-DSL, used to collect and model orthogonal and crosscutting features of software agents;
(ii) an AO architecture modeling a family of software agents. It is centered on the definition of aspectual components to modularize the crosscutting agent features;
(iii) a code generator that maps abstractions of the Agent-DS L to specific compositions of
steps followed in the development of the generative approach were:
1.Domain Analysis
a.Definition of the domain
b.Identification and modeling of common and variable features of the domain
c.Identification and modeling of the crosscuting features of the domain
2.Domain Design
a.Specification of the generic AO architecture
b.Identification and specification of the DSLs
c.Specification of the configuration knowledge
3.Domain Implementation
a.Implementation of the DSLs
b.Implementation of the AO architecture and additional components
c.Implementation of the code generator
The following sections describe in more detail most of these steps. Section 3.1 describes the domain analysis phase by presenting the resulted feature model and the proposed notation to represent crosscutting features in a feature model. S ection 3.2 presents the AO agent architecture and the proposed notation to represent aspectual and non-aspectual components. Section 4 describes the steps to implement the elements of the generative approach.
AO framework. Because of this decision, the step 2(b) that involves the identification and specification of the DSLs was simplified. It was necessary a definition of a sole configuration DSL used to instantiate the AO framework. Section 4.1 presents the specification and implementation of this DSL.
Due to limited space the step 2(c) of the domain design is not described in this paper. The specification of the configuration knowledge was accomplished in our work by defining a pattern language [12]. A pattern language defines how a set of interrelated design patterns can be used together to address a larger problem. Our pattern language shows how the domain features of MASs can be mapped to specific design structures of classes and aspects. A complete description of this pattern language can be found in [13].
3.1 Domain Analysis
During the domain analysis, recurring agent concerns of multi-agent systems (MASs) were modeled using feature models [21]. Feature models are used to represent common and variable features of system families. Our domain analysis was supported by experience gained from our extensive previous work on the development of several multi-agent systems [13-17], and by surveys of different MAS modeling languages, architectures and platforms [17, 32]. We captured the different features associated with the agent concept, including orthogonal and crosscutting agent features.Figure 2 depicts a partial feature model produced during this phase.
The agent concept is composed of its knowledge and its basic properties, which we termed “agenthood ”. The knowledge feature encompasses beliefs ,goals and plans . Agent beliefs describe information about the agent itself and about the external environment with which the agent interacts.To achieve a goal, an agent executes a specific plan. During the execution of a plan, the agent manipulates its beliefs. The agenthood feature is composed of three subfeatures:interaction ,adaptation and autonomy .
Knowledge
Belief Plan PlanAdaptation Goal Message ExecutionAutonomy Interaction alternative features Sensory crosscuts
DecisionGoal
The interaction feature is the agent capacity to communicate with the environment. The agent can receive or send messages to the environment by means of its sensors and effectors , respectively.External messages are translated to the agent ontology using specific parsers in its sensors. Effector parsers translate internal messages to a specific external representation.
The adaptation feature is formed by belief adaptation and plan adaptation . Belief adaptation is responsible for interpreting received messages from the environment and for manipulating its beliefs based on the message contexts. Plan adaptation determines the plan the agent must execute whenever a new goal needs to be achieved.The purpose of the autonomy feature is to instantiate and manage the agent goals. It deals with three types of goals: reactive goals ,proactive goals , and decision goals . Reactive goals are instantiated when the agent receives an external request from other agents or environment components. Proactive goals are instantiated due to internal events that occurs, such as, the end of a plan execution or the achievement of a specific agent state. Finally, the decision goals are instantiated due to external or internal events and are used to decide if special reactive or proactive goals could be instantiated. The autonomy property is also responsible for monitoring the adopted concurrency strategy . It supports the goal achievement by implementing a mechanism for executing concurrently agent plans.In addition to the agent knowledge and the agenthood features, an agent can incorporate additional properties.Additional features include collaboration ,mobility , and learning . The current version of the generative approach just provides support for the collaboration feature. An agent collaborates with other agents by playing different roles. A role gives to the agent extra capacities of knowledge,interaction, adaptation and autonomy. Each agent can play different roles during its execution.
To support the representation of crosscutting features in feature models, a new kind of relation between features, called crosscuts relation, has been introduced. We say that a feature A crosscuts a feature B, when either A or one of its subfeatures depends and inspects B or one of the subfeatures of B. In the feature model of the Figure 2, for instance, Adaptation is characterized as a crosscutting feature because it is composed of two features (BeliefAdaptation and PlanAdaptation ) that inspect common features of the Agent Knowledge (Goal and Plan ) and the Agent Interaction (Message ). As a result, the Adaptation feature crosscuts the Knowledge and Interaction features.
The Interaction feature is also characterized as crosscutting because it is composed of a subfeature (MessageSending ) that inspects features of the Agent K nowledge (Plan ). In addition, the Autonomy feature crosscuts the K nowledge and Interaction features.
3.2 Domain Design
Domain design consists of specifying a generic and flexible AO agent architecture for the domain at hand. Each feature modeled during domain analysis needs to be considered in the design. The AO agent architecture is a refinement of a previous work [16,17]. It uses two kinds of components: (i) a central component that modularizes the orthogonal features associated with the agent knowledge;and (ii) the aspectual components that separate the crosscutting agent features from each other and from the Knowledge component. Aspectual components represent crosscutting features at the architectural level.
Figure 3 depicts the components of the AO agent architecture. We have used a new notation to graphically represent an AO architecture. It is an extension of the ASideML modeling language [6].We developed this notation to enable the representation of aspectual components. An aspectual component may crosscut other aspectual or non-aspectual components using its crosscutting interfaces. A crosscutting interface may both add new state or behavior in other components and intercept (and modify) the existent behavior of components. Non-aspectual (normal) components are represented in a similar way to UML [3] and offer their services through the normal interfaces .knowledge feature. It contains two normal interfaces: (i)IKnowledgeUpdating – to update the agent knowledge; and (ii) IServices – to offer agent services. In the domain implementation (section 4.2), this component is refined as a set of classes.Each of the crosscutting agent features (interaction, adaptation, autonomy and role) are modeled as aspectual components in the agent architecture. Each aspectual component was refined during the domain implementation (section 4.2) as a set of aspects and auxiliary classes, which are also part of the crosscutting feature.
The Interaction aspectual component models the interaction crosscutting feature. It is composed of two crosscutting interfaces: (i)IMessageReception – which introduces the capacity to receive external messages into the Knowledge component; and (ii)IMessageSending – which crosscuts elements of the Knowledge component to define specific points where is necessary to send messages to the environment. It also crosscuts elements of the Collaboration aspectual component to specify specific points in collaboration plans where is also necessary to send messages to the environment.
The Adaptation aspectual component models the adaptation crosscutting feature. It is composed of two crosscutting interfaces: (i)IBeliefAdaptation – which intercepts the invocation of services provided by the IMessageReception interface of the Interaction component to
Reception
Creation
IExecution IExtrinsic
Knowledge
update agent beliefs when new external messages are received by the agent; and (ii) IPlanAdaptation – which intercepts the invocation of services provided by the IKnowledgeUpdating interface of the Knowledge component to instantiate new plans to be executed when the agent needs to achieve a specific goal.
Finally, the Collaboration aspectual component models the role crosscutting feature. It is composed of two crosscutting interfaces: (i)IExtrinsicKnowledge – which introduces new knowledge (state and behavior) associated with agent roles in the Knowledge component; and (ii) IRoleBinding – which defines specific points in the Knowledge component where agent roles are instantiated and bound to the agents.
4. Implementing the Generative Approach
This section describes the implementation of the generative approach elements: (i) the Agent-DSL, (ii) the AO agent architecture, and (iii) the code generator.
4.1 Agent-DSL
Based on the feature models defined in the domain analysis (section 3.1), we defined a configuration domain-specific language (DS L), called Agent-DS L. A configuration DS L allows to specify a concrete instance of a concept [8]. It can be directly derived from feature models. This language is used to specify the agent features that an agent instance could have to accomplish its tasks. It allows modeling the agent features, such as, knowledge, interaction, adaptation, autonomy and collaboration.
An XML Schema [34] was used to specify the semantics of the Agent-DSL. The feature models were translated to XML Schema complex types. For each specific agent of a MAS to be generated, it must be created an agent description XML document. This document must conform to the XML Schema that defines the Agent-DSL. The right side of Figure 5 depicts a partial specification of an agent type used in a case study developed by our research group [13]. Subsection 4.3 describes in more detail the case study.
4.2 The Aspect-Oriented Agent Architecture
The implementation of the generic AO agent architecture (section 3.2) was realized using Java and AspectJ [22] programming languages. The basis of the architecture implementation is an AO framework that contains hot-spots as classes and aspects [24]. Figure 4presents a partial description of the AO framework. The ASideML modeling language [6] is used to represent visually the framework.This language extends UML with notations for representing aspects. The notations provide a detailed description of the aspect elements. In this modeling language, an aspect is represented by a diamond; it is composed of internal structure and crosscutting interfaces. The internal structure declares the internal attributes and methods. A crosscutting interface specifies when and how the aspect affects one or more classes [6]. Each crosscutting interface is composed of inter-type declarations, pointcuts and advices. The first part of a crosscutting interface represents inter-type declarations, and the second part represents pointcuts and their attached advices. The notation uses a dashed arrow to represent the crosscutting relationship, which relates one aspect to classes and/or aspects.Every class and aspect presented in the figure are hot-spots.
The Knowledge component (section 3.2) was refined as a set of classes – Agent,Belief,Goal and Plan classes. Each one of them represents a specific hot-spot that can be extended to define an
agent type. Agent beliefs are defined in our architecture as domain classes that Agent instances can
aggregate.Each one of the aspectual components (section 3.2) was refined as a central aspect and a
set of auxiliary classes. Figure 4 only presents the main aspects that refine the agent knowledge
classes incorporating specific agent features.
The Interaction component is defined as an abstract aspect that introduces interaction capabilities
(inbox, outbox, sensors, effectors, parsers) in the Agent class. It also intercepts domain classes and
sensors in the agent environment to enable the message reception by means of AspectJ pointcuts and
advices. Finally, the Interaction aspect defines two abstract pointcuts and some abstract
methods. The abstract pointcuts are used to define specific points in role aspects and plan classes
where internal messages must be sent. The abstract methods are specialized to create and initialize
specific sensors and effectors. The Interaction subaspects define the concrete configuration of
the Interaction aspect by implementing the abstract pointcuts and methods. It is possible to
specify a different Interaction subaspect for each one of the agent types or roles defined in a
MAS.
The Adaptation component defines the Adaptation abstract aspect, which enables the Agent
class to adapt its beliefs and plans. The belief adaptation of the Adaptation aspect is defined by
intercepting the receiveMsg() method of the Agent class (introduced by the Interaction
aspect). After that, specific advices and methods are responsible for updating beliefs based on
external messages received by the agent. The plan adaptation, defined in the Adaptation aspect,
intercepts the setGoal() method of the Agent class and the erroneous execution of the execute() method of the Plan subclasses. The purpose is to determine new agent plans to be executed by the agent to reach a specific goal. The Adaptation abstract aspect also offers abstract
methods to be defined by subaspects. These subaspects allow defining specific belief and plan
adaptation for each one of the agent types or roles in a open MASs.
The Autonomy component defines the Autonomy aspect, which enables the Agent class to
instantiate and manage reactive goals and execute concurrently several plans (execution autonomy).
However, for sophisticated agent types, the Autonomy aspect also allows to define proactive and
decision autonomy. To instantiate reactive goals, the Autonomy aspect also intercepts the receiveMsg() method of the Agent class. This interception is used to verify if specific external events (for instance, a request of another agent) demand the instantiation of reactive goals. The execution autonomy is implemented in the Autonomy aspect by defining an Active Object [24], which monitors the list of plans to perform of the Agent class to execute them in separate threads. The proactive autonomy is implemented by specifying: (i) several pointcuts in agent knowledge classes that represent specific events of interest, and (ii) an advice associated with these pointcuts which is responsible for determining if a proactive goal must be instantiated in the occurrence of any of these events. Finally, the decision autonomy only defines a mak eDecision() method in the Autonomy aspect that is invoked in the advices associated with the pointcuts of reactive and proactive goal instantiation. This method verifies whether it is necessary to execute a decision plan on the occurrence of a specific event or on the reception of a message. Autonomy subaspects can also be implemented to define specialized proactive, reactive and decision autonomy for each one of the agent types and roles defined in a MAS.
The Collaboration component is implemented by defining role aspects that introduce attributes and
methods in an agent type (Agent class or subclass). These elements define respectively specific
beliefs and behaviors of roles. Also, specific Plan and Goal subclasses must be defined for the
roles. The plans defined for a role manipulate the attributes (beliefs) and invoke methods (behaviors)
introduced by the role aspect. Goal classes specified for a role are instantiated by an Autonomy
subaspect which is specially created for the role. S pecific interaction, adaptation and autonomy subaspects can be defined for an agent role. Next section exemplifies the definition of subaspects for agent roles of a specific case study developed by our research group.
Besides the framework, some components were created to implement specific functionalities associated with the agenthood features, such as:
?interaction feature: concrete sensors and effectors specially tailored to specific agent platforms (such as JADE [2]);
?autonomy feature: concrete concurrency strategies (such as thread pool and a thread per request) used by the active object to implement the agent’s execution autonomy.
interface>>
4.3 Code Generator
In the configuration knowledge of the generative approach, we implemented a code generator as an Eclipse plug-in [30]. This generator maps abstractions in the Agent-DSL to normal and aspectual components of the agent architecture. The AO framework (section 4.2) is used as the basis of the agent architecture. The main task of the generator is to instantiate the framework, creating subclasses and subaspects for specific hot-spots of the framework. Depending on the agent descriptions provided, new types of agents (or roles) with their respective agent properties can be generated. We present below examples of classes and aspects generated for the context of a case study.
We have used the generative approach for the development of the ExpertCommittee (EC) system, which is a case study undertaken by our research group [13]. EC is an open system that supports the management of paper submissions and the reviewing process for a conference. Software agents have been introduced to EC in order to assist its users with time-consuming activities and automate repetitive user tasks. EC agents are software assistants that represent paper authors, chairs, PC members and reviewers and coordinate their activities. The EC system also includes information agents.
Figure 5 presents the elements of the generative approach applied to the EC system. The left side of the figure contains an agent description file for a specific agent type of the EC, called
18o Simpósio Brasileiro de Engenharia de Software ResearcherUserAgent. The chair role played by this agent type is also presented. We used the JAXB plug-in [20] to enable reading the agent description XML file by the code generator.
The center of the figure is the code generator. It is responsible for reading the agent description file
and customizing code templates based on information collected by the Agent-DSL. Code templates
allow us to represent structure and behavior of specific classes and aspects that we want to generate.
They are used to represent each one of subclasses and subaspects of the framework hot-spots. Java
Emitter Templates (JET), a generic template engine of the Eclipse Modeling Framework (EMF) [4],
has been used to write the source templates. Examples of classes and aspects that we wrote as
templates are: (i) concrete instances of hot-spots (classes or aspects), such as specific agent type
classes, specific agenthood (interaction, adaptation and autonomy) subaspects; (ii) specific agent
plans and goals classes; and (iii) specific role aspects.
Finally, the right side of the figure shows the specific elements (subclasses and subaspects) generated
for the EC system. Several classes and aspects are generated based on its Agent-DSL description
file and on the JET source templates. First, the ResearchUserAgent class, a specific agent type, is
generated. The two roles played by instances of this class are also generated. They are called Chair
and Reviewer aspects. Each one of them introduces specific beliefs and behaviors in the ResearchUserAgent class. Specific Plan and Goal classes are also generated to the two roles. Moreover, different Interaction,Adaptation and Autonomy subaspects are generated to each
one of the roles. For instance, the ChairInteraction,ChairAdaptation and ChairAutonomy
aspects are produced to agents playing the chair role. ChairInteraction initializes JADE sensors
and effectors to be used by the agents playing the chair role. ChairAdaptation realizes specific
belief and plan adaptation of the chair role. Finally, ChairAutonomy defines: (i) a reactive autonomy
– to instantiate specific goals when receiving external messages from reviewer agents; (ii) a proactive
autonomy – to instantiate specific goals when internal events occur; and (iii) an execution autonomy –
which defines a “thread per request” concurrency strategy to execute agent plans.
5. Discussion and Lessons Learned
Based on the experience of development of an AO generative approach, we have already identified
some important requirements and techniques that are useful and relevant during the integration of GP
and AOSD technologies. Below, we synthesize these lessons learned.
?support to crosscutting features in the domain analysis – the modeling of crosscutting concerns in early design phases has been recognized recently as an important topic of research in AOSD [9, 29]. The extension of feature models to represent crosscutting features, presented in this paper (section 3.1), helps to become explicit the existence of crosscutting concerns in system families during domain analysis. More research need to be developed to understand better how to model crosscutting features and their interactions;
?specification of aspect-oriented architectures – a fundamental activity when constructing program families (and product lines) is the modeling of a software architecture that addresses common and variable features.We have presented in this paper (section 3.2) a new notation that allows representing aspectual components.The use of this notation enables us to represent in a concise way the main components (and their interactions) of AO architectures. The definition of principles and patterns to model AO architectures so that it can be possible to address different crosscutting concerns is an important topic of research that we intend to explore;
? "agent-dsl.xsd"> SERVICE_DISTRIBUTE_PAPERS ThreadPool PaperDistributionGoal ... ...
Role Aspect
Code
Autonomy
Subaspect Code
Figure 5. Problem Space | Configuration Knowledge | Solution Space
(Agent-DSL) (Code Generator) (Agent Architecture Generated)
?specification of the configuration knowledge – the configuration knowledge in a generative domain model (section 2.1) defines how specific combinations of features in the problem space can be mapped to specific combinations of components in the solution space. The configuration knowledge was specified in our work by defining a pattern language [13]. A pattern language defines how a set of interrelated design patterns can be used together to address a larger problem. Each one of the components of the AO architecture was specified as a design pattern of the pattern language. The description of each pattern emphasizes: (i) a specific problem in the context of agent architectures; and (ii) a flexible design structure to address that problem;
?construction of domain-specific languages – during the implementation of our generative approach, we have defined a unique configuration domain-specific language to express orthogonal and crosscutting features of software agents (section 4.1). Configuration DSLs are recognized as a suitable alternative to define generative approaches that require to instantiate object-oriented frameworks [5, 11]. In our case, it was also suitable to represent the crosscutting features encountered in a definition of a software agent. An interesting work is the investigation of the combined use of a configuration DSL to express only the orthogonal features and aspectual DS Ls to express each one of the crosscutting features (see related work in section 6) existent in a domain;
?implementation of aspect-oriented frameworks – object-oriented frameworks are a common and useful technology to implement architectures for system families [10]. They address the implementation of common (frozen-spots) and variable (hot-spots) features of system families. The use of the aspect abstraction in the definition of frameworks enables us to define common and variable behaviors of crosscutting features. An AO framework that models a set of crosscutting features encountered in agent architectures has been presented in this work (section 4.2). We believe that AO frameworks are a fundamental technology to be used during the implementation of AO generative approaches. In the implementation of our framework it was used some of the AspectJ idioms presented in [19] (such as, Abstract Pointcut,Chained Advice,Pointcut Method,Template Advice). We found that they represent basic and recurrent constructions used to define AO frameworks in AspectJ.
6. Related Work
Some recent reports explored the integration of GP and AOSD [18, 26, 31]. However, these reports have not covered or described in sufficient detail all the typical phases encountered while developing a generative approach.
Pinto et al [26] have proposed DAOP-ADL, an architecture description language used to describe software architectures. This language supports the concepts of components and aspects. DAOP-ADL is interpreted by DAOP (Dynamic Aspect-Oriented Platform), a specific component and aspect-based middleware platform [27]. DAOP platform uses the information presented in the ADL to compose dynamically components and aspects of a application. DAOP-ADL enables the specification of AO architectures independent of programming languages and component platforms. The notation (section 3.2) proposed in this paper can also be formalized as an ADL.
S honle et al [31] have developed XAspects, an extensible system that allows to define aspectual domain-specific languages. An aspectual DS L allows to express specific crosscutting concerns into modularized constructs [8].Examples of aspectual DSLs presented
by them are [31]: (i) a coordination language used to specify thread coordination concerns; and (ii) a traversal language used to express collaborative behavior between classesXAspects also provides support to generate Java and AspectJ code derived from one or more aspectual DSLs. In our work we have studied the domain of software agents to define a unique DSL that express orthogonal and crosscutting agent features.
Colyer et al [7] have presented some principles that guide the definition of flexible and configurable AO systems. They show the proper use of AOSD technologies to follow these principles. They also illustrate how the application of the principles can help in the configuration of different features in a product line. The work presented by these authors is an important step in the definition of guidelines for constructing program families in order to maximize configurability in AO architectures. This kind of principle is very useful to guide the specification of AO architectures that can be configured with different feature combinations in
a generative approach.
7. Conclusion and Future Work
This paper reported our experience in the definition of an AO generative approach. The goal of this approach is to explore the horizontal domain that MAS s represent in order to enable the code generation of agent architectures. We organized the development of the generative approach using typical phases encountered in domain engineering processes. During the development process of the generative approach, it was necessary to adapt modeling notations used in generative programming due to the adoption of AOSD. The feature model was extended to support the representation of crosscutting features (section 3.1). Also, a new notation was proposed to support the representation of AO architectures (section 3.2). Aspectual components have been used to model crosscutting features from the architectural point of view.
We believe that the definition of AO generative approaches can bring important benefits to the development of software families. GP allows: (i) to evolve the problem and solution spaces independently; and (ii) to define clearly the mapping between high-level features and implementation components. The integrated use of GP and AOSD techniques brings additional benefits, such as: (i) clear separation of orthogonal and crosscutting features starting at early design phases; and (ii) direct mapping of crosscutting features in aspectual components. This latter benefit simplifies the implementation of code generators, because the composition of crosscutting concerns is accomplished by the aspect weavers. Using only OO abstractions, crosscutting agent features need to be hand-coded in the code of classes.
This work aimed at identifying relevant techniques and requirements to be considered on the development of AO generative approaches. It represents a significant step in the definition of a method to develop AO generative approaches. In this context, our future work consists of the: (i) application of the same process presented in this paper to develop an AO generative approach for a different software domain; (ii) investigation of the benefits and drawbacks of the use of aspectual domain-specific languages; and (iii) definition of a set of principles and guidelines to specify artifacts in a generative domain model considering the use of AOS D technologies using the notations presented.
Acknowledgments.This work has been partially supported by CNPq under grant No. 140252/2003-7 for UiráKulesza, grant No. 141457/2000-7 for Alessandro Garcia, and by
FAPERJ under grant No. E-26/150.699/2002 for Alessandro. The authors are also supported by the PRONEX Project under grant 7697102900, and by ESSMA under grant 552068/2002-0 and by the art. 1st of Decree number 3.800, of 04.20.2001.
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脐带间充质干细胞的研究进展 间充质干细胞（mesenchymal stem cells,MSC S ）是来源于发育早期中胚层 的一类多能干细胞[1-5]，MSC S 由于它的自我更新和多项分化潜能，而具有巨大的 治疗价值 ,日益受到关注。MSC S 有以下特点：(1)多向分化潜能，在适当的诱导条件下可分化为肌细胞[2]、成骨细胞[3、4]、脂肪细胞、神经细胞[9]、肝细胞[6]、心肌细胞[10]和表皮细胞[11, 12]；(2)通过分泌可溶性因子和转分化促进创面愈合；(3) 免疫调控功能，骨髓源（bone marrow ）MSC S 表达MHC-I类分子，不表达MHC-II 类分子，不表达CD80、CD86、CD40等协同刺激分子，体外抑制混合淋巴细胞反应，体内诱导免疫耐受[11, 15]，在预防和治疗移植物抗宿主病、诱导器官移植免疫耐受等领域有较好的应用前景；(4)连续传代培养和冷冻保存后仍具有多向分化潜能，可作为理想的种子细胞用于组织工程和细胞替代治疗。1974年Friedenstein [16] 首先证明了骨髓中存在MSC S ，以后的研究证明MSC S 不仅存在于骨髓中，也存在 于其他一些组织与器官的间质中：如外周血[17]，脐血[5]，松质骨[1, 18]，脂肪组织[1]，滑膜[18]和脐带。在所有这些来源中，脐血(umbilical cord blood)和脐带(umbilical cord)是MSC S 最理想的来源，因为它们可以通过非侵入性手段容易获 得，并且病毒污染的风险低，还可冷冻保存后行自体移植。然而，脐血MSC的培养成功率不高[19, 23-24]，Shetty 的研究认为只有6%，而脐带MSC的培养成功率可 达100%[25]。另外从脐血中分离MSC S ，就浪费了其中的造血干/祖细胞(hematopoietic stem cells/hematopoietic progenitor cells,HSCs/HPCs) [26, 27]，因此，脐带MSC S (umbilical cord mesenchymal stem cells, UC-MSC S )就成 为重要来源。 一．概述 人脐带约40 g, 它的长度约60–65 cm, 足月脐带的平均直径约1.5 cm[28, 29]。脐带被覆着鳞状上皮，叫脐带上皮，是单层或复层结构，这层上皮由羊膜延续过来[30, 31]。脐带的内部是两根动脉和一根静脉，血管之间是粘液样的结缔组织，叫做沃顿胶质，充当血管外膜的功能。脐带中无毛细血管和淋巴系统。沃顿胶质的网状系统是糖蛋白微纤维和胶原纤维。沃顿胶质中最多的葡萄糖胺聚糖是透明质酸，它是包绕在成纤维样细胞和胶原纤维周围的并维持脐带形状的水合凝胶，使脐带免受挤压。沃顿胶质的基质细胞是成纤维样细胞[32]，这种中间丝蛋白表达于间充质来源的细胞如成纤维细胞的，而不表达于平滑肌细胞。共表达波形蛋白和索蛋白提示这些细胞本质上肌纤维母细胞。 脐带基质细胞也是一种具有多能干细胞特点的细胞，具有多项分化潜能，其 形态和生物学特点与骨髓源性MSC S 相似[5, 20, 21, 38, 46]，但脐带MSC S 更原始，是介 于成体干细胞和胚胎干细胞之间的一种干细胞，表达Oct-4, Sox-2和Nanog等多
精神分裂症的病因及发病机理 精神分裂症病因：尚未明，近百年来的研究结果也仅发现一些可能的致病因素。（一）生物学因素1．遗传遗传因素是精神分裂症最可能的一种素质因素。国内家系调查资料表明：精神分裂症患者亲属中的患病率比一般居民高6.2倍，血缘关系愈近，患病率也愈高。双生子研究表明：遗传信息几乎相同的单卵双生子的同病率远较遗传信息不完全相同 的双卵双生子为高，综合近年来11项研究资料：单卵双生子同病率（56.7%），是双卵双生子同病率（12.7%）的4.5倍，是一般人口患难与共病率的35-60倍。说明遗传因素在本病发生中具有重要作用，寄养子研究也证明遗传因素是本症发病的主要因素，而环境因素的重要性较小。以往的研究证明疾病并不按类型进行遗传，目前认为多基因遗传方式的可能性最大，也有人认为是常染色体单基因遗传或多源性遗传。Shields发现病情愈轻，病因愈复杂，愈属多源性遗传。高发家系的前瞻性研究与分子遗传的研究相结合，可能阐明一些问题。国内有报道用人类原癌基因Ha-ras-1为探针，对精神病患者基因组进行限止性片段长度多态性的分析，结果提示11号染色体上可能存在着精神分裂症与双相情感性精神病有关的DNA序列。2．性格特征：约40%患者的病前性格具有孤僻、冷淡、敏感、多疑、富于幻想等特征，即内向
型性格。3．其它：精神分裂症发病与年龄有一定关系，多发生于青壮年，约1/2患者于20～30岁发病。发病年龄与临床类型有关，偏执型发病较晚，有资料提示偏执型平均发病年龄为35岁，其它型为23岁。80年代国内12地区调查资料：女性总患病率（7.07%。）与时点患病率（5.91%。）明显高于男性（4.33%。与3.68%。）。Kretschmer在描述性格与精神分裂症关系时指出：61%患者为瘦长型和运动家型，12.8%为肥胖型，11.3%发育不良型。在躯体疾病或分娩之后发生精神分裂症是很常见的现象，可能是心理性生理性应激的非特异性影响。部分患者在脑外伤后或感染性疾病后发病；有报告在精神分裂症患者的脑脊液中发现病毒性物质；月经期内病情加重等躯体因素都可能是诱发因素，但在精神分裂症发病机理中的价值有待进一步证实。（二）心理社会因素1．环境因素①家庭中父母的性格，言行、举止和教育方式（如放纵、溺爱、过严）等都会影响子女的心身健康或导致个性偏离常态。②家庭成员间的关系及其精神交流的紊乱。③生活不安定、居住拥挤、职业不固定、人际关系不良、噪音干扰、环境污染等均对发病有一定作用。农村精神分裂症发病率明显低于城市。2．心理因素一般认为生活事件可发诱发精神分裂症。诸如失学、失恋、学习紧张、家庭纠纷、夫妻不和、意处事故等均对发病有一定影响，但这些事件的性质均无特殊性。因此，心理因素也仅属诱发因
全国翻译价格 关于全国各地区翻译价格我们根据客户的不同需求和具体情况，提供多种等级和特色的翻译服务，供客户选择：（注：以下报价均为参考价格，精确报价将根据稿件内容的难度、技术处理的复杂程度和时限要求的缓急而定。
品质控制 坚持高端定位是外语通翻译的核心要素，追求高品质翻译需要译员具备深厚的语言功底和专业背景知 识，更需要严格的质量控制体系来管理这一过程： 外语通六阶梯质量控制体系 第一阶梯：译文评估承接 分析稿件性质、用途要求、商务背景、专业术语、数量和交稿时间等，确定是否有100%的把握承接， 否则坚决放弃，以免因质量或交稿时间耽误客户和影响品牌形象。 第二阶梯：专业译员翻译 专业背景的译员只专注于一个行业领域的精准翻译，项目经理根据译文评估，从外语通全球译员库中 分析挑选多名此行业的专业译员成立项目组，统一专业术语和标准，协同翻译。 第三阶梯：翻译质量监控 项目经理监控翻译进展，每日集中疑难词汇，请签约专家释疑。每日抽查译文质量，及时解决译文质 量问题。 第四阶梯：译文校对排版 汇总所有译文，查错补漏，进一步统一术语，按原文进行排版，形成完整初稿。 第五阶梯：专家译审修改 专家译审对翻译初稿进行翻译准确性审核，确保译稿忠于原文，专业词汇纯正地道。 六阶梯：外籍母语润色第 在华外籍翻译（外译中稿件由中文功底深厚的编辑）对译稿的语法、词汇进行修正和润色，确保译稿 纯正、地道，达到母语品质。 外语通翻译严格执行《ISO译文质量体系》，《翻译质量国家标准GB/T 19682-2005》： 译文质量标准Ⅲ类通用笔译Ⅱ类专业笔译Ⅰ类高级笔译译文用途内容概要、参考资料一般文件和材料正式文件、法律文书、出版物错漏译率小于5‰小于2‰0‰ 译员经验3年以上5年以上8年以上 译员学历硕士以上硕士以上硕士以上 行业背景常识业内资深 海外背景无/短期中期长期 译文校对有有有 专家译审无有有 母语润色无无有 译文排版简单排版详细排版出版级别
脐带血造血干细胞库管理办法（试行） 第一章总则 第一条为合理利用我国脐带血造血干细胞资源，促进脐带血造血干细胞移植高新技术的发展，确保脐带血 造血干细胞应用的安全性和有效性，特制定本管理办法。 第二条脐带血造血干细胞库是指以人体造血干细胞移植为目的，具有采集、处理、保存和提供造血干细胞 的能力，并具有相当研究实力的特殊血站。 任何单位和个人不得以营利为目的进行脐带血采供活动。 第三条本办法所指脐带血为与孕妇和新生儿血容量和血循环无关的，由新生儿脐带扎断后的远端所采集的 胎盘血。 第四条对脐带血造血干细胞库实行全国统一规划，统一布局，统一标准，统一规范和统一管理制度。 第二章设置审批 第五条国务院卫生行政部门根据我国人口分布、卫生资源、临床造血干细胞移植需要等实际情况，制订我 国脐带血造血干细胞库设置的总体布局和发展规划。 第六条脐带血造血干细胞库的设置必须经国务院卫生行政部门批准。 第七条国务院卫生行政部门成立由有关方面专家组成的脐带血造血干细胞库专家委员会（以下简称专家委
员会），负责对脐带血造血干细胞库设置的申请、验收和考评提出论证意见。专家委员会负责制订脐带血 造血干细胞库建设、操作、运行等技术标准。 第八条脐带血造血干细胞库设置的申请者除符合国家规划和布局要求，具备设置一般血站基本条件之外， 还需具备下列条件： （一）具有基本的血液学研究基础和造血干细胞研究能力； （二）具有符合储存不低于1 万份脐带血的高清洁度的空间和冷冻设备的设计规划； （三）具有血细胞生物学、HLA 配型、相关病原体检测、遗传学和冷冻生物学、专供脐带血处理等符合GMP、 GLP 标准的实验室、资料保存室； （四）具有流式细胞仪、程控冷冻仪、PCR 仪和细胞冷冻及相关检测及计算机网络管理等仪器设备； （五）具有独立开展实验血液学、免疫学、造血细胞培养、检测、HLA 配型、病原体检测、冷冻生物学、 管理、质量控制和监测、仪器操作、资料保管和共享等方面的技术、管理和服务人员； （六）具有安全可靠的脐带血来源保证； （七）具备多渠道筹集建设资金运转经费的能力。 第九条设置脐带血造血干细胞库应向所在地省级卫生行政部门提交设置可行性研究报告，内容包括：
精神分裂症的发病原因是什么 精神分裂症是一种精神病，对于我们的影响是很大的，如果不幸患上就要及时做好治疗，不然后果会很严重，无法进行正常的工作和生活，是一件很尴尬的事情。因此为了避免患上这样的疾病，我们就要做好预防，今天我们就请广州协佳的专家张可斌来介绍一下精神分裂症的发病原因。 精神分裂症是严重影响人们身体健康的一种疾病，这种疾病会让我们整体看起来不正常，会出现胡言乱语的情况，甚至还会出现幻想幻听，可见精神分裂症这种病的危害程度。 (1)精神刺激：人的心理与社会因素密切相关，个人与社会环境不相适应，就产生了精神刺激，精神刺激导致大脑功能紊乱，出现精神障碍。不管是令人愉快的良性刺激，还是使人痛苦的恶性刺激，超过一定的限度都会对人的心理造成影响。 (2)遗传因素：精神病中如精神分裂症、情感性精神障碍，家族中精神病的患病率明显高于一般普通人群，而且血缘关系愈近，发病机会愈高。此外，精神发育迟滞、癫痫性精神障碍的遗传性在发病因素中也占相当的比重。这也是精神病的病因之一。 (3)自身：在同样的环境中，承受同样的精神刺激，那些心理素质差、对精神刺激耐受力低的人易发病。通常情况下，性格内向、心胸狭窄、过分自尊的人，不与人交往、孤僻懒散的人受挫折后容易出现精神异常。 (4)躯体因素：感染、中毒、颅脑外伤、肿瘤、内分泌、代谢及营养障碍等均可导致精神障碍，。但应注意，精神障碍伴有的躯体因素，并不完全与精神症状直接相关，有些是由躯体因素直接引起的，有些则是以躯体因素只作为一种诱因而存在。 孕期感染。如果在怀孕期间，孕妇感染了某种病毒，病毒也传染给了胎儿的话，那么，胎儿出生长大后患上精神分裂症的可能性是极其的大。所以怀孕中的女性朋友要注意卫生，尽量不要接触病毒源。 上述就是关于精神分裂症的发病原因，想必大家都已经知道了吧。患上精神分裂症之后，大家也不必过于伤心，现在我国的医疗水平是足以让大家快速恢复过来的，所以说一定要保持良好的情绪。
精神分裂症的病因是什么 精神分裂症是一种精神方面的疾病，青壮年发生的概率高，一般 在16～40岁间，没有正常器官的疾病出现，为一种功能性精神病。 精神分裂症大部分的患者是由于在日常的生活和工作当中受到的压力 过大，而患者没有一个良好的疏导的方式所导致。患者在出现该情况 不仅影响本人的正常社会生活，且对家庭和社会也造成很严重的影响。 精神分裂症常见的致病因素： 1、环境因素：工作环境比如经济水平低低收入人群、无职业的人群中，精神分裂症的患病率明显高于经济水平高的职业人群的患病率。还有实际的生活环境生活中的不如意不开心也会诱发该病。 2、心理因素：生活工作中的不开心不满意，导致情绪上的失控，心里长期受到压抑没有办法和没有正确的途径去发泄，如恋爱失败， 婚姻破裂，学习、工作中不愉快都会成为本病的原因。 3、遗传因素：家族中长辈或者亲属中曾经有过这样的病人，后代会出现精神分裂症的机会比正常人要高。 4、精神影响：人的心里与社会要各个方面都有着不可缺少的联系，对社会环境不适应，自己无法融入到社会中去，自己与社会环境不相
适应，精神和心情就会受到一定的影响，大脑控制着人的精神世界， 有可能促发精神分裂症。 5、身体方面：细菌感染、出现中毒情况、大脑外伤、肿瘤、身体的代谢及营养不良等均可能导致使精神分裂症，身体受到外界环境的 影响受到一定程度的伤害，心里受到打击，无法承受伤害造成的痛苦，可能会出现精神的问题。 对于精神分裂症一定要配合治疗，接受全面正确的治疗，最好的 疗法就是中医疗法加心理疗法。早发现并及时治疗并且科学合理的治疗，不要相信迷信，要去正规的医院接受合理的治疗，接受正确的治 疗按照医生的要求对症下药，配合医生和家人，给病人创造一个良好 的治疗环境，对于该病的康复和痊愈会起到意想不到的效果。
翻译公司收费标准 1.客户需要翻译的目标语言的普遍性和稀缺性可能导致非常 不同的费用。英语比较普遍，需求大，市场专业的英语翻译人 才也很多，翻译公司无论是从降价到抢占市场，还是成本核算 来考虑，英语收费都比较合理和透明。 其他诸如法语、德语、日语、俄语排在第二梯队，翻译公司收 费标准一般都是200-280元，视稿件专业度和数量略有调整； 意大利，西班牙，越南，泰文等东南亚语种已经接近稀有语 种了，翻译报价至少300元千字起。 2.根据翻译项目类型 常见的翻译方法主要包括翻译翻译、同声传译、本地翻译、口译翻译等，翻译项目自然是不同的收费。 3.根据翻译项目时长 这一时期的持续时间主要是指项目长度：同声传译、会议翻译、商务洽谈、双语主持人、口译、护送翻译、展览翻译，当然，视频翻译、音频翻译按时间计算的时间和会议类型是一个重要因素，是翻译时间决定翻译价格的一个重要因素。 4.根据翻译项目字数
翻译项目的字数是影响收费的重要因素之一，翻译字数主要对于笔译而言，例如：文件翻译、图书翻译、资料翻译、画册翻译等等，这些文件资料的字数决定了项目的翻译价格和翻译收费标准。 5.根据翻译项目语种 主流语种：英语、日语、韩语等和小语种：阿拉伯语、希腊语、印尼语等的翻译收费标准区别。我们知道：“物以稀为贵，”所以小语种的翻译报价会比主流语种收费要高的。 6.根据翻译项目难易程度 对于翻译公司来说，翻译费在很大程度上取决于翻译的难度程度，不同的行业术语不同，难度不同; 专业翻译公司将根据翻译人员的翻译水平、专业知识、翻译经验等方式来评价自己的翻译团队，高层次的翻译人员当然都是高收费; 如通用翻译、精细翻译、出版层次等不同类型的翻译报价不同，稿件的行业领域、材料难度、选择翻译类型等都是决定翻译公司收费标准的因素。
卫生部办公厅关于印发《脐带血造血干细胞治疗技术管理规 范(试行)》的通知 【法规类别】采供血机构和血液管理 【发文字号】卫办医政发[2009]189号 【失效依据】国家卫生计生委办公厅关于印发造血干细胞移植技术管理规范(2017年版)等15个“限制临床应用”医疗技术管理规范和质量控制指标的通知 【发布部门】卫生部(已撤销) 【发布日期】2009.11.13 【实施日期】2009.11.13 【时效性】失效 【效力级别】部门规范性文件 卫生部办公厅关于印发《脐带血造血干细胞治疗技术管理规范（试行）》的通知 （卫办医政发〔2009〕189号） 各省、自治区、直辖市卫生厅局，新疆生产建设兵团卫生局： 为贯彻落实《医疗技术临床应用管理办法》，做好脐带血造血干细胞治疗技术审核和临床应用管理，保障医疗质量和医疗安全，我部组织制定了《脐带血造血干细胞治疗技术管理规范（试行）》。现印发给你们，请遵照执行。 二〇〇九年十一月十三日
脐带血造血干细胞 治疗技术管理规范（试行） 为规范脐带血造血干细胞治疗技术的临床应用，保证医疗质量和医疗安全，制定本规范。本规范为技术审核机构对医疗机构申请临床应用脐带血造血干细胞治疗技术进行技术审核的依据，是医疗机构及其医师开展脐带血造血干细胞治疗技术的最低要求。 本治疗技术管理规范适用于脐带血造血干细胞移植技术。 一、医疗机构基本要求 （一）开展脐带血造血干细胞治疗技术的医疗机构应当与其功能、任务相适应，有合法脐带血造血干细胞来源。 （二）三级综合医院、血液病医院或儿童医院，具有卫生行政部门核准登记的血液内科或儿科专业诊疗科目。 1.三级综合医院血液内科开展成人脐带血造血干细胞治疗技术的，还应当具备以下条件： （1）近3年内独立开展脐带血造血干细胞和（或）同种异基因造血干细胞移植15例以上。 （2）有4张床位以上的百级层流病房，配备病人呼叫系统、心电监护仪、电动吸引器、供氧设施。 （3）开展儿童脐带血造血干细胞治疗技术的，还应至少有1名具有副主任医师以上专业技术职务任职资格的儿科医师。 2.三级综合医院儿科开展儿童脐带血造血干细胞治疗技术的，还应当具备以下条件：
英文合同翻译价格英文合同翻译需要多少钱 在企业的经营过程中，有时候可能会涉及到翻译这个问题，但是一般的小企业并没有专门的人去做这件事情，大部分都是外包。那么对于企业来讲，翻译一份英文合同需要多少钱呢？作为浙江省最大的翻译公司，以琳翻译就在这里为大家解读一下。 一般来讲，翻译这项服务都是以字数来计价的，市场上的一般的价格是50-80元/千字，这是一个基本的价格。但是不同的公司的专业性质不一样的话，所给出的价格也是不一样的。对于公司的衡量标准来讲，影响价格的因素主要有：公司的资历、翻译人员的专业性、翻译文件的种类、难度等。所以，如果你需要去找翻译公司去服务，那么就需要考虑这些方面的东西。而对于合同这种文件，对于公司来讲是十分重要的，所以也需要去找专业的公司去进行翻译，如果是找一个资质不够的公司或者团队，那么就可能产生一些意想不到的问题，从而影响到公司的最终利益。 下面，我们来看看以琳翻译给出的翻译的价格。 从上面的价格可以看出，以琳翻译给出的价格是高于一般市场上的价格的，最低级别的翻译是160元/千字，然后分为A、B、C三级。C级译稿为普通中籍译员+中籍译员审核，满足客户对译文的普通要求。这是对于一般的合同而言的，但是如果是部分专业性质较强或者要求比较高的译文的话，那么可以选择更高级别的翻译，当然价格还是相对比较高的。 那么以琳翻译的资质是怎么样呢？我们再来看一下。 杭州以琳翻译有限公司是浙江省最大的实体翻译公司、中国翻译协会单位会员、美国翻译协会会员、全国翻译专业硕士研究生教育实习基地、西博会指定合作伙伴、以琳杭州翻译公司翻译团队成员均具有五年以上专业翻译、项目管理经验，绝大部分成员具有十年以上行业翻译经验。翻译服务涵盖英语、法语、韩语、日语、德语、俄语、西班牙语、葡萄牙语、
精神分裂症应该怎么治疗 1、坚持服药治疗 服药治疗是最有效的预防复发措施临床大量统计资料表明，大多数精神分裂症的复发与自行停药有关。坚持维持量服药的病人复发率为40%。而没坚持维持量服药者复发率高达80%。因此，病人和家属要高度重视维持治疗。 2、及时发现复发的先兆，及时处理 精神分裂症的复发是有先兆的，只要及时发现，及时调整药物和剂量，一般都能防止复发，常见的复发先兆为：病人无原因出现睡眠不好、懒散、不愿起床、发呆发愣、情绪不稳、无故发脾气、烦躁易怒、胡思乱想、说话离谱，或病中的想法又露头等。这时就应该及时就医，调整治疗病情波动时的及时处理可免于疾病的复发。 3、坚持定期门诊复查 一定要坚持定期到门诊复查，使医生连续地、动态地了解病情，使病人经常处于精神科医生的医疗监护之下，及时根据病情变化调整药量。通过复查也可使端正人及时得到咨询和心理治疗解除病人在生活、工作和药物治疗中的各种困惑，这对预防精神分裂症的复发也起着重要作用。 4、减少诱发因素 家属及周围人要充分认识到精神分裂症病人病后精神状态的薄弱性，帮助安排好日常的生活、工作、学习。经常与病人谈心，帮助病人正确对待疾病，正确对待现实生活，帮助病人提高心理承受能力，学会对待应激事件的方法，鼓励病人增强信心，指导病人充实生活，使病人在没有心理压力和精神困扰的环境中生活。 首先是性格上的改变，塬本活泼开朗爱玩的人，突然变得沉默寡言，独自发呆，不与人交往，爱干净的人也变的不注意卫生、生活
懒散、纪律松弛、做事注意力不集中，总是和患病之前的性格完全 相悖。 再者就是语言表达异常，在谈话中说一些无关的谈话内容，使人无法理解。连最简单的话语都无法准确称述，与之谈话完全感觉不 到重心。 第三个就是行为的异常，行为怪异让人无法理解，喜欢独处、不适意的追逐异性，不知廉耻，自语自笑、生活懒散、时常发呆、蒙 头大睡、四处乱跑，夜不归宿等。 还有情感上的变化，失去了以往的热情，开始变的冷淡、对亲人不关心、和友人疏远，对周围事情不感兴趣，一点消失都可大动干戈。 最后就是敏感多疑，对任何事情比较敏感，精神分裂症患者，总认为有人针对自己。甚至有时认为有人要害自己，从而不吃不喝。 但是也有的会出现难以入眠、容易被惊醒或睡眠不深，整晚做恶梦或者长睡不醒的现象。这些都有可能是患上了精神分裂症。 1.加强心理护理 心理护理是家庭护理中的重要方面，由于社会上普遍存在对精神病人的歧视和偏见，给病人造成很大的精神压力，常表现为自卑、 抑郁、绝望等，有的病人会因无法承受压力而自杀。家属应多给予 些爱心和理解，满足其心理需求，尽力消除病人的悲观情绪。病人 生活在家庭中，与亲人朝夕相处，接触密切，家属便于对病人的情感、行为进行细致的观察，病人的思想活动也易于向家属暴露。家 属应掌握适当的心理护理方法，随时对病人进行启发与帮助，启发 病人对病态的认识，帮助他们树立自信，以积极的心态好地回归社会。 2.重视服药的依从性 精神分裂症病人家庭护理的关键就在于要让病人按时按量吃药维持治疗。如果不按时服药，精神病尤其是精神分裂症的复发率很高。精神病人在医院经过一系统的治疗痊愈后，一般需要维持2~3年的
精诚英语翻译报价50-80元千字（市场价格100左右 精诚英语翻译工作室是由众多英语方面精英组成的翻译团队,一直致力于为广大中小企业和个人提供专业低价中英文翻译服务。价格是我们永远的优势！！！！最低价格支付宝担保交易，让你省钱又放心接受试译！！自信源于专业可以百度搜索精诚英语翻译找到我们 选择我们的理由：可以百度搜索精诚英语翻译找到我们 1.保证价格最低，团队网络化运作，无需经营成本，可以通过低价让利于客户。（有些客户看到这么低的价格还不敢相信，但是对于我们来说是完全可以接受的。） 2.保证准时、保密、准确 3.接受淘宝交易，让您没有任何担忧。 4.长期翻译经验，保证质量让您满意。 龚如心遗产案虽然告一段落，「遗产」二字仍然成为近日香港的焦点。新春期间，民政事务局局长曾德成表示，政府将展开全港非物质文化遗产首期普查，希望市民为遗产清单提出建议。 「遗产」是「资产」？ 近五、六年间，香港对保护本地小区和文化传统的意识高涨，现在政府带头要列一个「非物质文化遗产」清单，理应是很受欢迎之举。不过普查尚未展开，就引来学者争议，其中单是「非物质文化遗产」这个译名，就引起不少误会。 「非物质文化遗产」的原文是intangible cultural heritage（英文）或patrimoine culturel immateriel （法文），是联合国在1997年以尊重多元文化为大原则而提出的概念，并由联合国教科文组织制定「保护非物质文化遗产公约」，2006年生效。 「非物质文化遗产」是中国大陆的翻译，香港有学者不约而同就「非物质」和「遗产」二字提出质疑。香港城市大学中国文化中心主任郑培凯早在2005年就大声疾呼译名不妥。他认为原文heritage/patrimoine的意义是「传承」而非资产，不容易引发出财产的概念。而现在约定俗成译作「遗产」，容易令人觉得祖宗留下的东西，是可以变卖和投资的生财工具，与联合国提出的文化传承精神背道而驰。郑教授认识，正确的译名是「非物质文化承继」或「非实物文化传承」。另一位民俗学研究者陈云进一步指出，intangible「乃触摸不到的事，无形无相之事」，应用「精神价值」代之，「非物质」有消灭了精神之嫌，所以中国人应堂堂正正将之翻译为「无形文化传承」。 姗姗来迟的「遗产」 不论是「非物质」还是「无形」，「遗产」还是「承传」，即使公约成员国中国曲译甚至错译，香港特区政府还是只能照单全收。而且，随之而来的不止是字面的斟酌，而是「遗产」的搜寻和管理问题。 中国自2005年起，就开始非物质文化遗产（由于这个名称已约定俗成，故下文仍沿用之，并简称为「非遗」）普查，并陆续列出清单。香港也在翌年提出编制非遗清单，但却延至去年才聘专家普查，估计最快要2012年才完成。 非遗普查尚未展开，在国家文化部的再三邀请（或是说催促？）下，去年九月，香港终于申请将长洲太平清醮、大澳端午游涌、大坑舞火龙和香港潮人盂兰胜会列为第三批国家级非遗，预计今年六月有结果。 其实香港已错过了2006和2008年首批和第二批的申报机会，所以，至目前为止，在中国的文化版图上，香港是唯一没有任何有形和无形「遗产」的主要城市／特区，就连比邻的澳门也凭神像雕刻工艺获得2008年国家级非遗之「奖项」。 有人说非遗不过是人有我有，纯粹锦上添花；也有人说，中国在维护主权和领土完整的概念下，又怎能在文化层面少了香港一席？香港能够「出产」一个非遗，中国在全球的文化图谱中就多一个筹码。 姑勿论背后原因为何，由于「保护非物质文化遗产公约」也适用于香港，香港特区政府就有责任找出和保护濒危失传、与社会关系密切及具香港独特性的文化传统。现在起步虽迟，但为时未晚。 「遗产」的管理问题 不过，既然政府要展开普查，另一个问题来了。民间传统应该是属于民间的，并由民间自行发展，还是属于官方，由政府承担保护与管理？ 据政府委聘负责首期普查的香港科技大学华南研究中心主任廖迪生表示，政府至今仍未有任何政策配合或承诺给予全面的保护，所以，即使清单出炉，有些遗产仍有可能难逃「破产」的命运。他强调制作非遗清单只是第一步，更重要的是如何保护这些项目。 再问民政事务局，曾德成局长除了曾向立法会议员表示，制定清单是向国家文化部申请列为国家级非遗的第一步，进而再向联合国教科文组织提出申报为世界非物质文化遗产，他所提出的，就是以遗产作招徕吸引外地游客，「以提升香港作为旅游目的地的吸引力」。 这才是令人担心的地方。「非遗」这个金漆招牌在中国许多地方都有点石成金之效。戴上这个冠冕，民俗文化很容易沦为生财工具、游客的消费品，连婚嫁仪式也可用来表演，完全违背了保护非遗的原意。曾德成之言，是否意味着香港也要跟着祖国一起走上同一条路？
卫生部关于印发《脐带血造血干细胞库设置管理规范(试行)》的通知 发文机关：卫生部(已撤销) 发布日期： 2001.01.09 生效日期： 2001.02.01 时效性：现行有效 文号：卫医发(2001)10号 各省、自治区、直辖市卫生厅局： 为贯彻实施《脐带血造血干细胞库管理办法（试行）》，保证脐带血临床使用的安全、有效，我部制定了《脐带血造血干细胞库设计管理规范（试行）》。现印发给你们，请遵照执行。 附件：《脐带血造血干细胞库设置管理规范（试行）》 二○○一年一月九日 附件： 脐带血造血干细胞库设置管理规范（试行） 脐带血造血干细胞库的设置管理必须符合本规范的规定。 一、机构设置 （一）脐带血造血干细胞库（以下简称脐带血库）实行主任负责制。 （二）部门设置 脐带血库设置业务科室至少应涵盖以下功能：脐带血采运、处理、细胞培养、组织配型、微生物、深低温冻存及融化、脐带血档案资料及独立的质量管理部分。 二、人员要求
（一）脐带血库主任应具有医学高级职称。脐带血库可设副主任，应具有临床医学或生物学中、高级职称。 （二）各部门负责人员要求 1．负责脐带血采运的人员应具有医学中专以上学历，2年以上医护工作经验，经专业培训并考核合格者。 2．负责细胞培养、组织配型、微生物、深低温冻存及融化、质量保证的人员应具有医学或相关学科本科以上学历，4年以上专业工作经历，并具有丰富的相关专业技术经验和较高的业务指导水平。 3．负责档案资料的人员应具相关专业中专以上学历，具有计算机基础知识和一定的医学知识，熟悉脐带血库的生产全过程。 4．负责其它业务工作的人员应具有相关专业大学以上学历，熟悉相关业务，具有2年以上相关专业工作经验。 （三）各部门工作人员任职条件 1．脐带血采集人员为经过严格专业培训的护士或助产士职称以上卫生专业技术人员并经考核合格者。 2．脐带血处理技术人员为医学、生物学专业大专以上学历，经培训并考核合格者。 3．脐带血冻存技术人员为大专以上学历、经培训并考核合格者。 4．脐带血库实验室技术人员为相关专业大专以上学历，经培训并考核合格者。 三、建筑和设施 （一）脐带血库建筑选址应保证周围无污染源。 （二）脐带血库建筑设施应符合国家有关规定，总体结构与装修要符合抗震、消防、安全、合理、坚固的要求。 （三）脐带血库要布局合理，建筑面积应达到至少能够储存一万份脐带血的空间；并具有脐带血处理洁净室、深低温冻存室、组织配型室、细菌检测室、病毒检测室、造血干/祖细胞检测室、流式细胞仪室、档案资料室、收/发血室、消毒室等专业房。 （四）业务工作区域应与行政区域分开。
精神分裂症患者在怎样的情况下会自杀 精神分裂症是最常见的一种精神病。早期主要表现为性格改变，如不理采亲人、不讲卫生、对镜子独笑等。病情进一步发展，即表现为思维紊乱，病人的思考过程缺乏逻辑性和连贯性，言语零乱、词不达意。精神分裂症患者随时有可能出现危险行为，这主要是指伤人毁物、自伤自杀和忽然出走。这些危险行为是受特定的精神症状支配的.那么精神分裂症患者在什么情况下会自杀呢？ 被害妄想：这是所有精神病人最常见的症状之一，多数病人采取忍耐、逃避的态度，少数病人也会“先下手为强”，对他的“假想敌”主动攻击。对此，最重要的是弄清病人的妄想对象，即：病人以为是谁要害他。假如病人的妄想对象是某个家里人，则应尽量让这位家属阔别病人，至少不要让他与病人单独在一起。 抑郁情绪：精神分裂症病人在疾病的不同时期，可能出现情绪低落，甚至悲观厌世。特别需要留意的是，有相当一部分自杀成功的病人，是在疾病的恢复期实施自杀行为的。病人在精神病症状消除以后，因自己的病背上了沉重的思想包袱，不能正确对待升学、就业、婚姻等现实问题，感到走投无路，因此选择了轻生。对此，家属一定要防患于未然，要尽早发现病人的心理困扰，及时疏导。 对已经明确表示出自杀观念的病人，家属既不要惊慌失措，也不要躲躲闪闪，要主动与病人讨论自杀的利弊，帮助病人全面、客观地评估现实中碰到的各种困难，找出切实可行的解决办法。 另外，这种病人在自杀之前，是经过周密考虑，并且做了充分预备的，例如写遗书、收拾旧物、向家人离别、选择自杀时间、预备自杀工具等。这类病人的自杀方式也是比较温顺的，多数是服药自杀。因此，他需要一定的时间来积攒足足数目的药物，这时就能看出由家属保管药品的重要性了。只要家属密切观察病人的情绪变化，是不难早期发现病人的自杀企图的。 药源性焦虑：抗精神病药的副作用之一是可能引起病人莫名的焦躁不安、手足无措，并伴有心慌、出汗、恐惧等。这些表现多是发作性的，多数发生在下午到傍晚时分，也有的病人在打长效针以后的2?3天内出现上述表现。这种时间上的规律性，有助于家属判定病人的焦虑情绪是否由于药物所致。病人急于摆脱这种强烈的痛苦，会出现冲动伤人或自伤，这些行为只是为了发泄和解脱，并不以死为终极目的。家属可以在病人发作时，给他服用小剂量的安定类药物，或者在医生的指导下，调整抗精神病药的剂量或品种，这样就可以有效地控制病人的焦虑发作。 极度兴奋：病人的精神症状表现为严重的思维紊乱、言语杂乱无章、行为缺乏目的性，这类病人也可能出现自伤或伤人毁物。由于病人的兴奋躁动是持续性的，家属有充分的思想预备，一般比较轻易防范。家属要保管好家里的刀、剪、火、煤气等危险物品，但最根本的办法，是使用大剂量的、具有强烈镇静作用的药物来控制病人的兴奋。假如在家里护理病人确有困难，则可以强制病人住院治
英文翻译价格 根据以英文作为母语的人数计算，英文是最多国家使用的官方语言，英语也是世界上最广泛的第二语言，也是欧盟，最多国际组织和英联邦国家的官方语言之一。但仅拥有世界第二位的母语使用者，少于标准汉语。上两个世纪英国和美国在文化、经济、军事、政治和科学上的领先地位使得英语成为一种国际语言。如今，许多国际场合都使用英语做为沟通媒介。英语也是与电脑联系最密切的语言，大多数编程语言都与英语有联系，而且随着网络的使用，使英文的使用更普及。英语是联合国的工作语言之一。 为了方便大家了解英文翻译价格，小编在目前汇集最多翻译团队的高校译云上面获得了不同翻译精英团队所展示的价格。 暨南大学翻译中心：中英---普稿---150---千字英中---普稿---250---千字 武汉理工大学-外国语学院MTI翻译中心 ：中英互译中英130-150 英中100-130 华中科技大学-翻译研究中心 ：中英互译中英120-150 英中100-120 湖南科技大学MTI中心：中英---普稿---150---千字 上海师大外国语学院翻译中心： 中英---普稿---200元---千字英语普通文本译成汉语---120元---千字西南大学翻译中心：中英---普稿----300---千字英中---普稿---200---千字 上海理工大学MTI翻译中心：中英---普稿---100---千字 南京财经大学外国语学院翻译研究中心：中英---普稿---100---千字 一般英文翻译价格是是在100—300元每千字，根据译员质量、翻译内容、需要的时间等都会有一定的波动，所以以上价格供大家参考，具体的可以准备好稿件了去问，这样会更加准确一些。
脐带血间充质干细胞的分离培养和鉴定 【摘要】目的分离培养脐带血间充质干细胞并检测其生物学特性。方法在无菌条件下用密度梯度离心的方法获得脐血单个核细胞，接种含10%胎牛血清的DMEM培养基中。单个核细胞行贴壁培养后，进行细胞形态学观察，绘制细胞生长曲线，分析细胞周期，检测细胞表面抗原。结果采用Percoll(1.073 g/mL)分离的脐血间充质干细胞大小较为均匀，梭形或星形的成纤维细胞样细胞。细胞生长曲线测定表明接后第5天细胞进入指数增生期，至第9天后数量减少;流式细胞检测表明50%～70%细胞为CD29和CD45阳性。结论体外分离培养脐血间充质干细胞生长稳定，可作为组织工程的种子细胞。 【关键词】脐血;间充质干细胞;细胞周期;免疫细胞化学 Abstract: Objective Isolation and cultivation of mesenchymal stem cells (MSCs) in human umbilical cord in vitro, and determine their biological properties. Methods The mononuclear cells were isolated by density gradient centrifugation from human umbilical cord blood in sterile condition, and cultured in DMEM medium containing 10% fetal bovine serum. After the adherent mononuclear cells were obtained, the shape of cells were observed by microscope, then the cell growth curve, the cell cycle and the cell surface antigens were obtained by immunocytochemistry and flow cytometry methods. Results MSCs obtained by Percoll (1.073 g/mL) were similar in size, spindle-shaped or star-shaped fibroblasts-liked cells. Cell growth curve analysis indicated that MSCs were in the exponential stage after 5d and in the stationary stages after 9d. Flow cytometry analysis showed that the CD29 and CD44 positive cells were about 50%～70%. Conclusions The human umbilical cord derived mesenchymal stem cells were grown stably in vitro and can be used as the seed-cells in tissue engineering. Key words:human umbilical cord blood; mesenchymal stem cells; cell cycle; immunocytochemistry 间充质干细胞(mesenchymal stem cells，MSCs)在一定条件下具有多向分化的潜能，是组织工程研究中重要的种子细胞来源。寻找来源丰富并不受伦理学制约的间充质干细胞成为近年来的研究热点[1]。脐血(umbilical cord blood, UCB)在胚胎娩出后，与胎盘一起存在的医疗废物。与骨髓相比，UCB来源更丰富，取材方便，具有肿瘤和微生物污染机会少等优点。有人认为脐血中也存在间充质干细胞(Umbilical cord blood-derived mesenchymal stem cells，UCB-MSCs)。如果从脐血中培养出MSCs，与胚胎干细胞相比，应用和研究则不受伦理的制约，蕴藏着巨大的临床应用价值[2,3]。本研究将探讨人UCB-MSCs体外培养的方法、细胞的生长曲线、增殖周期和细胞表面标志等方面，分析UCB-MSCs 作为间充质干细胞来源的可行性。
出生前背景 母亲是地道、淳朴、专一，文化程度不高的农村主妇，父亲是当地的混混，好色成性，道德观念淡薄，无责任感，为非作歹，攻击性强，专横，常聚众斗殴，浪荡无比。他的放荡从和母亲接姻前持续到今。从母亲断断断断续的回忆中我恍知我没呱呱落地前就已有不寻常的经历，失职的母亲怀着我和父亲怄气经常绝食威胁，奢望唤醒父亲的为父为夫的责任感。可怜的女人，痴痴的等待，身心俱损终换不来一时的真爱。他从不掩饰自己的劣迹，而是将其当作显示自己无限魅力和能耐的招牌加以渲染，毫无顾忌在当众谈论。 童年背景 除父母，还有两兄，我是幼女，相比较受宠爱。 爷爷 奶奶，传统的封建妇女，极重男轻女，从未给过我好脸色。爷爷、奶奶在家中居从属地位，对我没产生至关重要的影响。 儿时家里很穷，主要靠母亲支撑维系家族。她非常辛苦，在纺织厂，三班制。歇工还要步行到七八公里外的田地里劳作。很难照顾到我们的感受，她所能做的就是竭尽所能维系家庭的完整，让我们能生存下去。与此同时，她还要忍受父亲周而复始的背叛，虐待、暴打。生活不如意加之贫困无比，让她难免脾气暴躁，我是她时常爆发时的接纳对象。如此妇女，受封建思想灌输至深，永远铭记自己要恪守妇道，她始终如一的忠诚与父亲，永不离弃他，爱护他，疼爱他（她比父亲年长些，父亲相貌俊秀，而母亲姿色平平）。我可怜而鄙视她，丈夫如果某天一改往日作贱她的口吻，她会像孩子似的受宠若惊的心花怒放。 父亲霸道无比，家里人人惧怕他，他无比自恋。除了母亲，伤害最深的是大哥，每天无缘无故的遭受父亲的暴打。他性情多变，无法揣摩，吃饭时一家人欢声笑语，吃完饭看看大哥不顺眼他操起皮鞭就抽。看到大哥在皮鞭下嚎哭，新的皮鞭疤痕烙在旧疤痕上，我和二哥感到恐惧，怜悯大哥，然而我们是无助的，谁也不能阻挡皮鞭的落下。尽管如此，父亲当时在我心目中是高大的，令人崇拜的，对我产生的正负影响也是最强烈的。他多才多艺，知识渊博，开明，前卫，聪明，而母亲相比之下平庸很多，她每天只是起早贪黑的工作，思想保守，愚昧，无任何才华而言。 童年，虽说不是幸福的，但也算不上痛苦。 童年转青春期阶段 邻居是一个恶老太婆，和当时大多传统村妇一样，没知识、没修养也没教养。她确实很恶，不允许她看不顺眼的小孩从她家旁边的小巷经过，她不喜欢我。每次我冒险经过她都会如同恶狗样在我刚出现在她视野中就开始狂吠，连同我的老祖宗也一起骂，持续到我再次从原路返回，躲到家里，她的吠声还要延续十分钟。 被爱妄想出现在五年级，应该更早些。我喜欢上一个家境优越的的男生，尽管那时他已经有“女朋友”。从爱上他那刻起我就很明确他也是爱我的，他和同桌说话其实余光是在看我，尽管没有任何证实，我非常明确他就是偷偷看我的。即使在上课，即使他没有和同桌说话，我感觉他在狠狠的想着我。他回答老师的提问也暗示着对我的爱意。比如他的回答里有“她”，那就是暗示他说的是我。或是我读书看到书上的“他”字样，心便狂喜的乱跳，认为这是我暗恋对象给我的暗示，他一直在我身边！ 妄想形成初期就有泛化倾向，我似乎对自己相貌无限自信，觉得自己是最美的，一上街满街的男孩都为我的美貌所折服，他们都不由自主的盯着我看，我的一举一动都被他们密切关注着，一出门便有那么多双眼睛注视着我。
脐带血干细胞检测 对每份脐血干细胞进行下列检测： ①母体血样做梅毒、HIV和CMV等病原体检测，这一检测使脐血干细胞适合于其它家庭成员应用。如任何一种病原体测试阳性，需重复测定。 ②每份脐血干细胞样本同时检测确定没有微生物污染。 ③细胞活性检测、有核细胞数、CD34+细胞数、集落形成试验等。CD34是分子量115KD 的糖蛋白分子，使用特定单克隆抗体（抗-CD34）确定，脐血祖细胞的大部分，包括体外培养产生造血集落的细胞都包含在表达CD34抗原的细胞群中。 ④HLA组织配型、ABO血型。 一、采血方式及其优点 再生缘生物科技公司采用最严谨的封闭式血袋收集法，避免在收集脐带血液时可能遭受微生物污染的发生，且以最少之操作步骤，收集最大量之脐带血液方式，在产房内即可完成。 二、脐带血处理与保存 脐带血收集于血袋，经专人运送至再生缘生物科技公司之无菌细胞分离实验室后，由专业的技术人员于完全无菌的环境下，依标准操作程序将血液进行分离，收集具有细胞核的细胞，其中含有丰富的血液干细胞，经加入冷冻保护剂和适当品管检测后，并进行以最适合
血液干细胞的冷冻降温程序方式，进行细胞冷冻程序，达到避免细胞受到冷冻过程之伤害。完成后，冷冻细胞立刻保存于摄氏零下196度的液态氮槽中。所有操作程序记录和细胞保存相关数据，均由计算机条形码系统追踪确认，完全符合国际脐带血库之标准操作程序和品管要求。 母亲血液之检测 为确保所操作和保存的脐带血液细胞，符合国际血液操作规范，并提供客户最大的保障，对于产妇血液必须同时进行一些病毒传染病的检测，以确保没有下列病毒，如艾滋病毒(HIV)、C型肝炎病毒(HCV)、人类T细胞淋巴病毒(HTLV)和梅毒(syphilis)，同时对于B型肝炎病毒(HBV)和巨细胞病毒(CMV)加以侦测和纪录，作为将来可能应用脐带血细胞时之必要参考数据并符合卫生医疗之要求。 脐带血细胞之品管 对于所保存之脐带血细胞均进行多项操作流程监控和品管检测，如微生物污染检测、血液细胞浓度、细胞存活率、细胞活性测定等，每一步骤均有详细之纪录，在操作方法和使用仪器方面均定期进行验证和校验，以符合国际医疗标准。 三、实验室、贮存处所介绍 再生缘生物科技公司拥有符合美国联邦标准(FED-STD-209E)和中华民国优良药品制造标准（一区、二区、三区）的生物安全实验室和无菌操作设备，在专业的技术人员依标准操作程序下进行血液分离和保存步骤，保障客户珍贵样品和权益。 分离后之细胞将依浓度分装入4-6个冷冻管，计算机降温冷冻完成后，即由食品工业发展研究所国家细胞库专业液态氮库房人员，将冷冻细胞分别存放于二个不同的脐带血细胞专属液态氮槽中保存，在安全机制上更有保障。液态氮库房拥有五吨的液态氮供应系统，每一液氮槽均有自动充填装置和异常警报系统，和每日值勤人员监控，确保冷冻细胞处于最佳的冷冻状态。 四、安全管制措施 脐带血液经快递送达无菌细胞分离实验室后，每一步骤均有专业技术人员操作和监督，并将所有分析数值详细填于具有条形码管制之分析表格和计算机数据表中，利用条形码和读码系统确认样品之专一性，避免人为失误，且便于追溯和数据品管。 在冷冻细胞保存上