Weighted Scale-Free Networks with Stochastic Weight Assignments

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Weighted Scale-Free Networks with Stochastic Weight

Assignments Dafang Zheng 1,?,Ste?en Trimper 1,Bo Zheng 1,2and P.M.Hui 31Fachbereich Physik,Martin-Luther-Universit¨a t,D-06099Halle,Germany 2Department of Physics,Zhejiang University,Hangzhou 310027,P.R.China 3Department of Physics,The Chinese University of Hong Kong,Shatin,New Territories,Hong Kong Abstract We propose and study a model of weighted scale-free networks incorpo-rating a stochastic scheme for weight assignments to the links,taking into account both the popularity and ?tness of a node.As the network grows the weights of links are driven either by the connectivity with probability p or by the ?tness with probability 1?p .Results of numerical simulations show that the total weight associated with a selected node exhibits a power law distribution with an exponent σ,the value of which depends on the proba-bility p .The exponent σdecreases continuously as p increases.For p =0,the total weight distribution displays the same scaling behavior as that of the connectivity distribution with σ=γ=3,where γis the exponent charac-terizing the connectivity distribution.An analytical expression for the total weight is derived so as to explain the features observed in the numerical re-

sults.Numerical results are also presented for a generalized model with a

?tness-dependent link formation mechanism.

PACS numbers:89.75.Hc,05.65.+b,02.50Cw,84.35.+i

Typeset using REVT E X

I.INTRODUCTION

Many complex systems,including social,biological,physical,economic,and computer systems,can be studied using network models in which the nodes represent the constituents and links or edges represent the interactions between constituents[1,2].One of important measures of the topological structure of a network is its connectivity distribution P(k),which is de?ned as the probability that a randomly selected node has exactly k edges.In traditional random graphs[3,4]as well as in the small-world networks[5–7]the connectivity distribution shows exponential decay in the tail.However,empirical studies on many real networks showed that the connectivity distribution exhibits a power law behavior P(k)～k?γfor large k[1,2].Networks with power-law connectivity distributions are called scale-free(SF) networks.Typical examples of SF networks include the Internet[8–10],World-Wide-Web [11–13],scienti?c citations[14],cells[15,16],the web of actors[17],and the web of human sexual contacts[18].The?rst model of SF networks was proposed by Barab′a si and Albert (BA)[19].In BA networks two important ingredients are included in order to obtain power law behavior in the connectivity distributions,namely the networks are continuously growing by adding in new nodes as time evolves,and the newly added nodes are preferentially attached to the highly connected nodes.The idea of incorporating preferential attachment in a growing network has led to proposals of a considerable number of models of SF networks [20–26](see also Refs.[1,2]and references therein).

In most growing network models,all the links are considered equivalent.However,many real systems display di?erent interaction strengths between nodes.It has been shown that in systems such as the social acquaintance network[27],the web of scientists with collaborations [28],and ecosystems[29],links between nodes may be di?erent in their in?uence and the so-called the weak links play an important role in governing the network’s functions.Therefore, real systems are best described by weighted growing networks with non-uniform strengths of the links.Only recently,a class of models of weighted growing networks was proposed by Yook,Jeong and Barab′a si(YJB)[30].In the basic weighted scale-free(WSF)model of YJB,

both the topology and the weight are driven by the connectivity according to the preferential attachment rule as the network grows.It was found that the total weight distribution follows a power law P(w)～w?σ,with an exponentσdi?erent from the connectivity exponentγ.It was also shown analytically that the di?erent scaling behavior in the weight and connectivity distributions are results of strong logarithmic corrections,and asymptotically(i.e.,in the long time limit)the weighted and un-weighted models are identical[30].

In real systems one would expect that a link’s weight and/or the growth rate in the number of links of a node depend not only on the“popularity”of the node represented by the connectivity,but also on some intrinsic quality of the node.The intrinsic quality can be collectively represented by a parameter referred to as the“?tness”[31,32].Besides popularity,the competitiveness of a node in a network may depend,taking for example a node being an individual in a certain community,on the personality,survival skills,character, etc..A newly added node may take into account of these factors beside popularity in their decision on making connections with existing nodes and on the importance of each of the established links.Clearly,there is always a spectrum of personality among the nodes and therefore a distribution in the?tness.While one may argue that factors determining the popularity may overlap with those in?tness,it is not uncommon that popularity is not the major factor on the importance of a connection.For example,we often hear that a popular person actually has very few good friends,and an in?uential and powerful?gure in a network may often be someone very di?cult to work with.In the present work,we generalize the WSF model of YJB to study the e?ects of?tness.In our model,the weights assigned to the newly added links are determined stochastically either by the connectivity with probability p or by the?tness of nodes with probability1?p.The scaling behavior of the total weight distribution is found to be highly sensitive to the weight assignment mechanism through the parameter p.

The plan of the paper is as follows.In Sec.II,we present our model and simulation results.In Sec.III,we derive an analytical expression between the total weight and the total connectivity of a node and provide a theoretical explanation on the features observed in the

numerical results.Results on a generalized model with a?tness-dependent link formation mechanism are presented in Sec.IV,together with a summary of results.

II.THE MODEL AND NUMERICAL RESULTS

The topological structure of our model follows that of the BA model of SF networks[19].

A small number(m0)of nodes are created initially.At each time step,a new node j with m(m≤m0)links is added to the network.These m links will connect to m pre-existing nodes in the system according to the preferential attachment rule that the probabilityΠi of an existing node i being selected for connection is proportional to the total number of links k i that node i carries,i.e.,

k i

Πi=

{i′}k i′,(2) where {i′}is a sum over the m nodes to which the new node j is connected.With probability 1?p,w ji is determined by the?tness through

ηi

w ji=

In Eqs.(2)and(3),w ji is normalized so that the sum of the weights for the m new links is unity,i.e., {i′}w ji′=1[30].For p=1,our model reduces to the basic WSF model of

YJB in which the weights are driven by the connectivity alone[30].For p=0,the weights are driven entirely by the?tness of the nodes.For0

We performed extensive numerical simulations on the model.In our simulations,we studied networks up to N=5×105nodes with m=m0=5.For each value of p,results are obtained by averaging over10independent runs.First we study the total weight distribution P(w),which is de?ned as the probability that a randomly selected node has a total weight w.The total weight of a node i is given by the sum of the weights of all links connected to it,i.e.,w i= j w ij.Figure1shows that P(w)behaves as a power law P(w)～w?σ, with an exponentσthat decreases from the value of3at p=0continuously as p increases. For p=1,σ=2.4,a result in agreement with that of the WSF model of YJB[30].For p=0,σ=3(=γ)showing that P(w)follows the same scaling behavior as P(k).YJB found that the scaling behavior of P(w)depends strongly on m[30]in their model.In the present model,we found that the m-dependence persists for all p>0.Only when p=0,σbecomes independent of m.

It is also interesting to study the dynamical behavior of the total weight w i(ηi,t)of some node i with?tnessηi.Fig.2shows that w i(ηi,t)grows with a power law behavior with time with an exponentδthat depends on p.For p>0,δ>β,whereβ=1/2is the exponent characterizing the dynamical behavior of the connectivity k i(t)[19].For p=0,w i(ηi,t) shows the same scaling behavior as k i(t)withδ=β=1/2.For0

The probability distribution P(w ij)of the weights w ij of individual links is also worth investigating.To suppress statistical?uctuations,Fig.3shows the cumulative distribution,

P(x>w ij),instead of P(w ij),on a log-linear scale.For p=0,P(x>w ij)decays expo-nentially in the tail.Recall that P(w)and w i(ηi,t)show identical behavior as P(k)and k i(t)for p=0respectively,and the latter two quantities are not sensitive to the weight assignment scheme.Here P(x>w ij)shows an exponentially decaying behavior,implying that the weighted and un-weighted models are not totally identical even for p=0.For p>0,the tail deviates from an exponential decaying form and decays faster as p increases. For p=1,we recover the results in the YJB model[30].

III.ANALYTICAL SOLUTION

To understand the di?erent behavior between w i(ηi,t)and k i(t)(as well as between P(w) and P(k))found in numerical simulations,we derive an analytical expression for the total weight w i(ηi,t)of a node i with?tnessηi at time t.Following YJB[30],w i(ηi,t)can be expressed as

w i(ηi,t)=1+ t t0i ∞m 10?P i(m,t′)w ji(ηl,k l)?(k l)ρ(ηl)dηl dk l dt′,(4) where?P i(m,t)is the probability that node i is selected for connection to a new node j at time t for given m and it is related toΠi in Eq.(1)by a factor of m.Here,t0i is the time at which the node i has been added to the system.w ji(ηl,k l)is the weight assigned to the link between node j and node i.?(k)andρ(η)are the probability distributions of k andη, respectively.According to the stochastic weight assignment scheme modelled by Eqs.(2) and(3),the weight w ji(ηl,k l),on the average,can be written as

w ji(ηl,k l)=p k i

ηi+ηl

,(5)

for the simple case of m=2.Generalization to arbitrary value of m is straightforward.

From the connectedness of the SF model,?P i(m,t),?(k)and k i(t)are given by[33,30]

?P i (m,t)=mΠi=

k i(t)

k i(t)=m

t0i √

ηi ]k i(t)?

1

t0i

)2?4ln2ln t

ηi

k i(t),(10)

leading to the same scaling behavior of w i(ηi,t)and k i(t),as observed in the simulation results.For p=1corresponding to the WSF model of YJB[30],the dynamical behavior of w i(ηi,t)deviates most from that of k i(t).For arbitrary m,w i(ηi,t)follows a similar form with m dependence coming into the second term on the right hand side of Eq.(9).

IV.DISCUSSION

Our model can be easily generalized to allow for a?tness-dependent link formation mechanism[31,32].In the basic model with?tness[31],the probabilityΠi that a new link is established with an existing node i is determined jointly by the node’s connectivity k i and ?tnessηi with

Πi=

ηi k i

log k

k?γ′,(12)

withγ′=2.255.Fig.4shows the numerical results for the total weight distribution P(w)for three di?erent values of p=0,0.5and1.It is found that P(w)follows the same generalized power law form as P(k),but with a di?erent exponentσ′that depends on p.For p>0,σ′<γ′.Only for p=0,P(w)and P(k)have the same exponent ofσ′=2.25～γ′.For the cumulative distribution P(x>w ij)of weights of individual links,the numerical results are similar to those shown in Fig.3.

In summary,we proposed and studied a model of weighted scale-free networks in which the weights assigned to links as the network grows are stochastically determined by the connectivity of nodes with probability p and by the?tness of nodes with probability1?p. The model leads to a power law probability distribution for the total weight characterized by an exponentσthat is highly sensitive to the probability p.If the weight is driven solely by the?tness,i.e.,p=0,P(w)follows the same scaling behavior of P(k)with the same exponentσ=γ.Similar results were also found in a generalized model with a?tness dependent link formation mechanism.An expression relating the total weight and the total connectivity of a node was derived analytically.The analytical result was used to explain the features observed in the results of numerical simulations.In closing,we note that although the total weight distribution P(w)and the connectivity distribution P(k)carry di?erent exponentsσandγfor p>0in our model,P(w)still follows a power law,i.e.,has the same functional form as P(k).The same feature was also found in the generalized model. However,one would expect that in some complex real systems even the functional forms of P(w)and P(k)may be di?erent.It remains a challenge to introduce simple and yet non-trivial models that give one behavior for the geometrical connection among the constituents and another behavior for the extend of connectivity between constituents.

ACKNOWLEDGMENTS

This work was supported by a DFG grant TR3000/3-3.One of us(P.M.H.)acknowledges the support from the Research Grants Council of the Hong Kong SAR Government under

grant number CUHK4241/01P.

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FIGURE CAPTIONS

Figure1:The weight distribution P(w)as a function of the total weight w on a log-log scale for di?erent values of p=0,0.1,0.5,1.0.The two solid lines are guide to the eye corresponding to the exponentsσ=2.4and3.0,respectively.

Figure2:The total weight w i(ηi,t)of a randomly selected node i with?tnessηi(=0.75)as a function of time t on a log-log scale for di?erent values of p=0,0.5,1.0.The solid line is a guide to the eye corresponding to an exponentσ=0.5.

Figure3:The cumulative distribution P(x>w ij)of the weights of individual links as a function of w ij on a log-linear plot for di?erent values of p=0,0.1,0.5,1.0.

Figure4:The weight distribution P(w)as a function of the total weight w on a log-log scale for di?erent values of p=0,0.5,1.0in a model with?tness-dependent link formation mechanism.The two solid lines are plotted according to the form of Eq.(12),but with an exponentσ′characterizing P(w)that takes on the values1.82and2.25respectively.

w 100101102103104

P (w )10-10

10-9

10-8

10-7

10-6

10-5

10-410-3

10-2

10-1

100

p=0p=0.1p=0.5p=1.0

-3.0-2.4Figure 1

Zheng et al.

t 104105106

w i (ηi ,t )

101

102

103104

p=1.0p=0.5p=0

0.5

Figure 2

Zheng et al.

W ij 0.0.2.4.6.8 1.0

P (x >w i j )10-4

10-3

10-210-1

100

p=0

p=0.1

p=0.5

p=1.0

Figure 3

Zheng et al.

w 100101102103104

P (w )10-9

10-8

10-7

10-6

10-5

10-4

10-310-2

10-1

100

p=0p=0.5p=1.0

-2.25-1.82Figure 4Zheng et al.

with复合结构专项练习96126

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2、 With the meal over ， we all went home.（with+名词+副词，作时间状语） 3、The master was walking up and down with the ruler under his arm。（with+名词+介词短语，作伴随状语。） The teacher entered the classroom with a book in his hand. 4、He lay in the dark empty house，with not a man ，woman or child to say he was kind to me.（with+名词+不定式，作伴随状语）He could not finish it without me to help him.（without+代词 +不定式，作条件状语） 5、She fell asleep with the light burning.（with+名词+现在分词，作伴随状语） Without anything left in the with结构是许多英 语复合结构中最常用的一种。学好它对学好复合宾语结构、不定式复合结构、动名词复合结构和独立主格结构均能起很重要的作用。本文就此的构成、特点及用法等作一较全面阐述，以帮助同学们掌握这一重要的语法知识。 二、with结构的用法 with是介词，其意义颇多，一时难掌握。为帮助大家理清头绪，以教材中的句子为例，进行分类，并配以简单的解释。在句子中with结构多数充当状语，表示行为方式，伴随情况、时间、原因或条件（详见上述例句）。 1.带着，牵着…… (表动作特征)。如： Run with the kite like this.

精神分裂症的发病原因是什么

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。

with复合宾语的用法(20201118215048)

with+复合宾语的用法 一、with的复合结构的构成 二、所谓"with的复合结构”即是"with+复合宾语”也即"with +宾语+宾语补足语” 的结构。其中的宾语一般由名词充当（有时也可由代词充当）；而宾语补足语则是根据 具体的需要由形容词，副词、介词短语，分词短语（包括现在分词和过去分词）及不定式短语充当。下面结合例句就这一结构加以具体的说明。 三、1、with +宾语+形容词作宾补 四、①He slept well with all the windows open.（82 年高考题） 上面句子中形容词open作with的宾词all the windows的补足语， ②It' s impolite to talk with your mouth full of food. 形容词短语full of food 作宾补。Don't sleep with the window ope n in win ter 2、with+宾语+副词作宾补 with Joh n away, we have got more room. He was lying in bed with all his clothes on. ③Her baby is used to sleeping with the light on.句中的on 是副词，作宾语the light 的补足语。 ④The boy can t play with his father in.句中的副词in 作宾补。 3、with+宾语+介词短语。 we sat on the grass with our backs to the wall. his wife came dow n the stairs,with her baby in her arms. They stood with their arms round each other. With tears of joy in her eyes ,she saw her daughter married. ⑤She saw a brook with red flowers and green grass on both sides. 句中介词短语on both sides 作宾语red flowersandgreen grass 的宾补， ⑥There were rows of white houses with trees in front of them.，介词短语in front of them 作宾补。 4、with+宾词+分词（短语 这一结构中作宾补用的分词有两种，一是现在分词，二是过去分词，一般来说，当分词所表 示的动作跟其前面的宾语之间存在主动关系则用现在分词，若是被动关系，则用过去分词。 ⑦In parts of Asia you must not sit with your feet pointing at another person.（高一第十课），句中用现在分词pointing at…作宾语your feet的补足语，是因它们之间存在主动关系，或者说point 这一动作是your feet发出的。 All the after noon he worked with the door locked. She sat with her head bent. She did not an swer, with her eyes still fixed on the wall. The day was bright,with a fresh breeze（微风）blowing. I won't be able to go on holiday with my mother being ill. With win ter coming on ,it is time to buy warm clothes. He soon fell asleep with the light still bur ning. ⑧From space the earth looks like ahuge water covered globe,with a few patches of land stuk ing out above the water而在下面句子中因with的宾语跟其宾补之间存在被动关系，故用过去分词作宾补：

精神分裂症的病因是什么

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。

(完整版)with的复合结构用法及练习

with复合结构 一. with复合结构的常见形式 1.“with+名词/代词+介词短语”。 The man was walking on the street, with a book under his arm. 那人在街上走着，腋下夹着一本书。 2. “with+名词/代词+形容词”。 With the weather so close and stuffy, ten to one it’ll rain presently. 天气这么闷热，十之八九要下雨。 3. “with+名词/代词+副词”。 The square looks more beautiful than even with all the light on. 所有的灯亮起来，广场看起来更美。 4. “with+名词/代词+名词”。 He left home, with his wife a hopeless soul. 他走了，妻子十分伤心。 5. “with+名词/代词+done”。此结构过去分词和宾语是被动关系，表示动作已经完成。 With this problem solved, neomycin 1 is now in regular production. 随着这个问题的解决，新霉素一号现在已经正式产生。 6. “with+名词/代词+-ing分词”。此结构强调名词是-ing分词的动作的发出者或某动作、状态正在进行。 He felt more uneasy with the whole class staring at him. 全班同学看着他，他感到更不自然了。 7. “with+宾语+to do”。此结构中，不定式和宾语是被动关系，表示尚未发生的动作。 So in the afternoon, with nothing to do, I went on a round of the bookshops. 由于下午无事可做，我就去书店转了转。 二. with复合结构的句法功能 1. with 复合结构，在句中表状态或说明背景情况，常做伴随、方式、原因、条件等状语。With machinery to do all the work, they will soon have got in the crops. 由于所有的工作都是由机器进行，他们将很快收完庄稼。（原因状语） The boy always sleeps with his head on the arm. 这个孩子总是头枕着胳膊睡觉。（伴随状语）The soldier had him stand with his back to his father. 士兵要他背对着他父亲站着。（方式状语）With spring coming on, trees turn green. 春天到了，树变绿了。（时间状语） 2. with 复合结构可以作定语 Anyone with its eyes in his head can see it’s exactly like a rope. 任何一个头上长着眼睛的人都能看出它完全像一条绳子。 【高考链接】 1. ___two exams to worry about, I have to work really hard this weekend.（04北京） A. With B. Besides C. As for D. Because of 【解析】A。“with+宾语+不定式”作状语，表示原因。 2. It was a pity that the great writer died, ______his works unfinished. (04福建) A. for B. with C. from D.of 【解析】B。“with+宾语+过去分词”在句中作状语，表示状态。 3._____production up by 60%, the company has had another excellent year. (NMET) A. As B.For C. With D.Through 【解析】C。“with+宾语+副词”在句中作状语，表示程度。

With复合结构的用法小结

With复合结构的用法小结 with结构是许多英语复合结构中最常用的一种。学好它对学好复合宾语结构、不定式复合结构、动名词复合结构和独立主格结构均能起很重要的作用。本文就此的构成、特点及用法等作一较全面阐述，以帮助同学们掌握这一重要的语法知识。 一、with结构的构成 它是由介词with或without+复合结构构成，复合结构作介词with或without的复合宾语，复合宾语中第一部分宾语由名词或代词充当，第二 部分补足语由形容词、副词、介词短语、动词不定式或分词充当，分词可以是现在分词，也可以是过去分词。With结构构成方式如下： 1. with或without-名词/代词+形容词； 2. with或without-名词/代词+副词； 3. with或without-名词/代词+介词短语； 4. with或without-名词/代词+动词不定式； 5. with或without-名词/代词+分词。 下面分别举例： 1、She came into the room，with her nose red because of cold.（with+名词+形容词，作伴随状语） 2、With the meal over ，we all went home.（with+名词+副词，作时间状语） 3、The master was walking up and down with the ruler under his arm。（with+名词+介词短语，作伴随状语。）The teacher entered the classroom with a book in his hand. 4、He lay in the dark empty house，with not a man ，woman or child to say he was kind to me.（with+名词+不定式，作伴随状语）He could not finish it without me to help him.（without+代词+不定式，作条件状语） 5、She fell asleep with the light burning.（with+名词+现在分词，作伴随状语）Without anything left in the cupboard，shewent out to get something to eat.（without+代词+过去分词，作为原因状语） 二、with结构的用法 在句子中with结构多数充当状语，表示行为方式，伴随情况、时间、原因或条件（详见上述例句）。 With结构在句中也可以作定语。例如： 1.I like eating the mooncakes with eggs. 2.From space the earth looks like a huge water-covered globe with a few patches of land sticking out above the water. 3.A little boy with two of his front teeth missing ran into the house. 三、with结构的特点 1. with结构由介词with或without+复合结构构成。复合结构中第一部分与第二部分语法上是宾语和宾语补足语关系，而在逻辑上，却具有主谓关系，也就是说，可以用第一部分作主语，第二部分作谓语，构成一个句子。例如：With him taken care of，we felt quite relieved.（欣慰）→（He was taken good care of.）She fell asleep with the light burning. →（The light was burning.）With her hair gone，there could be no use for them. →（Her hair was gone.） 2. 在with结构中，第一部分为人称代词时，则该用宾格代词。例如：He could not finish it without me to help him. 四、几点说明： 1. with结构在句子中的位置：with 结构在句中作状语，表示时间、条件、原因时一般放在

精神分裂症应该怎么治疗

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

精神分裂症患者在怎样的情况下会自杀

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

with_的复合结构

with without 引导的独立主格结构 介词with without +宾语+宾语的补足语可以构成独立主格结构，上面讨论过的独立主格结构的几种情况在此结构中都能体现。 A．with+名词代词+形容词 He doesn’t like to sleep with the windows open. 他不喜欢开着窗子睡觉。 = He doesn’t like to sleep when the windows are open. He stood in the rain, with his clothes wet. 他站在雨中，衣服湿透了。 = He stood in the rain, and his clothes were wet. 注意： 在“with+名词代词+形容词”构成的独立主格结构中，也可用已形容词化的-ing 形式或-ed形式。 With his son so disappointing，the old man felt unhappy. 由于儿子如此令人失望,老人感到很不快乐。 With his father well-known, the boy didn’t want to study. 父亲如此出名，儿子不想读书。 B．with+名词代词+副词 Our school looks even more beautiful with all the lights on. 所有的灯都打开时，我们的学校看上去更美。 = Our school looks even more beautiful if when all the lights are on. The boy was walking, with his father ahead. 父亲在前，小孩在后走着。 = The boy was walking and his father was ahead. C．with+名词代词+介词短语 He stood at the door, with a computer in his hand. 或 He stood at the door, computer in hand. 他站在门口，手里拿着一部电脑。 = He stood at the door, and a computer was in his hand. Vincent sat at the desk, with a pen in his mouth. 或 Vincent sat at the desk, pen in mouth. 文森特坐在课桌前，嘴里衔着一支笔。 = Vincent sat at the desk, and he had a pen in his mouth. D．with+名词代词+动词的-ed形式 With his homework done, Peter went out to play. 作业做好了，彼得出去玩了。 = When his homework was done, Peter went out to play. With the signal given, the train started. 信号发出了，火车开始起动了。 = After the signal was given, the train started. I wouldn’t dare go home without the job finished. 工作还没完成，我不敢回家。 = I wouldn’t dare go home because the job was not finished.

with的复合结构用法及练习

页眉内容 with复合结构 一. with复合结构的常见形式 1.“with+名词/代词+介词短语”。 The man was walking on the street, with a book under his arm. 那人在街上走着，腋下夹着一本书。 2. “with+名词/代词+形容词”。 With the weather so close and stuffy, ten to one it’ll rain presently. 天气这么闷热，十之八九要下雨。 3. “with+名词/代词+副词”。 The square looks more beautiful than even with all the light on. 所有的灯亮起来，广场看起来更美。 4. “with+名词/代词+名词”。 He left home, with his wife a hopeless soul. 他走了，妻子十分伤心。 5. “with+名词/代词+done”。此结构过去分词和宾语是被动关系，表示动作已经完成。 With this problem solved, neomycin 1 is now in regular production. 随着这个问题的解决，新霉素一号现在已经正式产生。 6. “with+名词/代词+-ing分词”。此结构强调名词是-ing分词的动作的发出者或某动作、状态正在进行。 He felt more uneasy with the whole class staring at him. 全班同学看着他，他感到更不自然了。7. “with+宾语+to do”。此结构中，不定式和宾语是被动关系，表示尚未发生的动作。 So in the afternoon, with nothing to do, I went on a round of the bookshops. 由于下午无事可做，我就去书店转了转。 二. with复合结构的句法功能 1. with 复合结构，在句中表状态或说明背景情况，常做伴随、方式、原因、条件等状语。With machinery to do all the work, they will soon have got in the crops. 由于所有的工作都是由机器进行，他们将很快收完庄稼。（原因状语） The boy always sleeps with his head on the arm. 这个孩子总是头枕着胳膊睡觉。（伴随状语）The soldier had him stand with his back to his father. 士兵要他背对着他父亲站着。（方式状语）With spring coming on, trees turn green. 春天到了，树变绿了。（时间状语） 2. with 复合结构可以作定语 Anyone with its eyes in his head can see it’s exactly like a rope. 任何一个头上长着眼睛的人都能看出它完全像一条绳子。 【高考链接】 1. ___two exams to worry about, I have to work really hard this weekend.（04北京） A. With B. Besides C. As for D. Because of 【解析】A。“with+宾语+不定式”作状语，表示原因。 2. It was a pity that the great writer died, ______his works unfinished. (04福建) A. for B. with C. from D.of 【解析】B。“with+宾语+过去分词”在句中作状语，表示状态。 3._____production up by 60%, the company has had another excellent year. (NMET) A. As B.For C. With D.Through 【解析】C。“with+宾语+副词”在句中作状语，表示程度。

我的精神分裂症形成和发展史

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。

引起精神分裂症的诱因有哪些

引起精神分裂症的诱因有哪些 精神分裂症作为一种高发疾病，给患者的健康带来了极大的危害，也让患者的家庭遭受着痛苦的折磨。精神分裂症虽然是一种精神类疾病，但是它给患者带来的创伤绝不亚于身体上的伤害。多了解一些有关精神分裂症疾病方面的知识，对于我们预防和治疗这种疾病，都有积极的意义。下面，请专家来为大家简单介绍一下，精神分裂症这种疾病发病诱因到底是什么： 精神分裂症诱因一：心理方面的因素。 人的心理方面的抵抗力如同自身的免疫系统，是一道天然的保护屏障。如果心理承受能力低下，当我们遭遇重大变故或者精神刺激的时候，就会发生严重的心理质变和扭曲，导致颓废、悲伤、痛苦，严重者就可能发生精神分裂症。 其实，影响心理承受能力的根本原因，还是在个人的性格方面。 精神分裂症诱因二：自身免疫系统的功能状况。 自身免疫系统就如同是一道坚固的堡垒，时刻抵御着外界的侵扰和威胁，保护着我们自身的身体健康。免疫力低下的人，很容易因外界环境因素的影响而发生器质性病变，比如有毒物质伤害神经递质，从而间接引发精神分裂症。因此，在生活和工作中，我们应当注意远离有毒物质和有污染的环境。 精神分裂症诱因三：社会因素。 人是一种社会性动物，在社会这个大的环境下生存和成长。因此，不可避免地影响着他人和被他人影响着。我们在成长中经历的各种重大事件，都会对自身的心理发生着潜移默化的影响。一个人若是长期处于悲观失望、极度痛苦的负面情绪中，就有可能在精神方面受到强烈的刺激，严重者就可能发生精神分裂症。 精神分裂症诱因四：遗传因素。 遗传因素也是导致精神分裂症的一个重要原因。有临床研究表明，精神分裂症患者中，有家族精神病史的患者占据着一个很大的比例。而且，精神分裂症的发病年龄段正在呈现逐渐年轻化的趋势。 总的来说，精神分裂症的发病原因非常复杂，这里仅仅例举了其中四个主要的原因。科学无止境，在精神分裂症的诱发原因方面，我们不了解的而还有很多，还有许多需要不断地去研究和探求的知识。但是，随着科学的而不断发展和进步，相信人类将来一定能克服这种精神疾病，迎来一个健康的精神面貌。