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171.
姚琦  马华维  阎欢  陈琦 《心理科学进展》2014,22(10):1647-1659
以社交网络的典型代表Facebook为例, 以社交网络用户个体行为为着眼点, 从个体使用社交网络的动机、社交网络用户个体行为的主要表现及其影响因素和结果变量四个方面, 梳理国外心理学领域有关社交网络的最新研究成果。今后研究可以在社交网络用户个体行为的测量、样本代表性、线上和线下社交网络的交互作用、具体人格特质变量的预测作用以及对社交网络功能的动态考察等方面推进已有研究。  相似文献   
172.
生命意义感获取的心理机制及其影响因素   总被引:1,自引:0,他引:1  
生命意义感体验对个体身心健康有重要的影响,其相关研究也已开始受到心理学各个领域的广泛关注。生命意义感获得与维持的理论研究主要是包括意义感层次模型、意义感构建模型及意义感维持与流动模型。大五人格、心理模拟、积极/消极情绪和亲社会行为是影响个体生命意义感体验的主要因素。未来研究要进一步探讨生命意义感产生的影响因素,完善相关的理论模型,并要从时间序列的角度探讨意义感的产生过程,并对生命意义感获得及维持的跨文化差异进行探讨。  相似文献   
173.
为了考察中低功能自闭症儿童在动态条件下的多目标注意加工特点,研究采用多目标追踪实验范式,具体追踪任务采用多目标随机运动和碰撞反弹算法。实验设计为两因素混合设计,组间变量为年龄和性别匹配的中低功能自闭症和正常儿童组,组内变量为追踪目标数量(分别为1、2、3、4个目标),因变量为被试在多目标追踪任务中的追踪正确率和追踪容量。结果发现:(1)中低功能自闭症儿童在目标数量为1到目标数量为4时的正确率均明显低于正常儿童,且标准差变异较大,中低功能自闭症儿童的多目标的持续追踪能力和稳定性存在一定的缺陷;(2)当目标数量为1时,正常组儿童与中低功能自闭症儿童的追踪容量差异不显著;目标为2、3、4时,两组追踪容量差异均显著。不同目标数量情况下中低功能自闭症儿童平均的注意容量为0.83~1.24个(平均容量约为1个)明显低于正常儿童的0.95~3.72个(最大容量接近4个)。中低功能自闭症儿童在多目标追踪上表现为单焦点注意加工的特点,存在一定程度的注意转移缺陷。  相似文献   
174.
通过随机取样的方法选取大连市三所幼儿园553名3~6岁幼儿为测查对象,采用问卷方式探讨了家长教育价值观、父母教养方式、儿童气质以及儿童人格之间的关系。本研究构建了一个有调节的中介模型,即父母教养方式在教育价值观和儿童人格间起中介作用,这一中介作用受到儿童自身气质特点的调节。结果表明:(1)教育价值观关系性维度正向预测了儿童人格的智能特征;教育价值观好行为维度正向预测了儿童人格的情绪稳定性;(2)教养方式不一致性维度在关系性与智能特征的关系中起中介作用;教养方式溺爱性维度在好行为与情绪稳定性的关系中起中介作用;(3)气质的情绪性维度和反应性维度分别调节了教养方式不一致性和溺爱性的中介作用。  相似文献   
175.
时间压力是现代社会中人们经常面对的重要问题。以往研究认为时间压力只会产生消极影响, 然而现有研究发现时间压力也会产生积极影响。总结以往研究, 介绍了时间压力的概念和测量方式, 分别阐述了时间压力的损耗作用和促进作用, 并用注意焦点理论、激活理论、维生素模型和挑战?阻碍模型等理论解释时间压力的双刃效应。未来研究应该进一步关注:(1)基于时间心理账户开展时间压力的分类研究; (2)时间压力促进作用的动机和情绪双路径机制; (3)探寻有效缓解时间压力损耗作用的机制。  相似文献   
176.
领导情绪对员工绩效有非常重要的影响, 但并非总是遵循“对称假设”。在特定条件下, 领导表达的消极情绪对员工绩效起到积极作用。情绪即社会信息模型(EASI)可以通过情绪表达者、情绪接受者、组织氛围和组织文化四个角度解释这一不对称现象, 但也存在局限性。文章在以往研究的基础上, 从情绪和认知两条路径出发, 对领导情绪和员工绩效间的中介机制及影响因素进行了系统梳理, 并提出了一个整合模型。未来研究应该关注:领导消极情绪表达的时机和程度, 不同类型的消极情绪对员工绩效的影响, 员工情绪反应的差异性。  相似文献   
177.
对天津某高校大二3个教学班77名被试,采用教育实验法探讨了传统教学法、归因训练干预、活动教学法在大学生英语课堂教学中学业情绪的激发与调节情况。结果表明:传统教学法无显著影响;归因训练干预后,学生的焦虑、气愤、放松、自豪、厌烦、失望和兴趣等学业情绪有显著改变;活动教学后,学生的焦虑、羞愧、厌烦、愉快和兴趣等学业情绪有显著改变。实施后两种教学法后,正性情绪得分均有所提高,负性情绪得分均有所下降。两种教学法在激发与调节学业情绪的效果上各有侧重。  相似文献   
178.
为了探讨重症免疫性血小板减少性紫癜(ITP)的治疗方案,回顾性分析118例接受激素(92例)或丙种球蛋白(16例)或rhTPO(10例)治疗患者的临床资料,分析疗效及不良反应.结果显示:(1)激素组,丙种球蛋白组和rhTPO组总有效率分别为76.1%、81.3%和70%,组间差异无统计学意义.复发组有效率(67.3%)明显低于初治组(83.3%,P<0.05),PAIgG伴PAIgM升高组有效率明显低于不伴PAIgM升高组(P<0.05);(2)血小板达峰时间:激素组为(5.70±3.68)d,丙种球蛋白组为(4.31±0.75)d,rhTPO组为(5.00±1.63)d,激素组与丙种球蛋白组间差异有统计学意义(P<0.05);(3)不良反应:激素组均出现类库欣综合征表现,丙种球蛋白组未见不良反应,1例(10%)rhTPO组患者出现轻度转氨酶增高.总之,丙种球蛋白和rhTPO治疗成人重症ITP疗效好,不良反应轻微.  相似文献   
179.
目前尚不能根治哮喘,然而长期管理有助于达到哮喘控制,哮喘教育是其重要组成部分.哮喘教育内容应包括哮喘的诊断、预防及治疗相关的知识、技能.应当采取个体化、循序渐进的教育方式,集体教育是个体化教育重要的补充.  相似文献   
180.
Rodent studies have suggested that “pattern separation,” the ability to distinguish among similar experiences, is diminished in a subset of aged rats. We extended these findings to the human using a task designed to assess spatial pattern separation behavior (determining at time of test whether pairs of pictures shown during the study were in the same spatial locations). Using a standardized test of word recall to divide healthy aged adults into impaired and unimpaired groups relative to young performance, we demonstrate that aged impaired adults are biased away from pattern separation and toward pattern completion, consistent with the rodent studies.Memory impairment is a common complaint among aging individuals, yet the variability within the aging population is great in both rats (Gallagher et al. 2006; Robitsek et al. 2008) and humans (Hilborn et al. 2009). A rodent model of aging (Gallagher et al. 2006; Wilson et al. 2006) has demonstrated that ∼50% of healthy rats qualify as cognitively “impaired” by scoring outside the range of the young performance in a standard protocol (Gallagher et al. 1993). The other half, the “unimpaired” rats, perform on par with young adults, demonstrating a natural degree of variability in cognitive aging. In this study, we sought to capitalize on the variability observed in the aging of both rats and humans in a study of spatial pattern separation.One source of variability in memory performance is hypothesized to be tied to changes in the input to the dentate gyrus (DG), which has been shown in the rat to be affected by the aging process. Smith et al. (2000) reported a selective impairment in layer II entorhinal input into the DG and CA3 regions of the hippocampus in rats with cognitive impairment. Similarly, the number of synapses in the outer receiving layer of DG was reduced in autopsied aged brains and correlated with earlier performance on a delayed recall task (Scheff et al. 2006). Finally, in a human imaging study, Small et al. (2002) observed that 60% of their aging sample demonstrated diminished MRI signal in the hippocampal region (including the DG) and also had a greater decline in memory performance. These findings support the notion that changes in the DG associated with aging may affect memory performance.The DG may be particularly important for the computations that underlie pattern separation (Treves and Rolls 1994; McClelland et al. 1995; Norman and O''Reilly 2003). “Pattern separation” refers to the process by which similar inputs are stored as distinct, nonoverlapping representations. In contrast, “pattern completion” refers to the process by which an existing representation can be reinstated by the presentation of a partial or degraded cue. Numerous studies in the rodent have identified the importance of the DG for pattern separation using electrophysiological methods (Leutgeb et al. 2004, 2005, 2007; Leutgeb and Leutgeb 2007), immediate early gene expression (Vazdarjanova and Guzowski 2004), lesions (Lee et al. 2005; Gilbert and Kesner 2006; Goodrich-Hunsaker et al. 2008), and even genetic manipulations (Cravens et al. 2006; Kubik et al. 2007; McHugh et al. 2008). Human neuroimaging has also recently identified activity in the DG (and CA3 regions of the hippocampus) in an object pattern separation task (Kirwan and Stark 2007; Bakker et al. 2008).Given the importance of the DG in pattern separation and its vulnerability to changes that occur with aging, studies have begun to examine pattern separation in older adults. Our laboratory has designed a task to examine object-based pattern separation performance in humans (Kirwan and Stark 2007). In this task, pictures of objects were presented either once or repeatedly throughout the task. Critically, some of the items presented were lures that were similar but not identical to previously shown items. The overlapping features of the lures more heavily engaged pattern separation processes. In young adults, functional magnetic resonance imaging (fMRI) activity in the DG was sensitive to the lures, indicating a role in pattern separation processes in both an explicit (Kirwan and Stark 2007) and implicit (Bakker et al. 2008) version of this task. Toner et al. (2009) used the explicit version of this task to demonstrate that older adults showed a greater tendency to identify lures as “old” (repeated) relative to young adults. These findings were also recently replicated in our laboratory (Yassa et al., in press), with the additional demonstration that older adults exhibit greater fMRI CA3/DG activity for the lures during both encoding and retrieval.Since object-based pattern separation appears to be modulated by the DG in humans, we wondered if these findings could be extended to spatial pattern separation. Rodent studies have demonstrated that the DG has a particular role in spatial pattern separation (Gilbert et al. 2001; Kesner et al. 2004). Specifically, Hunsaker et al. (2008) placed rats with localized DG lesions in an environment with two objects spaced 60 cm apart. When the animals were later placed in the same environment with the same objects now placed 40 cm apart, DG-lesioned animals (unlike control animals) did not re-explore the objects or environment. These data suggest that the DG-lesioned rats were not able to discriminate between the training and test environments. That is, they were impaired in spatial pattern separation. Since converging evidence suggests that one feature of the aging process can be characterized as a DG knockdown, we modified this task design for humans to test spatial pattern separation performance in older adults. While the Hunsaker et al. (2008) task emphasized the distance between the two objects as the source of interference creating a greater need for pattern separation, the paradigm presented here moves an object in any direction, changing both the distance and the angle (i.e., changing more of the spatial relations). We posit that this amount of movement (close, medium, or far) may place similar demands on spatial pattern separation processes as in the rodent task.The present study included 20 young adults (mean age 19.9 yr, range 18–27 yr) and 30 aged adults (mean age 70.4 yr, range 59–80 yr). Aged adults completed a battery of standardized neuropsychological tests, including the Mini-Mental State Exam (Folstein et al. 1975), Rey Auditory–Verbal Learning Task (RAVLT) (Rey 1941), Digit Span, Vocabulary, and Matrices subtests from the Wechsler Adult Intelligence Scale III (Wechsler 1997). The Vocabulary and Matrices scores were entered into a weighted formula along with age, gender, and education to derive estimated IQ scores (Schoenberg et al. 2003). All aged participants scored within the normal age-adjusted ranges on these measures and were cognitively intact. Younger adults also completed the RAVLT and scored within the normal age-adjusted range. These data are presented in Table 
YoungAged (AU)Aged (AI)
UnimpairedImpaired
Years of age19.9 (2.4)69.1 (5.2)72.9 (4.1)
Years of education14.1 (1.7)a16.7 (1.8)15.5 (2.9)
Gender (male/female)3M/17F6M/14F5M/5F
RAVLT total performance53.5 (6.7)56.2 (6.4)43.4 (6.1)b
RAVLT immediate performance12.1 (1.9)12.2 (1.5)8.3 (1.9)b
RAVLT delay performance11.8 (1.4)11.8 (1.6)6.5 (1.7)b
Estimated IQ120.8 (5.5)115 (6.7)b
Digit span performance18.9 (4.5)17 (3.8)
Mini-Mental State examination28.6 (0.9)28.3 (0.9)
Open in a separate windowAll data are reported as mean (SD).aAn unpaired t-test revealed higher years of education for the aged adults (16.3, SD 2.3) than the young adults (14.1, SD 1.7), t(48) = 3.7, P < 0.001.bIn addition, unpaired t-tests showed a poorer performance for the AI group relative to the AU group for RAVLT Total t(28) = 5.2, P < 0.0001, RAVLT Immediate t(28) = 6.3, P < 0.0001, and RAVLT Delay t(28) = 8.6, P < 0.0001. Although there is a group difference in IQ t(26) = 2.5, P < 0.05, these are largely overlapping distributions, and the AI group''s IQ scores are certainly within normal limits. In addition, there was no relationship between IQ scores and performance on any of the tasks or other measures we used.The Spatial Pair Distance (SPD) task consisted of 10 study and test blocks for a total of 100 test pairs. Participants studied 10 unique pairs of pictures per block and were then tested on whether each of the 10 pairs was in the same or different locations compared to the study session. During the study session, participants viewed pairs of pictures for 2 sec each and were told to “try to remember the location of the pictures.” During the test session, participants were told to indicate (with a key press) whether the pictures were in the same location as before or whether one of the pictures was in a different location. They were not told which of the two pictures might change position and the test was self-paced. Critically, for the different trials, only one picture of the pair changed location. It could be moved a small amount (close; 10%–20% of the screen; 2.64°–5.72° of visual angle), a moderate amount (medium; 25%–35% of the screen; 6.64°–9.38° of visual angle), or a large amount (far; 40%–60% of the screen; 10.62°–15.94° of visual angle) as shown in Figure 1. We limited the placement of the pictures between 10% and 90% of the screen so that the images were never placed along the edge of the computer screen. For the different condition, one of the images was moved in the x-coordinate by a percentage of the screen (i.e., 10%–20% in the close condition) and in the y-coordinate by a percentage of the screen (i.e., 10%–20% in the close condition), while the other image remained in its original location.Open in a separate windowFigure 1.SAME and DIFFERENT (separated into close, medium, and far amounts of movement) conditions for the Spatial Paired Distance task. The dashed-line box demonstrates the original location of the second picture, but was not shown to the participants.The probability to respond “different” for the SAME and three DIFFERENT (close, medium, and far) conditions for young and aged adults is shown in Figure 2A. A 2 × 4 analysis of variance (ANOVA) with group (young and aged adults) as a between-group factor and condition (same, close, medium, far) as a within-group factor revealed a main effect of condition, F(3,192) = 35.62, P < 0.0001. A post-hoc trend analysis revealed a positive linear trend across the four conditions, r2 = 0.62, P < 0.0001. There was no effect of group or an interaction, indicating no overall difference in spatial pattern separation ability between young and aged adults.Open in a separate windowFigure 2.(A) The mean proportion correct for each of the four conditions. There is a main effect of Condition, with a linear trend of increasing DIFFERENT responses across the conditions, but no difference between the younger adults and aged adults. (B) When the aged adults are separated according to their RAVLT Delay performance into impaired (AI) and unimpaired (AU), the AI adults perform significantly worse than both the young and the AU adults on the three DIFFERENT conditions. (C) Averaging the groups'' performance on the DIFFERENT trials emphasizes the finding that AI performance is matched on the SAME condition and is selectively impaired on the DIFFERENT conditions that tax spatial pattern separation.Since we were interested in the variability associated with healthy aging, we explored the aged group further. While rats are typically divided into impaired and unimpaired groups based on their performance in the Morris water maze (Gallagher et al. 1993), we divided the aged group into aged unimpaired (AU) and aged impaired (AI) based on their RAVLT delayed word learning performance. Importantly, the aged impaired individuals scored within the normal range for their own age group (ages 60–80). Aged unimpaired participants scored within the normal range for young individuals (ages 20–29) on the delayed test of the RAVLT (mean words recalled 11.8, range 9–15), whereas aged impaired individuals scored more than 1 standard deviation below these norms (mean words recalled 6.5, range 5–8). Thus, the aged impaired group was not clinically impaired and only mildly impaired relative to the young. While the aged unimpaired (69.1 yr, range 59–78) group is marginally different from the aged impaired (72.9 yr, range 67–80) group, t(28) = 2.02, P = 0.053, there was not a significant correlation (r2 = 0.06, ns) between performance on the DIFFERENT conditions and age as might be expected if age alone were responsible for the pattern separation impairments reported here. These data are presented in Figure 2B.We entered the aged unimpaired and impaired groups into a 3 × 4 ANOVA with Group (Young, AI, and AU) and Condition as factors. We found a main effect of Condition as before, F(3,188) = 29.1, P < 0.0001. Critically, we also found an effect of Group, F(2,188) = 4.7, P < 0.05, such that the aged impaired group performed worse on the DIFFERENT conditions. We then calculated a separation bias score by averaging the three DIFFERENT conditions together (Fig. 2C) and analyzed these scores with a 2 × 2 ANOVA with Group and Condition as factors. Again, there was a main effect of Group F(2,94) = 4.7, P < 0.05; a main effect of Condition, F(1,94) = 500.8, P < 0.0001; and an interaction, F(2,94) = 4.7, P < 0.05. Bonferroni-corrected post-tests identified that the AI group was significantly impaired on the DIFFERENT trials compared to the AU group, t(94) = 4.1, P < 0.001; and the Young group, t(94) = 1.9, P < 0.05. These analyses all emphasize the same finding, namely, that AI individuals are impaired on the conditions taxing spatial pattern separation (i.e., DIFFERENT), but are not impaired on the condition that does not tax separation per se (i.e., SAME).Using the RAVLT delayed recall performance to divide the aged group into AI and AU was an effective way to capture some of the individual variability in memory performance exhibited in the aged group. Indeed, there was a strong correlation between the aged impaired RAVLT scores and their performance on the DIFFERENT trials. We entered the RAVLT delayed recall scores into a linear regression with their performance on the average of the DIFFERENT trials and found a positive linear correlation such that as RAVLT delayed recall scores increased, performance on the different trials increased, r2 = 0.28, P < 0.01 (Fig. 3A). When the AI and AU groups were split, we observed that the AI group''s correlation remained reliable, r2 = 0.40, P < 0.05, while the AU group no longer exhibited a significant correlation, r2 = 0.03, ns. These data support the notion that spatial pattern separation performance may be a sensitive index of memory variability in aging.Open in a separate windowFigure 3.For the aged group, there is a positive relationship between SPD different trial performance and RAVLT delay performance (A), SPD different trial performance and MS separation score performance (B), and MS separation score performance and RAVLT delay performance (C). These positive relationships indicate some shared underlying process that may be captured by individual differences in memory performance during the course of aging.Since we collected additional behavioral measures on the same sample, we sought to determine if spatial pattern separation performance and RAVLT delayed recall performance might predict object pattern separation performance. Twenty-eight of the aged adults also participated in the object pattern separation paradigm as detailed by Yassa et al. (in press). Briefly, participants encoded everyday objects by simply making an indoor/outdoor judgment. During the test session, they viewed the same object (REPEATS), similar objects (LURES), and new objects (FOILS). They were required to make an “old,” “similar,” or “new” judgment for each item. We then computed a separation bias score by subtracting the probability of making “similar” responses to the FOILS from the probability of making “similar” responses to LURES, that is, p(“similar”) | LURE − p(“similar”) | FOIL. As reported by Yassa et al. (in press) the separation bias in the aging group was reduced relative to young adults, consistent with the Toner et al. (2009) findings.If spatial pattern separation as assessed by the SPD task is engaging an underlying process similar to that engaged in object pattern separation, we would predict a positive relationship between SPD and object mnemonic similarity (OMS) task performance. We computed average performance on the DIFFERENT conditions (close, medium, and far) and entered it into a linear regression with the OMS separation score for each individual in the aged group. We observed a positive relationship, r2 = 0.26, P < 0.01, as shown in Figure 3B. Likewise, we hypothesized a positive relationship between the OMS separation score and RAVLT delay performance, since we observed such a relationship with SPD performance. We entered these data into a linear regression and again observed a positive relationship, r2 = 0.22, P < 0.05 (with one OMS outlier greater than two SDs removed), as shown in Figure 3C. We also examined the relationship between SPD performance and Digit Span performance and estimated IQ in the aged group, but we did not find any significant correlations. These data indicate that these measures of both object and spatial pattern separation are behavioral manifestations of a similar underlying process that may also be somewhat accounted for by RAVLT delay recall performance.One pertinent question is whether RAVLT performance would predict SPD performance in the Young group, making it a sensitive measure regardless of aging per se. When we examined this question by entering SPD performance on the average of the DIFFERENT conditions and RAVLT delay performance into a linear regression (two SPD outliers greater than two SDs removed), we found no evidence for this hypothesis (r2 = 0.02, ns). Likewise, it might appear circular to define the AI group based on their poorer RAVLT memory performance and then identify poorer performance on the SPD task. However, the AI versus AU difference is selective for the DIFFERENT condition, yet performance is matched for the SAME condition. One would expect both the SAME and DIFFERENT conditions to be similarly adversely affected if a general memory impairment could account for the poorer AI performance.We suggest that these data support the notion of an impairment in spatial pattern separation processing in AI individuals. Ideally, we would have predicted a gradient of this effect, with more severe impairments in performance in the Close condition and matched performance in the Far condition. Unfortunately, the performance in the Close condition is near the floor, with all groups hovering around chance performance (50%). This potential floor effect may be obscuring a greater deficit in the Close condition for the AI group. On the other end, performance on the Far condition may be suffering a bit from a ceiling effect. Performance in the Far condition is not much better than the same condition in any group, and that same performance is only ∼74% for each group. Therefore, the difficulty associated with this task may be such that we cannot create an “easy” enough Far condition to increase the percentage correct. Indeed, pilot testing on manipulations of this task (moving both items at test instead of just one, for example) did not result in greater accuracy performance for older or younger adults. While these data are not able to speak to a gradient of spatial pattern separation, we would argue that the selective impairments for the AI group for the DIFFERENT condition still reflect a deficit in spatial pattern separation processes.The Spatial Paired Distance task presented here appears to be a measure that is sensitive to individual variations in memory performance associated with aging. The dentate gyrus seems a likely candidate for the source of this variability given its involvement in rodent (Small et al. 2004) and human aging studies (Small et al. 2002). Future research quantifying the structural and functional integrity of the dentate gyrus and other medial temporal lobe structures may elucidate those relationships with this task. Whether the variability associated with this task is a source of natural variation in the aged population or a precursor to mild cognitive impairment and possibly Alzheimer disease (AD) is also not clear. Longitudinal assessment of these or other individuals would be required to determine whether those in the AI group were more likely to develop AD. If such is the case, then the SPD and object mnemonic similarity tasks may be particularly useful for early detection and diagnosis of pathological changes associated with dementia. Similarly, these tasks may be advantageous for use as outcome measures in clinical trials of new medications aimed at addressing these changes.  相似文献   
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