大学生的心理健康与人本教育

造成大学生心理问题的原因很多,从大学教育和管理的角度看,大学自主教育和管理模式的过度自由化,大学教师重业务、轻教育;重科研、轻管理的倾向,以及大学“全员育人”欠缺等,是不可忽视的重要原因。大学生心理健康教育是一个系统工程,必须坚持科学发展观,牢固树立“以人为本”的教育思想,做到提高心理健康教育的认识必须“以人为本”,开展心理健康教育坚持“以人为本”,创设心理健康发展的人文环境做到“以人为本”。     

试论大学生运动队管理中的心理契约构建

心理契约反映了组织与员工之间关于责任和承诺的一种期望,本文从心理契约的角度分析了对运动队管理的意义和作用,提出了应选择从确定价值目标观、设定契约构成、务实诚信履约等方面入手构建大学生运动队的管理。     

犯罪心理分析应用研究

犯罪心理分析作为一种新型的侦查手段,其理论研究及实践应用都尚未成熟,如何使犯罪心理分析更具可操作性是值得探索的问题.犯罪心理分析的运用可概括为"犯罪心理痕迹--犯罪信息--犯罪心理描绘--侦查对策……",在此基础上具体开展侦查活动,充分发挥其在控制犯罪活动中的作用.     

浅谈肢体残疾患者的康复护理

本文从心理护理、肢体残疾障碍护理、肢体残疾功能恢复护理等几个方面说明对肢体残疾患者的护理要求与具体做法,以帮助患者早日康复。     

当代大学生心理健康状况分析及对策

目前,大学生心理健康状况不容乐观,大学生的心理问题是多方面原因综合造成的。预防和解决大学生心理问题,应做好大学生的心理引导和研究工作,同时还应切实提高广大教职工心理健康教育的意识和能力,营造良好的校园环境,使我们所培养的学生能得到全面的发展,成为有用的人才。     

Reimagining Sutherland 80 years after white‐collar crime*

Eighty years ago, Edwin H. Sutherland conceptualized and defined white‐collar crime. In this article, I engage retrospectively with Sutherland's ideas and work to emphasize important aspects that continue to guide research today; to note where he was prescient as well as shortsighted. I center this discussion around “corporate crime” or crimes by business. Four main themes are discussed: 1) law and official responses to corporate offending—the data problem, 2) corporate crime and the life cycle of organizations, 3) psychological and trait‐based explanations, and 4) consequences of definitional ambiguity.     

Development and Validation of a Method Using Dried Oral Fluid Spot to Determine Drugs of Abuse

A liquid chromatography–mass spectrometry method using dried oral fluid spots was developed and validated for the simultaneous quantification of cocaine, benzoylecgonine, cocaethylene, amphetamine, and 3,4‐methylenedioxymethamphetamine. The oral fluid was applied to a Whatman 903 grade paper and submitted to a drying time of 2.5 h. The extraction procedure was optimized by chemometric approach using simplex centroid design. Spots were extracted with a mixture of acetonitrile, buffer, and methanol. Calibration curves covered a linear concentration range of 40–500 ng/mL. Validation parameters of linearity, precision, accuracy, selectivity, carryover, matrix effects, and stability were evaluated and showed satisfactory results. Spot homogeneity was also satisfactory, with less than 15% of deviation from nominal concentration. Spot volume did not influence accuracy when less than 100 μL of the sample was applied to the spot. The validation of the proposed method suggests a potential application in different scenarios in toxicology.     

Leveraging virtual machine introspection with memory forensics to detect and characterize unknown malware using machine learning techniques at hypervisor

The Virtual Machine Introspection (VMI) has emerged as a fine-grained, out-of-VM security solution that detects malware by introspecting and reconstructing the volatile memory state of the live guest Operating System (OS). Specifically, it functions by the Virtual Machine Monitor (VMM), or hypervisor. The reconstructed semantic details obtained by the VMI are available in a combination of benign and malicious states at the hypervisor. In order to distinguish between these two states, the existing out-of-VM security solutions require extensive manual analysis. In this paper, we propose an advanced VMM-based, guest-assisted Automated Internal-and-External (A-IntExt) introspection system by leveraging VMI, Memory Forensics Analysis (MFA), and machine learning techniques at the hypervisor. Further, we use the VMI-based technique to introspect digital artifacts of the live guest OS to obtain a semantic view of the processes details. We implemented an Intelligent Cross View Analyzer (ICVA) and implanted it into our proposed A-IntExt system, which examines the data supplied by the VMI to detect hidden, dead, and dubious processes, while also predicting early symptoms of malware execution on the introspected guest OS in a timely manner. Machine learning techniques are used to analyze the executables that are mined and extracted using MFA-based techniques and ascertain the malicious executables. The practicality of the A-IntExt system is evaluated by executing large real-world malware and benign executables onto the live guest OSs. The evaluation results achieved 99.55% accuracy and 0.004 False Positive Rate (FPR) on the 10-fold cross-validation to detect unknown malware on the generated dataset. Additionally, the proposed system was validated against other benchmarked malware datasets and the A-IntExt system outperforms the detection of real-world malware at the VMM with performance exceeding 6.3%.     

金融危机影响下职工心理关怀及工会对策

比金融危机更具冲击力的是由此衍生的心理危机。当企业因合并、经营困难等因素需要大规模裁减员工时,必然在职工中引发心理问题,直接影响企业劳动关系。因此,工会不仅要主动维护职工的经济利益,而且还要主动维护职工的精神文化权益,尤其要关注和解决职工存在的心理问题,为其提供心理关怀,促进职工心理和谐成长。     

大学生心理问题与违法犯罪行为的相关性研究

大学生群体犯罪问题日益严重.大学生学业、就业压力大、人际关系紧张等诸多因素直接引发相应的心理问题,压力的不可逆转、观念的缺乏更新和心理调节、适应能力的欠缺,以及受个体人格特质的左右,从而引发相应的行为问题.大学生违法犯罪行为的频繁发生也在所难免.因而大学生行为问题的预警与干预非常重要.