Deep learning questions can help selection of high ability candidates for universities

Selection of students for places at universities mainly depends on GCSE grades and predictions of A-level grades, both of which tend to favour applicants from independent schools. We have therefore developed a new type of test that would measure candidates’ ‘deep learning’ approach since this assesses the motivation and creative thinking that we look for in university students. We recruited 526 applicants to Oxford University and gave them a short commentary test and a learning style questionnaire. Specific deep learning approach questions correlated with results in the new test, and both predicted whether the candidate subsequently obtained a place at Oxford. Furthermore high scores on one open-ended commentary question, demanding arguments in favour of a case, produced a greater than 70% chance of obtaining a first class degree at the end of their course irrespective of the candidates’ type of school attended or GCSE scores. Candidates from State schools scored as well as those from Independent schools in both tests. Thus our test seemed to index candidates’ potential to succeed at a highly selective university, and might usefully be added to current selection procedures for such universities.     

Discriminant analysis of anthropometric and biomotor variables among elite adolescent female athletes in four sports

The aim of this study was to identify anthropometric and biomotor variables that discriminated among groups of elite adolescent female athletes aged 14.3 +/- 1.3 years (mean +/- s) from four different sports (tennis, n = 15; swimming, n = 23; figure skating, n = 46; volleyball, n = 16). The anthropometric variables included body mass, height, bi-epicondylar breadth of the distal extremity of the humerus and femur, maximal girth of the calf and biceps and the sum of five adipose skinfolds. The biomotor variables were maximal aerobic power, muscular endurance and flexibility of the trunk. Discriminant analysis revealed three significant functions (P < 0. 05). The first discriminant function primarily represented differences between figure skaters and all other groups of athletes. The other two underlined anthropometric and biomotor differences between swimmers and volleyball players and between tennis players and swimmers, respectively. After validation, the analysis showed that 88% of the athletes were correctly classified in their respective sports. Our model confirms that elite adolescent female athletes show physical and biomotor differences that clearly distinguish them according to their particular sport.     

Science instruction for the mildly handicapped: Direct instruction versus discovery teaching

The authors' purpose in this study was to compare the effectiveness of two instructional approaches on mildly handicapped and nonhandicapped students' science achievement. Students were assigned at random to one of two conditions: (a) direct instruction, and (b) discovery teaching. The content of the lessons remained constant across conditions and focused on such concepts as displacement, flotation, variable, controlled experimentation, and scientific prediction. The results show that students in both groups learned equally well as measured by an immediate posttest. However, students in the discovery teaching condition outperformed their direct instruction counterparts on a retention test administered two weeks after the posttest. Finally, learning-disabled students in the discovery condition performed better than their direct-instruction counterparts on a performance-based measure designed to assess generalization. Implications for research and for practice are discussed.     

畅想无线网络的应用

2005年7月,美国国家自然科学基金会NSF资助了一个项目。这个项目的目标是:整合大学、公司和政府中无线移动和传感器网络研究者的研究成果,创新网络结构,并且整理这些成果成为一个连贯的议程。这个计划极大地促进了无线网络的研究发展。这些研究者汇聚在一起,被称为NSF无线移动计划编制组WMPG。不久前,工作组发表了该项目的报告。从本期起,本刊将选择报告中的重点内容进行连续登载。     

Size and shape based chromosome separation in the inertial focusing device

In this paper, we use a spiral channel inertial focusing device for isolation and purification of chromosomes, which are highly asymmetric. The method developed is proposed as a sample preparation process for transchromosomic research. The proposed microfluidics-based chromosome separation approach enables rapid, label-free isolation of bioactive chromosomes and is compatible with chromosome buffer. As part of this work, particle force analysis during the separation process is performed utilizing mathematic models to estimate the expected behavior of chromosomes in the channel and the model validated with experiments employing fluorescent beads. The chromosome sample is further divided into subtypes utilizing fluorescent activated cell sorting , including small condensed chromosomes, single chromosomes, and groups of two chromosomes (four sister chromatids). The separation of chromosome subtypes is realized based on their shape differences in the spiral channel device under high flow rate conditions. When chromosomes become aligned in the shear flow, the balance between the inertial focusing force and the Dean flow drag force is determined by the chromosome projection area and aspect ratio, or shape difference, leading to different focusing locations in the channel. The achieved results indicate a new separation regime in inertial microfluidics that can be used for the separation of non-spherical particles based on particle aspect ratios, which could potentially be applied in fields such as bacteria subtype separation and chromosome karyotyping.