The Relationship between Motivation and Academic Performance in Chiropractic Students

This study aimed to investigate the relationship between motivation and academic performance in chiropractic students. This was a cross-sectional study. Three hundred and sixty-two students were recruited from the 1st and 3rd quarters during the 2017-2018 academic year. Out of 362 students, 305 completed the Inventory of School Motivation (ISM). Total scores from the 1st quarter General Anatomy course and the 3rd quarter Immunology/Endocrinology course were used to measure the 1st quarter and 3rd quarter academic performance, respectively. The mean total motivation score for all students was 28.40 ± 3.79 (mean ± SD). There was no signi?cant difference in total motivation score between students in the two quarters (p > .05). The mean of the 1st quarter praise scores was statistically significantly higher than those of the 3rd quarter (p < .05). The means of three motivation subscale scores for females were signi?cantly higher than that for males (task, effort, and praise, p < .05) while the mean competition score for males was signi?cantly higher than that for females (p < .01). The linear analysis demonstrated a weak but statistically significant correlation of task (r = .11, p < .05) and effort (r = .13, p < .05) with academic performance indicating that task and effort were minor predictors of academic outcome (p < .05).There was a weak, but statistically significant positive correlation between the three motivation subscales and academic performance. Female students scored significantly higher on three motivation subscales while males scored higher on one

The Chaotic Attractor Analysis of DJIA Based on Manifold Embedding and Laplacian Eigenmaps

By using the techniques of Manifold Embedding and Laplacian Eigenmaps, a novel strategy has been proposed in this paper to detect the chaos of Dow Jones Industrial Average. Firstly, the chaotic attractor of financial time series is assumed to lie on a low-dimensional manifold that is embedded into a high-dimensional Euclidean space. Then, an improved phase space reconstruction method and a nonlinear dimensionality reduction method are introduced to help reveal the structure of the chaotic attractor. Next, the empirical study on the financial time series of Dow Jones Industrial Average shows that there exists an attractor which lies on a manifold constructed by the time sequence of Moving average convergence divergence; finally, Determinism Test, Poincaré section, and translation analysis are used as test approaches to prove both whether it is a chaos and how it works

A Continuum Model for Dislocation Climb

Dislocation climb plays an important role in understanding plastic deformation of metallic materials at high temperature. In this paper, we present a continuum formulation for dislocation climb velocity based on densities of dislocations. The obtained continuum formulation is an accurate approximation of the Green's function based discrete dislocation dynamics method (Gu et al. J. Mech. Phys. Solids 83:319-337, 2015). The continuum dislocation climb formulation has the advantage of accounting for both the long-range effect of vacancy bulk diffusion and that of the Peach-Koehler climb force, and the two longrange effects are canceled into a short-range effect (integral with fast-decaying kernel) and in some special cases, a completely local effect. This significantly simplifies the calculation in the Green's function based discrete dislocation dynamics method, in which a linear system has to be solved over the entire system for the long-range effect of vacancy diffusion and the long-range Peach-Koehler climb force has to be calculated. This obtained continuum dislocation climb velocity can be applied in any available continuum dislocation dynamics frameworks. We also present numerical validations for this continuum climb velocity and simulation examples for implementation in continuum dislocation dynamics frameworks

High affinity binding of H3K14ac through collaboration of bromodomains 2, 4 and 5 is critical for the molecular and tumor suppressor functions of PBRM1.

Polybromo-1 (PBRM1) is an important tumor suppressor in kidney cancer. It contains six tandem bromodomains (BDs), which are specialized structures that recognize acetyl-lysine residues. While BD2 has been found to bind acetylated histone H3 lysine 14 (H3K14ac), it is not known whether other BDs collaborate with BD2 to generate strong binding to H3K14ac, and the importance of H3K14ac recognition for the molecular and tumor suppressor function of PBRM1 is also unknown. We discovered that full-length PBRM1, but not its individual BDs, strongly binds H3K14ac. BDs 2, 4, and 5 were found to collaborate to facilitate strong binding to H3K14ac. Quantitative measurement of the interactions between purified BD proteins and H3K14ac or nonacetylated peptides confirmed the tight and specific association of the former. Interestingly, while the structural integrity of BD4 was found to be required for H3K14ac recognition, the conserved acetyl-lysine binding site of BD4 was not. Furthermore, simultaneous point mutations in BDs 2, 4, and 5 prevented recognition of H3K14ac, altered promoter binding and gene expression, and caused PBRM1 to relocalize to the cytoplasm. In contrast, tumor-derived point mutations in BD2 alone lowered PBRM1\u27s affinity to H3K14ac and also disrupted promoter binding and gene expression without altering cellular localization. Finally, overexpression of PBRM1 variants containing point mutations in BDs 2, 4, and 5 or BD2 alone failed to suppress tumor growth in a xenograft model. Taken together, our study demonstrates that BDs 2, 4, and 5 of PBRM1 collaborate to generate high affinity to H3K14ac and tether PBRM1 to chromatin. Mutations in BD2 alone weaken these interactions, and this is sufficient to abolish its molecular and tumor suppressor functions

Multiple tumor suppressors regulate a HIF-dependent negative feedback loop via ISGF3 in human clear cell renal cancer.

Whereas VHL inactivation is a primary event in clear cell renal cell carcinoma (ccRCC), the precise mechanism(s) of how this interacts with the secondary mutations in tumor suppressor genes, including PBRM1, KDM5C/JARID1C, SETD2, and/or BAP1, remains unclear. Gene expression analyses reveal that VHL, PBRM1, or KDM5C share a common regulation of interferon response expression signature. Loss of HIF2α, PBRM1, or KDM5C in VHL-/-cells reduces the expression of interferon stimulated gene factor 3 (ISGF3), a transcription factor that regulates the interferon signature. Moreover, loss of SETD2 or BAP1 also reduces the ISGF3 level. Finally, ISGF3 is strongly tumor-suppressive in a xenograft model as its loss significantly enhances tumor growth. Conversely, reactivation of ISGF3 retards tumor growth by PBRM1-deficient ccRCC cells. Thus after VHL inactivation, HIF induces ISGF3, which is reversed by the loss of secondary tumor suppressors, suggesting that this is a key negative feedback loop in ccRCC. © 2018, Liao et al

ISA-Net: Improved spatial attention network for PET-CT tumor segmentation

Achieving accurate and automated tumor segmentation plays an important role in both clinical practice and radiomics research. Segmentation in medicine is now often performed manually by experts, which is a laborious, expensive and error-prone task. Manual annotation relies heavily on the experience and knowledge of these experts. In addition, there is much intra- and interobserver variation. Therefore, it is of great significance to develop a method that can automatically segment tumor target regions. In this paper, we propose a deep learning segmentation method based on multimodal positron emission tomography-computed tomography (PET-CT), which combines the high sensitivity of PET and the precise anatomical information of CT. We design an improved spatial attention network(ISA-Net) to increase the accuracy of PET or CT in detecting tumors, which uses multi-scale convolution operation to extract feature information and can highlight the tumor region location information and suppress the non-tumor region location information. In addition, our network uses dual-channel inputs in the coding stage and fuses them in the decoding stage, which can take advantage of the differences and complementarities between PET and CT. We validated the proposed ISA-Net method on two clinical datasets, a soft tissue sarcoma(STS) and a head and neck tumor(HECKTOR) dataset, and compared with other attention methods for tumor segmentation. The DSC score of 0.8378 on STS dataset and 0.8076 on HECKTOR dataset show that ISA-Net method achieves better segmentation performance and has better generalization. Conclusions: The method proposed in this paper is based on multi-modal medical image tumor segmentation, which can effectively utilize the difference and complementarity of different modes. The method can also be applied to other multi-modal data or single-modal data by proper adjustment

Self-Intercalation Tunable Interlayer Exchange Coupling in a Synthetic Van Der Waals Antiferromagnet

One of the most promising avenues in 2D materials research is the synthesis of antiferromagnets employing 2D van der Waals (vdW) magnets. However, it has proven challenging, due in part to the complicated fabrication process and undesired adsorbates as well as the significantly deteriorated ferromagnetism at atomic layers. Here, the engineering of the antiferromagnetic (AFM) interlayer exchange coupling between atomically thin yet ferromagnetic CrTe2 layers in an ultra-high vacuum-free 2D magnetic crystal, Cr5Te8 is reported. By self-introducing interstitial Cr atoms in the vdW gaps, the emergent AFM ordering and the resultant giant magnetoresistance effect are induced. A large negative magnetoresistance (10%) with a plateau-like feature is revealed, which is consistent with the AFM interlayer coupling between the adjacent CrTe2 main layers in a temperature window of 30 K below the Néel temperature. Notably, the AFM state has a relatively weak interlayer exchange coupling, allowing a switching between the interlayer AFM and ferromagnetic states at moderate magnetic fields. This work represents a new route to engineering low-power devices that underpin the emerging spintronic technologies, and an ideal laboratory to study 2D magnetism