Non-Borrowing Students’ Perceptions of Student Loans and Strategies of Paying for College

With the notable shift from grants to loans over the past several decades, many researchers have argued the positive impact of financial aid on student college choice, enrollment, and persistence. However, literature indicates that students from economically disadvantaged backgrounds are less likely to take loans to finance postsecondary education than those from affluent conditions. Qualitative research on the reasons for non-borrowers’ aversion to loans and strategies for college payment is rather scant. This study explores 30 lower- or lower-middle-class non-borrowing students’ lived experiences surrounding student loans from a qualitative phenomenological research lens. Data are collected from semi-structured interviews. Data analysis shows four main reasons that the participants generally avoid borrowing as they decide where to attend and how to pay for college: parental influence, fear of economic burden, underestimation of the value of college education, and lack of information about the loan system. The strategies they employ for college payment include scholarships and grants, family support, part-time jobs, and prepaid college tuition programs. This study uses peer debriefing to ensure its trustworthiness. Limitations of this study and implications for future research and practice are discussed

Potential of Tocotrienols in the Prevention and Therapy of Alzheimer’s Disease

Currently there is no cure for Alzheimer’s disease (AD); clinical trials are underway to reduce amyloid generation and deposition, a neuropathological hallmark in brains of AD patients. While genetic factors and neuroinflammation contribute significantly to AD pathogenesis, whether increased cholesterol level is a causative factor or a result of AD is equivocal. Prenylation of proteins regulating neuronal functions requires mevalonate-derived farnesyl pyrophosphate (FPP) and geranylgeranyl pyrophosphate (GGPP). The observation that the levels of FPP and GGPP, but not that of cholesterol, are elevated in AD patients is consistent with the finding that statins, competitive inhibitors of 3-hydroxy-3-methylglutaryl coenzyme A (HMG CoA) reductase, reduce FPP and GGPP levels and amyloid β protein production in preclinical studies. Retrospective studies show inverse correlations between incidence of AD and the intake and serum levels of the HMG CoA reductase-suppressive tocotrienols; tocopherols show mixed results. Tocotrienols, but not tocopherols, block the processing and nuclear localization of sterol regulatory element binding protein-2, the transcriptional factor for HMG CoA reductase and FPP synthase, and enhance the degradation of HMG CoA reductase. Consequently, tocotrienols deplete the pool of FPP and GGPP and potentially blunt prenylationdependent AD pathogenesis. The anti-inflammatory activity of tocotrienols further contributes to their protection against AD. The mevalonate- and inflammation- suppressive activities of tocotrienols may represent those of an estimated 23,000 mevalonate-derived plant secondary metabolites called isoprenoids, many of which are neuroprotective. Tocotrienol-containing plant foods and tocotrienol derivatives and formulations with enhanced bioavailability may offer a novel approach in AD prevention and treatment

CAVL: Learning Contrastive and Adaptive Representations of Vision and Language

Visual and linguistic pre-training aims to learn vision and language representations together, which can be transferred to visual-linguistic downstream tasks. However, there exists semantic confusion between language and vision during the pre-training stage. Moreover, current pre-trained models tend to take lots of computation resources for fine-tuning when transferred to downstream tasks. In this work, we present a simple but effective approach for learning Contrastive and Adaptive representations of Vision and Language, namely CAVL. Specifically, we introduce a pair-wise contrastive loss to learn alignments between the whole sentence and each image in the same batch during the pre-training process. At the fine-tuning stage, we introduce two lightweight adaptation networks to reduce model parameters and increase training speed for saving computation resources. We evaluate our CAVL on six main downstream tasks, including Visual Question Answering (VQA), Visual Commonsense Reasoning (VCR), Natural Language for Visual Reasoning (NLVR), Region-to-Phrase Grounding (RPG), Text-to-Image Retrieval (TIR), and Zero-shot Text-to-Image Retrieval (ZS-TIR). Compared to baselines, we achieve superior performance and reduce the fine-tuning time by a large margin (in particular, 76.17%). Extensive experiments and ablation studies demonstrate the efficiency of contrastive pre-training and adaptive fine-tuning proposed in our CAVL

Primordial Non-Gaussianity and the NRAO VLA Sky Survey

The NRAO VLA Sky Survey (NVSS) is the only dataset that allows an accurate determination of the auto-correlation function (ACF) on angular scales of several degrees for Active Galactic Nuclei (AGNs) at typical redshifts $z \simeq 1$. Surprisingly, the ACF is found to be positive on such large scales while, in the framework of the standard hierarchical clustering scenario with Gaussian primordial perturbations it should be negative for a redshift-independent effective halo mass of order of that found for optically-selected quasars. We show that a small primordial non-Gaussianity can add sufficient power on very large scales to account for the observed NVSS ACF. The best-fit value of the parameter $f_{\rm NL}$, quantifying the amplitude of primordial non-Gaussianity of local type is $f_{\rm NL}=62 \pm 27$ ($1\,\sigma$ error bar) and $25<f_{\rm NL}<117$ ($2\,\sigma$ confidence level), corresponding to a detection of non-Gaussianity significant at the $\sim 3\,\sigma$ confidence level. The minimal halo mass of NVSS sources is found to be $M_{\rm min}=10^{12.47\pm0.26}h^{-1}M_{\odot}$ ($1\,\sigma$) strikingly close to that found for optically selected quasars. We discuss caveats and possible physical and systematic effects that can impact on the results.Comment: 6 pages, 5 figure

Learning Language-Conditioned Deformable Object Manipulation with Graph Dynamics

Multi-task learning of deformable object manipulation is a challenging problem in robot manipulation. Most previous works address this problem in a goal-conditioned way and adapt goal images to specify different tasks, which limits the multi-task learning performance and can not generalize to new tasks. Thus, we adapt language instruction to specify deformable object manipulation tasks and propose a learning framework. We first design a unified Transformer-based architecture to understand multi-modal data and output picking and placing action. Besides, we have introduced the visible connectivity graph to tackle nonlinear dynamics and complex configuration of the deformable object. Both simulated and real experiments have demonstrated that the proposed method is effective and can generalize to unseen instructions and tasks. Compared with the state-of-the-art method, our method achieves higher success rates (87.2% on average) and has a 75.6% shorter inference time. We also demonstrate that our method performs well in real-world experiments.Comment: submitted to ICRA 202

Review on a Practical Approach of Sustainable Urban Design Strategy in the Perspective of Conflict in Shanghai

As the abstract of the main parts of a doctoral dissertation, this paper tried to show the overall study skeleton: a sustainable urban design strategy could be investigated from two domains, the space construction and the social action. In the perspective of "conflict", according to the urban development of Shanghai, five conflict fields were proposed and the relevant empirical studies were implemented, focusing on the above two dimensions and combined closely with the stage characteristics of urban development to explore practical approaches of sustainable urban design. Also, the content framework of sustainable urban design strategies was formed based on the above study and enumerated briefly