An intervention to improve provider-patient interaction at methadone maintenance treatment in China.

BackgroundThis study evaluated an intervention aiming to improve methadone maintenance therapy (MMT) service providers' interaction with their patients in China.MethodsSixty-eight MMT clinics were randomized to either an intervention or a control condition. Providers in the intervention group attended three group training sessions to enhance their communication skills. Trained providers were encouraged to practice the taught communication skills through provider-initiated individual sessions with their patients. A total of 418 service providers completed assessments from baseline to 24-month. Linear mixed-effects regression models were used to compare self-reported short-term and sustained improvement in provider-patient interaction between the intervention and the control conditions.ResultsThe intervention group service providers perceived significantly greater short-term and sustained improvement in provider-patient interaction compared to the control group service providers (estimated difference (±SE): 1.20 (0.24) and 1.35 (0.33), respectively; p-values < 0.0001). Providers' baseline job satisfaction was significantly associated with a greater perceived improvement in provider-patient interaction for both periods (reg. coef. (±SE): 0.02 (0.01) and 0.04 (0.01) for short-term and sustained periods, respectively; p-values < 0.01).ConclusionStudy findings suggest that the intervention could be beneficial for improving perceived provider-patient interaction in MMT programs. Service providers' job satisfaction should be addressed in training programs for the improvement of provider-patient interaction

Distributed Training Large-Scale Deep Architectures

Scale of data and scale of computation infrastructures together enable the current deep learning renaissance. However, training large-scale deep architectures demands both algorithmic improvement and careful system configuration. In this paper, we focus on employing the system approach to speed up large-scale training. Via lessons learned from our routine benchmarking effort, we first identify bottlenecks and overheads that hinter data parallelism. We then devise guidelines that help practitioners to configure an effective system and fine-tune parameters to achieve desired speedup. Specifically, we develop a procedure for setting minibatch size and choosing computation algorithms. We also derive lemmas for determining the quantity of key components such as the number of GPUs and parameter servers. Experiments and examples show that these guidelines help effectively speed up large-scale deep learning training

Efficient non-collinear antiferromagnetic state switching induced by orbital Hall effect in chromium

Recently orbital Hall current has attracted attention as an alternative method to switch the magnetization of ferromagnets. Here we present our findings on electrical switching of antiferromagnetic state in Mn3Sn/Cr, where despite the much smaller spin Hall angle of Cr, the switching current density is comparable to heavy metal based heterostructures. On the other hand, the inverse process, i.e., spin-to-charge conversion in Cr-based heterostructures is much less efficient than the Pt-based equivalents, as manifested in the almost one order of magnitude smaller terahertz emission intensity and spin current induced magnetoresistance in Cr-based structures. These results in combination with the slow decay of terahertz emission against Cr thickness (diffusion length of ~11 nm) suggest that the observed magnetic switching can be attributed to orbital current generation in Cr, followed by efficient conversion to spin current. Our work demonstrates the potential of light metals like Cr as an efficient orbital/spin current source for antiferromagnetic spintronics.Comment: 19 pages, 4 figure

Comparison of Radical Scavenging Activity, Cytotoxic Effects and Apoptosis Induction in Human Melanoma Cells by Taiwanese Propolis from Different Sources

Propolis is a sticky substance that is collected from plants by honeybees. We previously demonstrated that propolins A, B, C, D, E and F, isolated from Taiwanese propolis (TP), could effectively induce human melanoma cell apoptosis and were strong antioxidant agents. In this study, we evaluated TP for free radical scavenging activity by DPPH (1,2-diphenyl-2-picrylhydrazyl). The phenolic concentrations were quantified by the Folin–Ciocalteu method. The apoptosis trigger activity in human melanoma cells was evaluated. TP contained a higher level of phenolic compounds and showed strong capability to scavenge free radicals. Additionally, TP1g, TP3, TP4 and TP7 exhibited a cytotoxic effect on human melanoma cells, with an IC(50) of ∼2.3, 2.0, 3.3 and 3.3 μg/ml, respectively. Flow cytometric analysis for DNA fragmentation indicated that TP1g, TP2, TP3 and TP7 could induce apoptosis in human melanoma cells and there is a marked loss of cells from the G2/M phase of the cell cycle. To address the mechanism of the apoptosis effect of TP, we evaluated its effects on induction of apoptosis-related proteins in human melanoma cells. The levels of procaspase-3 and PARP [poly(ADP-ribose) polymerase] were markedly decreased. Furthermore, propolins A, B, C, D, E and F in TP were determined using HPLC. The results indicate that TP is a rich source of these compounds. The findings suggest that TP induces apoptosis in human melanoma cells due to its high level of propolins