Synthesis, Characterization, and Functionality of Novel 2D Material Sn3P2

In recent years, two-dimensional (2D) materials have gained a lot of attention due to their potential applications in devices and their promise to revolutionize technology. In our group, we are capable of synthesizing such materials and study their properties. I have discovered a new material of the tin-phosphorus family that displays the 2D layered structure and therefore shows potential to be used in future devices due to this reduced dimensionality from the typical three-dimensional counterpart. This 2D structure may allow for new phenomena to emerge as there is no longer any interatomic interactions along the z- axis. Under this motivation, I studied the crystal growth and properties of this new 2D layered crystal, Sn3P2

Adversarially Trained Autoencoders for Parallel-Data-Free Voice Conversion

We present a method for converting the voices between a set of speakers. Our method is based on training multiple autoencoder paths, where there is a single speaker-independent encoder and multiple speaker-dependent decoders. The autoencoders are trained with an addition of an adversarial loss which is provided by an auxiliary classifier in order to guide the output of the encoder to be speaker independent. The training of the model is unsupervised in the sense that it does not require collecting the same utterances from the speakers nor does it require time aligning over phonemes. Due to the use of a single encoder, our method can generalize to converting the voice of out-of-training speakers to speakers in the training dataset. We present subjective tests corroborating the performance of our method

Controlling magnetic exchange and anisotropy by non-magnetic ligand substitution in layered MPX3 (M = Ni, Mn; X = S, Se)

Recent discoveries in two-dimensional (2D) magnetism have intensified the investigation of van der Waals (vdW) magnetic materials and further improved our ability to tune their magnetic properties. Tunable magnetism has been widely studied in antiferromagnetic metal thiophosphates MPX3. Substitution of metal ions M has been adopted as an important technique to engineer the magnetism in MPX3. In this work, we have studied the previously unexplored chalcogen X substitutions in MPX3 (M = Mn/Ni; X = S/Se). We synthesized the single crystals of MnPS3-xSex (0 < x < 3) and NiPS3-xSex (0 < x < 1.3) and investigated the systematic evolution of the magnetism with varying x. Our study reveals the effective tuning of magnetic interactions and anisotropies in both MnPS3 and NiPS3 upon Se substitution. Such efficient engineering of the magnetism provides a suitable platform to understand the low-dimensional magnetism and develop future magnetic devices

CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images

We assemble a dataset of Creative-Commons-licensed (CC) images, which we use to train a set of open diffusion models that are qualitatively competitive with Stable Diffusion 2 (SD2). This task presents two challenges: (1) high-resolution CC images lack the captions necessary to train text-to-image generative models; (2) CC images are relatively scarce. In turn, to address these challenges, we use an intuitive transfer learning technique to produce a set of high-quality synthetic captions paired with curated CC images. We then develop a data- and compute-efficient training recipe that requires as little as 3% of the LAION-2B data needed to train existing SD2 models, but obtains comparable quality. These results indicate that we have a sufficient number of CC images (~70 million) for training high-quality models. Our training recipe also implements a variety of optimizations that achieve ~3X training speed-ups, enabling rapid model iteration. We leverage this recipe to train several high-quality text-to-image models, which we dub the CommonCanvas family. Our largest model achieves comparable performance to SD2 on a human evaluation, despite being trained on our CC dataset that is significantly smaller than LAION and using synthetic captions for training. We release our models, data, and code at https://github.com/mosaicml/diffusion/blob/main/assets/common-canvas.m

Perceptions of Barriers to and Facilitators of Participation in Health Research Among Transgender People

Purpose: Although transgender people may be at increased risk for a range of health problems, they have been the subject of relatively little health research. An important step toward expanding the evidence base is to understand and address the reasons for nonparticipation and dropout. The aim of this study was to explore the perceptions of barriers to and facilitators of participation in health research among a sample of transgender people in San Francisco, CA, and Atlanta, GA. Methods: Twelve in-person focus groups (FGs) were conducted; six (three with transwomen, three with transmen) were conducted in San Francisco and six FGs were conducted in Atlanta (three with transwomen and three with transmen). FGs were audiorecorded, transcribed, and uploaded to MaxQDA software for analysis. A codebook was used to code transcripts; new codes were added iteratively as they arose. All transcripts were coded by at least 2 of the 4 researchers and, after each transcript was coded, the researchers met to discuss any discrepancies, which were resolved by consensus. Results: Among 67 FG participants, 37 (55%) identified as transmen and 30 (45%) identified as transwomen. The average age of participants was ?41 years (range 18?67) and the majority (61%) were non-Hispanic Whites. Several barriers that can hinder participation in health research were identified, including logistical concerns, issues related to mistrust, a lack of awareness about participation opportunities, and psychosocial/emotional concerns related to being ?outed.? A broad range of facilitators were also identified, including the opportunity to gain knowledge, access medical services, and contribute to the transgender community. Conclusion: These findings provide insights about the perceived barriers to and facilitators of research participation and offer some guidance for researchers in our ongoing effort to engage the transgender community in health research.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140297/1/trgh.2016.0023.pd