Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks

We study the problem of synthesizing a number of likely future frames from a single input image. In contrast to traditional methods, which have tackled this problem in a deterministic or non-parametric way, we propose a novel approach that models future frames in a probabilistic manner. Our probabilistic model makes it possible for us to sample and synthesize many possible future frames from a single input image. Future frame synthesis is challenging, as it involves low- and high-level image and motion understanding. We propose a novel network structure, namely a Cross Convolutional Network to aid in synthesizing future frames; this network structure encodes image and motion information as feature maps and convolutional kernels, respectively. In experiments, our model performs well on synthetic data, such as 2D shapes and animated game sprites, as well as on real-wold videos. We also show that our model can be applied to tasks such as visual analogy-making, and present an analysis of the learned network representations.Comment: The first two authors contributed equally to this wor

Visual Dynamics: Stochastic Future Generation via Layered Cross Convolutional Networks

We study the problem of synthesizing a number of likely future frames from a single input image. In contrast to traditional methods that have tackled this problem in a deterministic or non-parametric way, we propose to model future frames in a probabilistic manner. Our probabilistic model makes it possible for us to sample and synthesize many possible future frames from a single input image. To synthesize realistic movement of objects, we propose a novel network structure, namely a Cross Convolutional Network; this network encodes image and motion information as feature maps and convolutional kernels, respectively. In experiments, our model performs well on synthetic data, such as 2D shapes and animated game sprites, and on real-world video frames. We present analyses of the learned network representations, showing it is implicitly learning a compact encoding of object appearance and motion. We also demonstrate a few of its applications, including visual analogy-making and video extrapolation.Comment: Journal preprint of arXiv:1607.02586 (IEEE TPAMI, 2019). The first two authors contributed equally to this work. Project page: http://visualdynamics.csail.mit.ed

Tibial Fracture Nonunions Following Intramedullary Nailing: An Application of Logistic Regression

This paper utilizes the principles of logistic regression analysis to study patient factors that are strongly linked to the outcome of intramedullary nail surgery. This surgery is performed on fractured tibial bones to bring the bone back to union, or a state of connection again. The alternative result of the surgery is nonunion, or a state in which the bone does not heal properly. This paper draws from a recent publication in the Journal of Orthopedic Trauma, “Tibial fracture nonunion and time to healing following reamed intramedullary nailing” (Dailey, Wu, Wu, McQueen, & Court-Brown, 2018)

Economic Consequences Of UK Immigration Reform Following Brexit

Domestic sentiment toward outsiders in the UK has become fueled with negativity and wariness. A heated Leave campaign succeeded in convincing the public that EU citizens were destroying the economy. This article studies the true economic role of EU citizens in the UK prior to dissecting the proposed immigration policy following Brexit to predict the effect of reduced EU immigration to different sectors of the UK economy

Point-contact tunneling spectroscopy measurement of Cux_xTiSe2_2: disorder-enhanced Coulomb effects

We performed point-contact spectroscopy tunneling measurements on Cu$_x$TiSe$_2$ bulk with $x=0.02$ and $0.06$ at temperatures ranging from $T=4-40$ K and observe a suppression in the density of states around zero-bias that we attribute to enhanced Coulomb interactions due to disorder. We find that the correlation gap associated with this suppression is related to the zero-temperature resistivity. We use our results to estimate the disorder-free transition temperature and find that the clean limit $T_{c0}$ is close to the experimentally observed $T_c$.Comment: 4 pages, 4 figure

A Review of 2D and 3D Plasmonic Nanostructure Array Patterns: Fabrication, Light Management and Sensing Applications

Abstract: This review article discusses progress in surface plasmon resonance (SPR) of two-dimensional (2D) and three-dimensional (3D) chip-based nanostructure array patterns. Recent advancements in fabrication techniques for nano-arrays have endowed researchers with tools to explore a material’s plasmonic optical properties. In this review, fabrication techniques including electron-beam lithography, focused-ion lithography, dip-pen lithography, laser interference lithography, nanosphere lithography, nanoimprint lithography, and anodic aluminum oxide (AAO) template-based lithography are introduced and discussed. Nano-arrays have gained increased attention because of their optical property dependency (lightmatter interactions) on size, shape, and periodicity. In particular, nano-array architectures can be tailored to produce and tune plasmonic modes such as localized surface plasmon resonance (LSPR), surface plasmon polariton (SPP), extraordinary transmission, surface lattice resonance (SLR), Fano resonance, plasmonic whisperinggallery modes (WGMs), and plasmonic gap mode. Thus, light management (absorption, scattering, transmission, and guided wave propagation), as well as electromagnetic (EM) field enhancement, can be controlled by rational design and fabrication of plasmonic nano-arrays. Because of their optical properties, these plasmonic modes can be utilized for designing plasmonic sensors and surfaceenhanced Raman scattering (SERS) sensors

All-Optical Ultrafast Control and Read-Out of a Single Negatively Charged Self-Assembled InAs Quantum Dot

We demonstrate the all-optical ultrafast manipulation and read-out of optical transitions in a single negatively charged self-assembled InAs quantum dot, an important step towards ultrafast control of the resident spin. Experiments performed at zero magnetic field show the excitation and decay of the trion (negatively charged exciton) as well as Rabi oscillations between the electron and trion states. Application of a DC magnetic field perpendicular to the growth axis of the dot enables observation of a complex quantum beat structure produced by independent precession of the ground state electron and the excited state heavy hole spins

Metabolic network analysis reveals microbial community interactions in anammox granules.

Microbial communities mediating anaerobic ammonium oxidation (anammox) represent one of the most energy-efficient environmental biotechnologies for nitrogen removal from wastewater. However, little is known about the functional role heterotrophic bacteria play in anammox granules. Here, we use genome-centric metagenomics to recover 17 draft genomes of anammox and heterotrophic bacteria from a laboratory-scale anammox bioreactor. We combine metabolic network reconstruction with metatranscriptomics to examine the gene expression of anammox and heterotrophic bacteria and to identify their potential interactions. We find that Chlorobi-affiliated bacteria may be highly active protein degraders, catabolizing extracellular peptides while recycling nitrate to nitrite. Other heterotrophs may also contribute to scavenging of detritus and peptides produced by anammox bacteria, and potentially use alternative electron donors, such as H2, acetate and formate. Our findings improve the understanding of metabolic activities and interactions between anammox and heterotrophic bacteria and offer the first transcriptional insights on ecosystem function in anammox granules

A qualitative study exploring women’s beliefs about physical activity after stillbirth

Background: Research provides strong evidence for improvements in depressive symptoms as a result of physical activity participation in many populations including pregnant and post-partum women. Little is known about how women who have experienced stillbirth (defined as fetal death at 20 or more weeks of gestation) feel about physical activity or use physical activity following this experience. The purpose of this study was to qualitatively explore women’s beliefs about physical activity following a stillbirth. Methods: This was an exploratory qualitative research study. Participants were English-speaking women between the ages of 19 and 44 years who experienced a stillbirth in the past year from their recruitment date. Interviews were conducted over the phone or in-person based on participants’ preferences and location of residence and approximately 30–45 minutes in length. Results: Twenty-four women participated in the study (M age = 33 ± 3.68 years; M time since stillbirth = 6.33 ± 3.06 months). Women’s beliefs about physical activity after stillbirth were coded into the following major themes: barriers to physical activity (emotional symptoms and lack of motivation, tired, lack of time, guilt, letting go of a pregnant body, and seeing other babies), benefits to physical activity (feeling better emotionally/mentally, helping women to cope or be therapeutic), importance of physical activity (working through grief, time for self), motivators for physical activity (body shape/weight, health, more children, be a role model, already an exerciser). Health care providers and their role in physical activity participation was also a major theme. Conclusions: This is the first study to qualitatively explore beliefs about physical activity in women after a stillbirth. Women who have experienced stillbirth have unique beliefs about physical activity related to their experience with stillbirth. Findings from this study may help to improve the health and quality of life for women who have experienced stillbirth by utilizing physical activity as a strategy for improving depressive symptoms associated with experiencing a stillbirth. Future research in this area is highly warranted