Robust Estimation of 3D Human Poses from a Single Image

Human pose estimation is a key step to action recognition. We propose a method of estimating 3D human poses from a single image, which works in conjunction with an existing 2D pose/joint detector. 3D pose estimation is challenging because multiple 3D poses may correspond to the same 2D pose after projection due to the lack of depth information. Moreover, current 2D pose estimators are usually inaccurate which may cause errors in the 3D estimation. We address the challenges in three ways: (i) We represent a 3D pose as a linear combination of a sparse set of bases learned from 3D human skeletons. (ii) We enforce limb length constraints to eliminate anthropomorphically implausible skeletons. (iii) We estimate a 3D pose by minimizing the $L_1$-norm error between the projection of the 3D pose and the corresponding 2D detection. The $L_1$-norm loss term is robust to inaccurate 2D joint estimations. We use the alternating direction method (ADM) to solve the optimization problem efficiently. Our approach outperforms the state-of-the-arts on three benchmark datasets

Activity Pattern Discovery from Network Captures

Investigating insider threat cases is challenging because activities are conducted with legitimate access that makes distinguishing malicious activities from normal activities difficult. To assist with identifying non-normal activities, we propose using two types of pattern discovery to identify a person\u27s behavioral patterns in network data. The behavioral patterns serve to deemphasize normal behavior so that insider threat investigations can focus attention on potentially more relevant. Results from a controlled experiment demonstrate the highlighting of a suspicious event through the reduction of events belonging to discovered patterns. Abstract © 2016 IEEE

Functional form of motion priors in human motion perception

It has been speculated that the human motion system combines noisy measurements with prior expectations in an optimal, or rational, manner. The basic goal of our work is to discover experimentally which prior distribution is used. More specifically, we seek to infer the functional form of the motion prior from the performance of human subjects on motion estimation tasks. We restricted ourselves to priors which combine three terms for motion slowness, first-order smoothness, and second-order smoothness. We focused on two functional forms for prior distributions: L2-norm and L1-norm regularization corresponding to the Gaussian and Laplace distributions respectively. In our first experimental session we estimate the weights of the three terms for each functional form to maximize the fit to human performance. We then measured human performance for motion tasks and found that we obtained better fit for the L1-norm (Laplace) than for the L2-norm (Gaussian). We note that the L1-norm is also a better fit to the statistics of motion in natural environments. In addition, we found large weights for the second-order smoothness term, indicating the importance of high-order smoothness compared to slowness and lower-order smoothness. To validate our results further, we used the best fit models using the L1-norm to predict human performance in a second session with different experimental setups. Our results showed excellent agreement between human performance and model prediction – ranging from 3% to 8% for five human subjects over ten experimental conditions – and give further support that the human visual system uses an L1-norm (Laplace) prior

Synthesizing and Salvaging NAD+: Lessons Learned from Chlamydomonas reinhardtii

The essential coenzyme nicotinamide adenine dinucleotide (NAD+) plays important roles in metabolic reactions and cell regulation in all organisms. Bacteria, fungi, plants, and animals use different pathways to synthesize NAD+. Our molecular and genetic data demonstrate that in the unicellular green alga Chlamydomonas NAD+ is synthesized from aspartate (de novo synthesis), as in plants, or nicotinamide, as in mammals (salvage synthesis). The de novo pathway requires five different enzymes: L-aspartate oxidase (ASO), quinolinate synthetase (QS), quinolate phosphoribosyltransferase (QPT), nicotinate/nicotinamide mononucleotide adenylyltransferase (NMNAT), and NAD+ synthetase (NS). Sequence similarity searches, gene isolation and sequencing of mutant loci indicate that mutations in each enzyme result in a nicotinamide-requiring mutant phenotype in the previously isolated nic mutants. We rescued the mutant phenotype by the introduction of BAC DNA (nic2-1 and nic13-1) or plasmids with cloned genes (nic1-1 and nic15-1) into the mutants. NMNAT, which is also in the de novo pathway, and nicotinamide phosphoribosyltransferase (NAMPT) constitute the nicotinamide-dependent salvage pathway. A mutation in NAMPT (npt1-1) has no obvious growth defect and is not nicotinamide-dependent. However, double mutant strains with the npt1-1 mutation and any of the nic mutations are inviable. When the de novo pathway is inactive, the salvage pathway is essential to Chlamydomonas for the synthesis of NAD+. A homolog of the human SIRT6-like gene, SRT2, is upregulated in the NS mutant, which shows a longer vegetative life span than wild-type cells. Our results suggest that Chlamydomonas is an excellent model system to study NAD+ metabolism and cell longevity

Finding diamonds in the rough: Targeted Sub-threshold Search for Strongly-lensed Gravitational-wave Events

Strong gravitational lensing of gravitational waves can produce duplicate signals separated in time with different amplitudes. We consider the case in which strong lensing produces identifiable gravitational-wave events and weaker sub-threshold signals hidden in the noise background. We present a search method for the sub-threshold signals using reduced template banks targeting specific confirmed gravitational-wave events. We apply the method to all events from Advanced LIGO's first and second observing run O1/O2. Using GW150914 as an example, we show that the method effectively reduces the noise background and raises the significance of (near-) sub-threshold triggers. In the case of GW150914, we can improve the sensitive distance by $2.0\% - 14.8\%$. Finally, we present the top $5$ possible lensed candidates for O1/O2 gravitational-wave events that passed our nominal significance threshold of False-Alarm-Rate $\leq 1/30$ days

Effects of milk heat treatment and solvent composition on physicochemical and selected functional characteristics of milk protein concentrate

peer-reviewedMilk protein concentrate (MPC) powders (∼81% protein) were made from skim milk that was heat treated at 72°C for 15 s (LHMPC) or 85°C for 30 s (MHMPC). The MPC powder was manufactured by ultrafiltration and diafiltration of skim milk at 50°C followed by spray drying. The MPC dispersions (4.02% true protein) were prepared by reconstituting the LHMPC and MHMPC powders in distilled water (LHMPCw and MHMPCw, respectively) or milk permeate (LHMPCp and MHMPCp, respectively). Increasing milk heat treatment increased the level of whey protein denaturation (from ∼5 to 47% of total whey protein) and reduced the concentrations of serum protein, serum calcium, and ionic calcium. These changes were paralleled by impaired rennet-induced coagulability of the MHMPCw and MHMPCp dispersions and a reduction in the pH of maximum heat stability of MHMPCp from pH 6.9 to 6.8. For both the LHMPC and MHMPC dispersions, the use of permeate instead of water enhanced ethanol stability at pH 6.6 to 7.0, impaired rennet gelation, and changed the heat coagulation time and pH profile from type A to type B. Increasing the severity of milk heat treatment during MPC manufacture and the use of permeate instead of water led to significant reductions in the viscosity of stirred yogurt prepared by starter-induced acidification of the MPC dispersions. The current study clearly highlights how the functionality of protein dispersions prepared by reconstitution of high-protein MPC powders may be modulated by the heat treatment of the skim milk during manufacture of the MPC and the composition of the solvent used for reconstitution

Battlespace Next™: Developing a Serious Game to Explore Multi-domain Operations

Changes in the geopolitical landscape and increasing technological complexity have prompted the U.S. Military to coin the terms Multi-Domain Operations (MDO) and Joint All-Domain Command and Control (JADC2) as over-arching strategy to frame the complexity of warfare across both traditional and emerging warfighting domains. Teaching new concepts associated with these terms requires both innovation as well as distinct education and training tools in order to realize the cultural change advocated by senior military leaders. Battlespace Next™ (BSN) is a serious game designed to teach concepts integral to MDO and initiate discussion on military strategy while conserving time, money, and manpower. BSN, a Collectable Card Game (CCG), is engineered to provide an engaging learning tool that educates on capabilities in a multi-domain conflict. This paper proposes an extensible game framework for modeling and reasoning about MDO concepts and presents our empirical feedback from over 120 military play testers evaluating a moderate to difficult version of the game. Results reveal the game teaches MDO concepts and delivers an engaging, hands-on learning experience. Specifically, we provide evidence it improved military readiness in seven areas of MDO in at least 62% of participants and 76% of respondents reported they enjoyed playing the game

Online optimization with switching cost

We consider algorithms for "smoothed online convex optimization (SOCO)" problems. SOCO is a variant of the class of "online convex optimization (OCO)" problems that is strongly related to the class of "metrical task systems", each of which have been studied extensively. Prior literature on these problems has focused on two performance metrics: regret and competitive ratio. There exist known algorithms with sublinear regret and known algorithms with constant competitive ratios; however no known algorithms achieve both. In this paper, we show that this is due to a fundamental incompatibility between regret and the competitive ratio -- no algorithm (deterministic or randomized) can achieve sublinear regret and a constant competitive ratio, even in the case when the objective functions are linear

Interactions of vegetable proteins with other polymers: Structure-function relationships and applications in the food industry

peer-reviewedBackground In recent years, there has been increasing interest in vegetable proteins, due to their various health beneficial functions and wide applications in the food industry. Vegetable proteins combined with other edible polymers can be used to improve the quality and nutritional value of food products. In these complex food systems, interactions between different components are inevitable, and these interactions have a significant influence on the structure and functions of food products. Scope and approach This study reviews the current status of knowledge of interactions between vegetable proteins and other polymers (proteins or polysaccharides) in food systems and the structure of complexes formed by these interactions. The study also provides a comprehensive review of the applications of the complexes. Key findings and conclusions Vegetable proteins display different types of interactions with other polymers (e.g., polysaccharides, or animal proteins) under different conditions, thus forming a variety of complexes with different structures (e.g., double networks, mosaic textures and cross-linked structures), which showed different impact on properties of the final food products and their applications (e.g., substitution for fat, or encapsulation for bioactive ingredients) in the food industry. However, previous studies mainly focused on leguminous proteins and vegetable-protein-based mixtures of two polymers, further studies on other vegetable proteins and more complex food systems containing vegetable proteins and other polymers are required

Delayed neurologic deficit after endovascular abdominal aortic aneurysm repair

AbstractParaplegia or paraparesis secondary to spinal cord ischemia is an extremely rare complication after elective repair of abdominal aortic aneurysm. We report delayed paraparesis after endovascular abdominal aortic aneurysm repair in which one hypogastric artery was unintentionally occluded due to atheroembolism. A spinal catheter was immediately inserted after onset of paraplegia to promote cerebrospinal fluid drainage, which partially reversed the neurologic deficit. Our case underscores both the importance of the critical spinal collateral supply from the hypogastric artery and the role of spinal fluid drainage to maximize spinal cord perfusion in the setting of spinal cord ischemia. (J Vasc Surg 2003;37:690-2.