Miracle-dz/UniFAR-FTUs huggingface dataset:
Computational Modeling of Blast Induced Human Injury Biomechanics and Traumatic Brain Injury

The work aims to understand the blast induced injury mechanism and facilitate the development of protection and treatment. Novel multi-scale and multi-physics computational models of coupled blast physics, whole body biodynamics and injury biomechanics are presented. Modeling components include blast wave threat characterization, anatomy-based high-fidelity human model, human body blast loading, biodynamics and body/brain biomechanics leading to primary injury, as well as the multi-physics solver suitable for high-performance computing. The coupled gas dynamics and biomechanics solutions were validated against shock tube test data. The parametric simulations of human body exposed to blasts were conducted to find biomechanical responses and brain injury mechanism.
Fixed transaction ordering and admission in blockchains

Blockchain cryptocurrencies such as Ethereum offer a secure and decentralized transaction system and have the potential to replace legacy financial transaction systems. Despite their potential, they suffer from transaction ordering and admission problems. These stem from having miners deciding the transaction execution order, as well as which transactions are admitted in the blockchain. Transaction censorship, transaction removal due to double-spending attacks and long transaction commit delays are some of the resulting problems. In this work in progress, we will propose a Fixed Transaction Ordering and Admission (FTOA) algorithm to mitigate these problems, using EpTO logical timestamps in a Byzantine setting. We focus on Ethereum, but the general ideas can be applied to other blockchains.
A functional limit theorem for irregular SDEs

Let $X_1, X_2, \ldots$ be a sequence of i.i. d. real-valued random variables with mean zero, and consider the scaled random walk of the form $Y^N_{k+1} = Y^N_{k} + a_N(Y^N_k) X_{k+1}$, where $a_N: \mathbb R \to \mathbb R_+$. We show, under mild assumptions on the law of $X_i$, that one can choose the scale factor $a_N$ in such a way that the process $(Y^N_{\lfloor N t \rfloor})_{t \in \mathbb R_+}$ converges in distribution to a given diffusion $(M_t)_{t \in \mathbb R_+}$ solving a stochastic differential equation with possibly irregular coefficients, as $N \to \infty$. To this end we embed the scaled random walks into the diffusion $M$ with a sequence of stopping times with expected time step $1/N$.
RenderMan

Pixar’s RenderMan renderer is used to render all of Pixar’s films and by many film studios to render visual effects for live-action movies. RenderMan started as a scanline renderer based on the Reyes algorithm, and it was extended over the years with ray tracing and several global illumination algorithms. This article describes the modern version of RenderMan, a new architecture for an extensible and programmable path tracer with many features that are essential to handle the fiercely complex scenes in movie production. Users can write their own materials using a bxdf interface and their own light transport algorithms using an integrator interface—or they can use the materials and light transport algorithms provided with RenderMan. Complex geometry and textures are handled with efficient multi-resolution representations, with resolution chosen using path differentials. We trace rays and shade ray hit points in medium-sized groups, which provides the benefits of SIMD execution without excessive memory overhead or data streaming. The path-tracing architecture handles surface, subsurface, and volume scattering. We show examples of the use of path tracing, bidirectional path tracing, VCM, and UPBP light transport algorithms. We also describe our progressive rendering for interactive use and our adaptation of denoising techniques.
Real-Time Long-Term Visual Object Tracking

Visual object tracking with focus on occlusion, background clutter, image noise and unsteady camera movements, those all in a long-term domain, remain unsolved despite the popularity it experiences in recent years. This paper summarizes a related work which has been done in trackers field and proposes an object tracking system focused on solving mentioned problems, especially the occlusion, rough camera movements and the long-term task. Therefore, a system combined from three parts is proposed here; the tracker, which is the core part, the detector, to re-initialize tracker after a failure or an occlusion, and a system of adaptive learning to handle long-term task. The tracker uses newly proposed approach of bidirectional tracking of points, which are generally weaker then commonly used keypoints. Outputs of both the tracker and the detector are fused together and the result is also used for the learning part. The proposed solution can handle mentioned problems well and in some areas is even better then the state-of-the-art solutions.
Multi-Objective Synthesis of Filtering Dipole Array Based on Tuning-Space Mapping

In the paper, we apply tuning-space mapping to multi-objective synthesis of a filtering antenna. The an- tenna is going to be implemented as a planar dipole array with serial feeding. Thanks to the multi-objective approach, we can deal with conflicting requirements on gain, imped- ance matching, side-lobe level, and main-lobe direction. MOSOMA algorithm is applied to compute Pareto front of optimal solutions by changing lengths of dipoles and pa- rameters of transmission lines connecting them into a se- rial array. Exploitation of tuning space mapping signifi- cantly reduces CPU-time demands of the multi-objective synthesis: a coarse optimization evaluates objectives using a wire model of the filtering array (4NEC2, method of moments), and a fine optimization exploits a realistic pla- nar model of the array (CST Microwave Studio, finite inte- gration technique). The synthesized filtering antenna was manufactured, and its parameters were measured to be compared with objectives. The number of dipoles in the array is shown to influence the match of measured param- eters and objectives.
Constrained control for a pressurized water reactor

One of the main objective in controlling a pressurized water reactor of a nuclear power plant is to regulate the temperature of the water of the primary circuit while satisfying many constraints on both input and measured variables. We describe two approaches to deal with such constraints. The first approach is a classical 2-step design procedure where the synthesis is oblivious of the constraints and then an anti-windup compensation is added. The second approach is a 1-step design procedure, reminiscent to predictive control, where the constraints are taken into account in the synthesis. Comparative simulations results are presented.
User Perspectives on Multi-Touch Tabletop Therapy

Technology-based activities are becoming increasingly popular in therapy programs. In particular, multi-touch tabletops seem to be well suited for many therapy activities. To better understand the benefits of using multi-touch tabletops during rehabilitation, we examined users’ attitudes towards rehabilitation activities on a multi-touch tabletop and on a noninteractive surface. Using a standardized questionnaire and semi-structured interviews, we identified many advantages and limitations of using multi-touch tabletops in rehabilitation. We discuss the implications of user expectations and experiences on the design of future activities and rehabilitation technologies.
Online pattern discovery in distributed , high-dimensional , streaming data under the YOLO principle

INTRODUCTION Over the past few decades the amount of data being produced and transferred over internet has been ever increasing at an almost exponential rate but so has the need to analyze them. This increase, makes storing the data in its entirety for OLAP processing intractable both for practical reasons (e.g. storage costs) as well as due to the inherent computational complexity of processing said data. Also, even if some data are kept, most of the times it is infeasible to provide exact answers within a reasonable amount of time, especially when working in the online setting where we only get to look at the incoming data only once, which is known as the YOLO1 principle. Additionally, we argue that in many use-cases it is acceptable to provide approximate answers that are close the exact ones but can be computed significantly faster while also requiring orders of magnitude less storage. In addition, to topic of finding and tracking emerging, hidden, or periodic patterns can be directly applicable many use-cases example of which are low latency stock market monitoring, temperature trend detection, DDoS attack detection and generally any interesting unbounded information signal. Of course, this is not a new concept and there have been numerous works either looking at the related theoretical or systems aspects but almost never both; we argue for such algorithmic tools in order to be practical and be actually used in practice both aspects need to be considered at the same time. In particular this work aims to be, in its final form, a combination of i) algorithmic tools and ii) systems architecture that will work in tandem to provide answers to the iii) top-k pattern tracking problem in the streaming, online setting at a massive scale.
Local Search Heuristic Inspired in Particle Swarm Optimization for Reducing Collisions in Constrained Navigation ( RCCN ) Problems

Collisions between mobile objects cause a negative impact to navigation systems, therefore reducing the number of collisions is deemed as an optimization problem. Besides, Particle Swarm Optimization is an algorithm intended to find solutions to optimization problems. This paper introduces a heuristic inspired in Particle Swarm Optimization to be applied to problems that we have called Reducing Collisions in Constrained Navigation (RCCN), detecting collisions between mobile objects in a roadmap and reducing the number of collisions through the establishment of wait times. An analysis based on the outcome of the heuristic's application to an instance of RCCN problems is presented finding that is possible to reduce collisions between mobile objects using Artificial Intelligence techniques.
Word-of-Mouth Communication and Percolation in Social Networks †

This paper develops a model of demand, pricing and advertising in the presence of social learning via word-of-mouth communication between friends. In the model consumers must receive information about a monopolist's product in order to consider purchasing it. The presence of word-of-mouth is not sufficient for demand to be more elastic and prices to be lower compared to an informed population. I derive the comparative static results of connectivity, mean-preserving spread of friendships, and clustering of friends on prices. The optimal targets for advertising are not, generically, the individuals with the most friends.
Light‐Driven Titanium‐Dioxide‐Based Reversible Microfireworks and Micromotor/Micropump Systems

Titanium dioxide (TiO2) possesses high photocatalytic activity, which can be utilized to power the autonomous motion of microscale objects. This paper presents the first examples of TiO2 micromotors and micropumps. UV‐induced TiO2 reversible microfireworks phenomenon was observed and diffusiophoresis has been proposed as a possible mechanism.
Differential responses in two varieties of winter wheat to elevated ozone concentration under fully open‐air field conditions

Two modern cultivars [Yangmai16 (Y16) and Yangfumai 2 (Y2)] of winter wheat (Triticum aestivum L.) with almost identical phenology were investigated to determine the impacts of elevated ozone concentration (E‐O3) on physiological characters related to photosynthesis under fully open‐air field conditions in China. The plants were exposed from the initiation of tillering to final harvest, with E‐O3 of 127% of the ambient ozone concentration (A‐O3). Measurements of pigments, gas exchange rates, chlorophyll a fluorescence and lipid oxidation were made in three replicated plots throughout flag leaf development. In cultivar Y2, E‐O3 significantly accelerated leaf senescence, as indicated by increased lipid oxidation as well as faster declines in pigment amounts and photosynthetic rates. The lower photosynthetic rates were mainly due to nonstomatal factors, e.g. lower maximum carboxylation capacity, electron transport rates and light energy distribution. In cultivar Y16, by contrast, the effects of E‐O3 were observed only at the very last stage of flag leaf ageing. Since the two cultivars had almost identical phenology and very similar leaf stomatal conductance before senescence, the greater impacts of E‐O3 on cultivars Y2 than Y16 cannot be explained by differential ozone uptake. Our findings will be useful for scientists to select O3‐tolerant wheat cultivars against the rising surface [O3] in East and South Asia.
On Minimax Duality in Optimal Stopping

Abstract In this article we relate the two following results: The multiplicative minimax duality formula in optimal stopping introduced by Jamshidian (2007, Stochastics 79: 27–60) and the martingale approach to optimal stopping introduced by Beibel and Lerche (1997, Statistica Sinica 7: 93–108). We obtain a minimax duality formula (3.4) similar to Jamshidian's one and discuss some related questions.
GKR: the Graphical Knowledge Representation for semantic parsing

This paper describes the first version of an open-source semantic parser that creates graphical representations of sentences to be used for further semantic processing, e.g. for natural language inference, reasoning and semantic similarity. The Graphical Knowledge Representation which is output by the parser is inspired by the Abstract Knowledge Representation, which separates out conceptual and contextual levels of representation that deal respectively with the subject matter of a sentence and its existential commitments. Our representation is a layered graph with each sub-graph holding different kinds of information, including one sub-graph for concepts and one for contexts. Our first evaluation of the system shows an F-score of 85% in accurately representing sentences as semantic graphs.
Learning to trust flu shots: quasi-experimental evidence on the role of learning in influenza vaccination decisions from the 2009 influenza A/H1N1 (swine flu) pandemic

This paper studies consumer learning in influenza vaccination decisions, i.e., potential causal effects of past experiences of being vaccinated on current use of influenza vaccine. Existing structural models of demand usually identify consumer learning parametrically based on functional form assumptions within dynamic forward-looking Bayesian demand models. To the best of our knowledge, we are the first to explore the potential role of consumer learning in pharmaceutical demand within a reduced form instrumental variable framework. The emergence of a new virus strain (influenza A H1N1/09) during the 2009 influenza pandemic resulted in the use of two different influenza vaccines each recommended for distinct population subgroups. We used these exogenous inputs to vaccination decisions to construct instrumental variables for the effect of past influenza vaccination experiences on the demand model for pandemic vaccine. We find large causal effects of seasonal vaccination on pandemic vaccination with changes in perceived vaccination safety being an important pathway. Our results suggest aimportant role of learning in vaccination decisions. Our findings further highlight that expanding uptake of seasonal vaccination is an important component of pandemic preparedness.
Antioxidant fractions and phenolic constituents from leaves of Pluchea carolinensis and Pluchea rosea

Objective: The objective is to evaluate the antioxidant potential of several polar fractions of Pluchea carolinensis and Pluchea rosea as well as pure chemicals, some of them quantified in both species by high-performance liquid chromatography (HPLC). Methods: The antioxidant potential of polar fractions and pure chemicals were assayed by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and oxygen radical potential methods. The phenolic content was performed by using Folin-Ciocalteu’s reagent. Specific phenolic acids and flavonoids were quantified by diode array detector-reversed phase-HPLC. Results: The highest DPPH antioxidant potential expressed in milligrams of trolox equivalents per gram of dry extract (mg TE/gDE) were frequently measured in fractions from n-butyl alcohol, i.e., 2 (192.1 ± 0.3); 6 (181.0 ± 0.1) of P. carolinensis and in fraction 7 (188.1 ± 5.5) of P. rosea while for oxygen radical scavenging capacity (mg TE/gDE) assay fraction 2 (543.0 ± 64.6) and 4 (501.4 ± 49.7) of P. carolinensis and 3 (401.3 ± 16.1) and 6 (401.3 ± 16.1) of P. rosea showed the best results. Some flavonoids and phenolic acids were also assayed; all of them showed highest oxygen radical absorbance capacity values. Conclusion: We report the antioxidant potential of polar fractions, as well as of some pure phenolics responsible of the antioxidant potential. Some phenolics were identified and quantified for the first time in both species. Apparently, caffeoylquinic acid derivatives contribute more significant to the total antioxidant potential of the extracts.
Designing Research for Monitoring Humanities-based Interdisciplinary Studies: A Case of Cultural Resources Studies (Bunkashigengaku 文化資源学) in Japan

The present paper aims at designing a monitoring framework for a yet new interdisciplinary research and education program in Japan, “Cultural Resources Studies. ”, "Bunkashigengaku" in Japanese. We analyze the linkage between a university, an academic association, and the practitioners’ institutions closely related with cultural resources through the mining of the principal texts produced by them. Our findings reveal the complicated relations among these stakeholder institutions, and attest to the importance of the revision cycle for the advance of interdisciplinary studies.
Optimal Solution Based Plasmonic Interfaces for Photocurrent Enhancement in Silicon-on-Insulator Devices

Renewable energy sources are a vital topic to the future of growing industrialized nations. Solar cells are a popular potential technology to become a major source of energy supply, with Silicon (Si) being the most common solar cell semiconductor material. To address the cost of bulk Si, thin film amorphous Silicon (a-Si) solar cell technology was developed. The drawback to using thin film a-Si solar cells is the reduction in power efficiency compared to bulk Si cells. In this work we explore the use of local plasmon resonance and nanoparticle interfaces to enhance photocurrent within thin film Si. Silver (Ag) nano ink and synthesized Ag nanoparticles were deposited onto Silicon-on-insulator devices through a spin-coating technique. The photocurrent response to the plasmonic interface for several solution weights and particle sizes were analyzed. The photocurrent responses of varying solution weights of 40 nm diameter Ag nano ink particles were tested. The maximum photocurrent response was found to be 149.96 ± 6.69% with a surface coverage of 7% and a solution of 0.1% wt. /vol. Two nanoparticle sizes of 31 nm and 69 nm were also synthesized through wet chemistry techniques. The 69 nm diameter particle had the greatest photocurrent enhancement of 198.84 ± 3.43%. The 31 nm diameter particles at the same solution dilution had a photcurrent enhancement of 48.92 ± 1.47%. This response is greater than the photocurrent enhancement of 16 nm diameter particles fabricated using the thermal evaporation and annealing techniques which reported a maximum enhancement of 33%. Using this simple method of prefabricating and spin-coating particles, reliable photocurrent enhancement may be achieved and the parameters of the nanoparticles may be controlled for maximum
A Micro Wind Turbine for Energy Harvesting

A micro wind turbine design is proposed for fabrication on a polyMUMPS process. The wind turbine consists of 6 blades angled using a scissor hinge. A pin joint keeps the rotating turbine in place while the inner ring of the turbine acts as an electrostatic generator to couple out energy. A preliminary layout and design are included assuming simplified physics. Using a simple model for a wind turbine system, a power conversion rate in the microwatt range is predicted at a wind speed of 10 m/s and a turbine rotation rate of 160 rotations per second. Keywords—polyMUMPS; wind turbine; energy harvesting; microelectromechanical systems (MEMS).
Analogical Reasoning with Knowledge-based Embeddings Douglas Summers-Stay

For robots to interact with natural language and handle realworld situations, some ability to perform analogical and associational reasoning is desirable. Consider commands like ”Fetch the ball” vs. ”Fetch the wagon”, the robot needs to know that carrying a ball is (in the appropriate sense) analogous to dragging a wagon. Without the ability to perform analogical reasoning, robots are incapable of generalizing in the ways that true natural language understanding requires. Inspired by implicit Verlet integration methods for mass spring systems in physics simulations, we present a novel knowledge-based embedding method in this paper, where distributional word representations and semantic relations derived from knowledge bases are incorporated. We use some SAT-style analogy questions to demonstrate potential feasibility of our approach on the analogical reasoning framework.
Global phase diagrams of run-and-tumble dynamics: equidistribution, waves, and blowup

For spatially one-dimensional run-and-tumble dynamics with mass conservation we develop a coarse phase diagram, that discriminates between global decay to equidistributed constant states, existence of spatially non-trivial waves, and finite time blowup of solutions. Motivated by counter-migrating ripples of high and low population density and fruiting body formation in myxobacteria, we identify phase boundaries as particular critical tumbling dynamics that allow for switching between these spatio-temporal phases upon slight changes in mass densities or parameter values.
Listening Culture of Kids and Adolescents Listening Analysis and Music Recommendation Tailored to the Young Markus Schedl

In this paper, we analyze a large dataset of user-generated music listening events from Last.fm, focusing on users aged 6 to 18 years. Our contribution is two-fold. First, we study the music genre preferences of this young user group and analyze these preferences for homogeneity within more fine-grained age groups and with respect to gender and countries. Second, we investigate the performance of a collaborative filtering recommender when tailoring music recommendations to different age groups. We find that doing so improves performance for all user groups up to 18 years, but decreases performance for adult users aged 19 years and older.
Modeling Video Saliency Dynamics for Viewer State Estimation

あらまし 映像視聴における人間の視線運動には,その時々における視聴者の状態及び映像中のシーンの特 性が反映される. 本研究では,映像のシーン特性と視線情報の関係性に基づいて視聴者の集中状態を推定する ことを目的とし,映像中の顕著領域が織りなす変動(顕著性変動)を線形システムにより表現する scene-based saliency dynamics model (SSDM) を提案する. 提案手法では映像のシーン表現として,物体カテゴリーといっ た多様性をもつ意味的情報ではなく,いくつかの典型的な顕著性変動パターンを導入する. これにより,映像の 多様性を許容しつつシーン(変動パターン)の特性を考慮した視線解析を行うことが可能となる. 本論文では, SSDM 及びそのモデル推定法を提案するとともに,集中状態推定において SSDM が有効に働くことを示す. キーワード 顕著性変動,saliency map,視線解析,集中状態推定