Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, E14.5, E15.5, E18.5, and adulthood. To standardize data collection, we implemented an atlas-based phenotyping pipeline that combines techniques from image registration, deep learning, and morphometrics. Alongside stage-specific atlases, we provide aligned micro-computed tomography images, dense anatomical landmarks, and segmentations (if available) for each specimen (N = 10,056). Our workflow is open-source to encourage transparency and reproducible data collection. The MusMorph data and scripts are available on FaceBase (www.facebase.org, https://doi.org/10.25550/3-HXMC) and GitHub (https://github.com/jaydevine/MusMorph).

The FaceBase Consortium, funded by the National Institute of Dental and Craniofacial Research of the National Institutes of Health, was established in 2009 with the recognition that dental and craniofacial research are increasingly data-intensive disciplines. Data sharing is critical for the validation and reproducibility of results as well as to enable reuse of data. In service of these goals, data ought to be FAIR: Findable, Accessible, Interoperable, and Reusable. The FaceBase data repository and educational resources exemplify the FAIR principles and support a broad user community including researchers in craniofacial development, molecular genetics, and genomics. FaceBase demonstrates that a model in which researchers "self-curate" their data can be successful and scalable. We present the results of the first 2.5 y of FaceBase's operations as an open community and summarize the data sets published during this period. We then describe a research highlight from work on the identification of regulatory networks and noncoding RNAs involved in cleft lip with/without cleft palate that both used and in turn contributed new findings to publicly available FaceBase resources. Collectively, FaceBase serves as a dynamic and continuously evolving resource to facilitate data-intensive research, enhance data reproducibility, and perform deep phenotyping across multiple species in dental and craniofacial research.

The FaceBase Consortium was established by the National Institute of Dental and Craniofacial Research in 2009 as a 'big data' resource for the craniofacial research community. Over the past decade, researchers have deposited hundreds of annotated and curated datasets on both normal and disordered craniofacial development in FaceBase, all freely available to the research community on the FaceBase Hub website. The Hub has developed numerous visualization and analysis tools designed to promote integration of multidisciplinary data while remaining dedicated to the FAIR principles of data management (findability, accessibility, interoperability and reusability) and providing a faceted search infrastructure for locating desired data efficiently. Summaries of the datasets generated by the FaceBase projects from 2014 to 2019 are provided here. FaceBase 3 now welcomes contributions of data on craniofacial and dental development in humans, model organisms and cell lines. Collectively, the FaceBase Consortium, along with other NIH-supported data resources, provide a continuously growing, dynamic and current resource for the scientific community while improving data reproducibility and fulfilling data sharing requirements.

Sharing of bioinformatics data within research communities holds the promise of facilitating more rapid discovery, yet the volume of data is growing at a pace exponentially greater than what traditional biocuration can support. We present here an approach that we have used to empower data producing researchers to curate high quality shared data that is ready for reuse and re-analysis.

The pace of discovery in eScience is increasingly dependent on a scientist's ability to acquire, curate, integrate, analyze, and share large and diverse collections of data. It is all too common for investigators to spend inordinate amounts of time developing ad hoc procedures to manage their data. In previous work, we presented DERIVA, a Scientific Asset Management System, designed to accelerate data driven discovery. In this paper, we report on the use of DERIVA in a number of substantial and diverse eScience applications. We describe the lessons we have learned, both from the perspective of the DERIVA technology, as well as the ability and willingness of scientists to incorporate Scientific Asset Management into their daily workflows.

This paper presents results on the development and fabrication of hollow 3D, programmable-volume, micro-scale, artificial, non-biological volume cells or voxels. The standardized silicon wafer processing method PolyMUMPs (R) was used to construct a variety of polysilicon devices capable of being folded from two-dimensional shapes into three-dimensional regular solids with dimensions in the order of 40 - 80 mu m per side. Folding of the devices was performed by a combination of magnetic and surface tension forces in water. Complete closure of pyramidal structures with dimensions down to 40 mu m per side was achieved, as well as folding of five-sided boxes and half-dodecahedrons (lotuses) with dimensions down to 40 mu m per side.

: The ATTEND (Analytical Tools To Evaluate Negotiation Difficulty) project was established to study computational complexity issues arising in complex dynamic and large-scale real-world problems requiring finding good-enough/soon- enough assignments of resources to tasks. Good-enough/soon- enough problems arise in situations where finding the best solution obtainable within time limits was preferable to finding an optimal solution in unbounded time. Examples range from real-time fire control problems in which time is of the essence to operational risk management and logistics problems in which size and complexity make it computationally infeasible to seek full optimality. Scope: The effort focused upon flight operations scheduling problems exemplifying challenges faced by Marines Corps flight schedulers for AV8-B-Harrier aircraft in Marine Aircraft Group 13. Methods: Our approach mapped resource allocation planning and scheduling problems to formal declarative representations which could then be solved and characterized using available state-of-the-art constraint solvers. Major Findings Including Results Conclusions and Recommendations: ATTEND showed the effectiveness of a multi-phase hybrid approach to solve computationally hard real-world problems: combining multiple solvers proved to be orders of magnitude more efficient that any individual solver that has been built or proposed for problems of the class which was studied.

We describe a Pseudo-Boolean encoding of a time-discretized model of the large and complex scheduling problem coming from the SNAP system. This problem involves the precise scheduling (with 1-minute resolution) of flight missions with multiple requirements of variable duration over large (several weeks at least) planning horizons. The problem is actually a combination of scheduling and planning, where the scheduling of some tasks in the right order might enable resources to perform additional tasks, thus improving the overall quality of the schedule. In order to maintain the scalability of our approach to large planning horizons, we introduce a time discretization of the planning horizon that enable us to solve the problem at variable resolutions. The encoding is fully integrated into the SNAP system and uses the OPARIS (CIRL) Pseudo-Boolean search engine to solve the resulting Pseudo-Boolean formula.

Large NP-hard combinatorial resource allocation problems are best solved via approximation techniques which produce acceptable solutions in the time available. The best of such “good-enough/soon-enough” techniques handle large problems, run in distributed environments, adapt rapidly to changes to the problem while solving, and exhibit good anytime performance. The Dynamic Marble Size (DMS) algorithm appears promising as an approach offering all those traits. It is a marketinspired distributed multi-agent scheme, in which task agents aggressively bid for their preferred resource bundles through single-resource auctions, coordinating their interdependent bids by bid adjustment. In the DMS algorithm, tasks maximally bid their value. This aggressive bidding strategy maximizes other bidders’ information about their prospects of succeeding, and thereby also help them focus on resources they can win. An oscillationavoiding bid adjustment algorithm utilizes a binary search technique to prevent those adjustments from introducing cycles or deadlocks. A “stubbornness-detection monitor” (a re-start limit) limits how many sets of resources a task will pursue. Aggressive bidding, oscillation-avoidance and stubbornness-detection promote rapid convergence on good solutions – bidders avoid highly-contended resources and focus upon more promising alternatives. To evaluate the DMS algorithm, we analyzed characteristics of randomly-generated problems, using results obtained with a Pseudo-Boolean encoding of the problem as the gold standard for quality obtainable from centralized solutions. For the types of problems that our problem generator can produce, DMS produces comparable solution quality, using significantly less time, as well as exhibiting a good anytime performance. Furthermore, a variant of DMS scales linearly in the problem size. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Copyright 2002 ACM X-XXXXX-XX-X/XX/XX ...$5.00.

We propose a technique for solving a type of overconstrained resource allocation problem that is commonly encountered at the heart of many realworld planning and scheduling applications. This type of resource allocation problems are characterized by what we call modular constraints: good solutions are those that guarantee the allocation of resources to tasks that can satisfy all of its requirements and avoid generating assignments that result in broken or partially satisfied tasks. Using SAT and Pseudo-Boolean encodings, we show that a typical or plain encoding results in solutions with a large number of broken tasks while our proposed encodings, by taking into account the modular constraint structure of the problems, guarantee good solutions. In addition, we show that the phase-transition characteristics of the resulting SAT formulas can be used to rapidly estimate the maximum number of satisfiable tasks. This information can be very valuable in the design and implementation of transition-aware solvers.

Helping organizations to marshal, analyze, discuss, and act on all of the available information about a situation playing out over space and time is a critical problem. GeoWorlds (http://www.isi.edu/geoworlds) is a component-based information management system that addresses this issue. It brings together information analysis, retrieval and collaboration tools and integrates digital library, geographic information systems (GIS), and remote sensor data management technologies. It provides three key services: 1) rapidly assembling a custom repository of geographic information about a region, 2) bi-directionally linking it to collections of document-based information from the World-Wide Web, and 3) monitoring real-time sensor data for information that might change conclusions or decisions formed on the basis of this rich information set. GeoWorlds framework enables synchronous and asynchronous collaboration over finding, filtering, organizing and visualizing the needed information.

Marbles schemes are a family of cooperative and adaptive algorithms for distributed resource allocation problems. Long-term goals for these schemes are fault-tolerance and real-time performance in which a good timely solution is preferable to an optimal but too late solution. This paper reports work in progress where we compare the performance and analyze characteristics of different Marbles schemes and centralized solvers working on large scale and complex resource allocation problems.

GeoWorlds (http://www.isi.edu/geoworlds ) is a component-based information management system aimed at helping organizations to marshal, analyze, discuss, and act on all of the available information about a situation playing out over space and time. The system integrates digital library, geographic information systems (GIS), and remote sensor data management technologies, together with other information analysis, retrieval and collaboration tools. It shows how users can rapidly assemble a custom repository of geographic information about a region, bi-directionally link it to collections of document- based information from the World-Wide Web, and monitor real-time sensor data for information that might change conclusions or decisions formed on the basis of this rich information set. This functionality is provided within a framework that enables synchronous and asynchronous collaboration over finding, filtering, organizing and visualizing the needed information.

The GeoWorlds system integrates geographic information systems, spatial digital libraries and other information analysis, retrieval and collaboration tools. It supports multiple applications ranging from intelligence gathering to urban planning, to crisis management and response. Teams can rapidly assemble collections of document-based information from the World-Wide Web and other specialized information sources, visualize geospatial distribution of these collections and monitor events that might change conclusions or decisions formed on the basis of an initial information set. This functionality is provided within a framework that supports both synchronous and asynchronous collaboration over finding, filtering and organizing information and presenting it in a rich visualization environment.

Rigid nanoscale 2D structures of up to four individual gold nanoparticles were formed by using bifunctional organic molecules (dithiols) in combination with scanning force microscopy manipulation. These structures can be either precisely translated by mechanical pushing across the surface or rotated about a specific axis. Experimental results are presented that show how simple geometric shapes can be manipulated and assembled to form more complicated structures. The nanoparticles were linked either by (i) forming a multiparticle structure and subsequent treatment with dithiols or by (ii) pushing together individual particles, which were treated with dithiols prior to manipulation.

Rigid nanoscale 2D structures of up to four individual gold nanoparticles were formed by using bifunctional organic molecules (dithiols) in combination with scanning force microscopy manipulation. These structures can be either precisely translated by mechanical pushing across the surface or rotated about a specific axis. Experimental results are presented that show how simple geometric shapes can be manipulated and assembled to form more complicated structures. The nanoparticles were linked either by (i) forming a multiparticle structure and subsequent treatment with dithiols or by (ii) pushing together individual particles, which were treated with dithiols prior to manipulation.

GeoWorlds is a situation understanding and management system that integrates geographic information systems, spatial digital libraries and other information analysis, retrieval and collaboration tools that can be used in several applications ranging from intelligence gathering to urban planning, to crisis management and response. The idea is to let teams of users marshal, analyze, collaborate and act on all of the available information about a situation playing out over space and time. Teams can rapidly assemble a custom repository of geographic information about a region, bi-directionally link it to collections of document gathered from the World-Wide-Web or other specialized information spaces, and monitor events that might effect decisions made on the basis of this rich information set. This functionality is provided within a framework that enables synchronous and asynchronous collaboration over finding, filtering and organizing a collection of information and presents the relevant geographic information in a rich 3D (VRML) visualization environment.

NP-hard resource allocation problems are best solved via ap- proximation techniques which produce acceptable solutions in the time available. The best of such "good-enough/soon- enough" techniques handle large problems, can run distributed, can adapt to changes to the problem while they are solving it, ensure that solution quality always increases, and start proposing solutions rapidly so that the user can quit opti- mizing at any time. And, maybe most importantly, they must let the user know when it makes sense to quit and when it is worthwhile to wait. Our Dynamic Marble Size (DMS) scheme appears promis- ing as an approach offering all those traits. It is a market- inspired distributed multi-agent scheme, in which coopera- tive task agents compete for resources through an auction but are capable of altruistically withdrawing to balance local vs. global concerns, reduce contention, and speed closure. In DMS, tasks maximally bid their value which maximizes other bidders' information about their prospects of succeed- ing, and thereby also guide them focus on resources they can win. An oscillation-avoiding bid adjustment algorithm uti- lizes binary search techniques to prevent those adjustments from introducing cycles or deadlocks. A "stubbornness- detection monitor" (a re-start limit) limits how many sets of resources a task will pursue. These three techniques com- bine to promote rapid convergence on good solutions - bid- ders avoid highly-contended resources and focus upon more promising alternatives. In addition, DMS schemes exhibit well-differentiated faster primary and slower secondary solution phases. They can de- tect which phase they are in, and thus guide the user in when it makes sense to stop and when it does not. Evaluations of DMS analyzed characteristics emerging from running very large numbers of randomly-generated prob- lems. In these evaluations we compare the solution qual- ity of DMS against results obtained with a Pseudo-Boolean encoding of the problem as the gold standard for central- ized solutions. For the types of problems that our problem