Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

With advances in tissue engineering, the possibility of regenerating injured tissue or failing organs has become a realistic prospect for the first time in medical history. Tissue engineering - the combination of bioactive materials with cells to generate engineered constructs that functionally replace lost and/or damaged tissue - is a major strategy to achieve this goal. One facet of tissue engineering is biofabrication, where three-dimensional tissue-like structures composed of biomaterials and cells in a single manufacturing procedure are generated. Cell-laden hydrogels are commonly used in biofabrication and are termed "bioinks". Hydrogels are particularly attractive for biofabrication as they recapitulate several features of the natural extracellular matrix and allow cell encapsulation in a highly hydrated mechanically supportive three-dimensional environment. Additionally, they allow for efficient and homogeneous cell seeding, can provide biologically-relevant chemical and physical signals, and can be formed in various shapes and biomechanical characteristics. However, despite the progress made in modifying hydrogels for enhanced bioactivation, cell survival and tissue formation, little attention has so far been paid to optimize hydrogels for the physico-chemical demands of the biofabrication process. The resulting lack of hydrogel bioinks have been identified as one major hurdle for a more rapid progress of the field. In this review we summarize and focus on the deposition process, the parameters and demands of hydrogels in biofabrication, with special attention to robotic dispensing as an approach that generates constructs of clinically relevant dimensions. We aim to highlight this current lack of effectual hydrogels within biofabrication and initiate new ideas and developments in the design and tailoring of hydrogels. The successful development of a "printable" hydrogel that supports cell adhesion, migration, and differentiation will significantly advance this exciting and promising approach for tissue engineering.

/pdf/25th-anniversary-article-engineering-hydrogels-for-52t0ojjbic.pdf

25th Anniversary Article: Engineering Hydrogels for Biofabrication

3D Printing promises to produce complex biomedical devices according to computer design using patient-specific anatomical data. Since its initial use as pre-surgical visualization models and tooling molds, 3D Printing has slowly evolved to create one-of-a-kind devices, implants, scaffolds for tissue engineering, diagnostic platforms, and drug delivery systems. Fueled by the recent explosion in public interest and access to affordable printers, there is renewed interest to combine stem cells with custom 3D scaffolds for personalized regenerative medicine. Before 3D Printing can be used routinely for the regeneration of complex tissues (e.g. bone, cartilage, muscles, vessels, nerves in the craniomaxillofacial complex), and complex organs with intricate 3D microarchitecture (e.g. liver, lymphoid organs), several technological limitations must be addressed. In this review, the major materials and technology advances within the last five years for each of the common 3D Printing technologies (Three Dimensional Printing, Fused Deposition Modeling, Selective Laser Sintering, Stereolithography, and 3D Plotting/Direct-Write/Bioprinting) are described. Examples are highlighted to illustrate progress of each technology in tissue engineering, and key limitations are identified to motivate future research and advance this fascinating field of advanced manufacturing.

/pdf/recent-advances-in-3d-printing-of-biomaterials-2tjce7ks8k.pdf

Recent advances in 3D printing of biomaterials

Conventional optical tweezers, formed at the diffraction-limited focus of a laser beam, have become a powerful and flexible tool for manipulating micrometre-sized objects. Extending optical trapping down to the nanometre scale would open unprecedented opportunities in many fields of science, where such nano-optical tweezers would allow the ultra-accurate positioning of single nano-objects. Among the possible strategies, the ability of metallic nanostructures to control light at the subwavelength scale can be exploited to engineer such nano-optical traps. This Review summarizes the recent advances in the emerging field of plasmon-based optical trapping and discusses the details of plasmon tweezers along with their potential applications to bioscience and quantum optics.

Plasmon nano-optical tweezers

A review of trends and limitations in hydrogel-rapid prototyping for tissue engineering

生物試料の3d計測学のための自己集合に基づくステップ高さ標準【jst・京大機械翻訳】

Ultrasonic 2D simulations to facilitate defect detection and classification for structural quality control of Swiss‐cheese are presented. Three economically relevant structure types were modeled with different geometry parameters and the back‐scattered ultrasonic field from the structure boundary was simulated to obtain reference data for waveform analysis. Simulated waveform characteristics were evaluated and compared to the experimental ones. Two parameters were introduced to classify different defects by exploiting the frequency spectrum of the signals. Signal waveform and correlation analysis, based on the simulation results, improved defect detection probability.

Simulations to improve structural defect detection and classification in swiss‐cheese

Predicting bond failure after 1.5 ms of bonding, an initial study

Ultrasound is employed in, e.g., non-destructive testing and environmental sensing. Unfortunately, conventional single-element ultrasound probes have a limited acoustic aperture. To overcome this limitation, we employ a modern method to increase the field-of-view of a commercial transducer and to test the approach by localizing a target. In practice, we merge the transducer with a chaotic cavity to increase the effective aperture of the transducer. In conventional pulse-echo ultrasound signal analysis, location estimation is based on determining the time-of-flight with known propagation speed in the medium. In the present case, the dispersing field induces complexity to this inverse problem, also in 2D. To tackle this issue, we use a convolutional neural network-based machine learning approach to study the feasibility of employing one single chaotic cavity transducer to localize an object in 2D. We show that we indeed can localize an inclusion inside a water-filled cylinder. The localization accuracy is one diameter of the inclusion. The area that we can infer increases by 49% in comparison to using the same transducer without applying the proposed chaotic cavity method.

Localizing a target inside an enclosed cylinder with a single chaotic cavity transducer augmented with supervised machine learning

We present ultrasonic quantitative inclusion and pore characterization in bearing steel 100Cr6. A 9.5MHz focused transducer (14cm focal length, 6.3MHz bandwidth) scanned across the top surface of immersed 22*12*6cm3 production samples (8pcs). Automatic pre‐processing was employed to detect inclusions in samples. Recorded RF‐data were analyzed. Continuous wavelet transform and cross‐correlation were applied to measured and registered RF‐signals from known (verified by SEM) inclusions and pores. This allowed characterizing the echoes by shape from wavelet coefficients (WC) and cross‐correlation coefficients: the echo is a superposition of the reflection from the inclusion front and back surface, whereas pores exhibit no back surface echo due to their large acoustic impedance mismatch. Fourier transform allows characterizing echo RF‐signals by frequency content. Dissimilarities ‐signal phase and WCs‐ in echo characteristics between different inclusion and pore classes allows quantitative inclusion and pore c...

/pdf/quantitative-ultrasonics-for-inclusion-and-pore-2pzlgyysy0.pdf

Edward Hæggström

Papers

生物試料の3d計測学のための自己集合に基づくステップ高さ標準【jst・京大機械翻訳】

Simulations to improve structural defect detection and classification in swiss‐cheese

Predicting bond failure after 1.5 ms of bonding, an initial study

Localizing a target inside an enclosed cylinder with a single chaotic cavity transducer augmented with supervised machine learning

Quantitative Ultrasonics for Inclusion and Pore Characterization of Steel Billets