I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

https://escholarship.org/content/qt4h56k1ch/qt4h56k1ch.pdf

Advanced monitoring of machining operations

This paper reviews a new field of direct femtosecond laser surface nano/microstructuring and its applications. Over the past few years, direct femtosecond laser surface processing has distinguished itself from other conventional laser ablation methods and become one of the best ways to create surface structures at nano- and micro-scales on metals and semiconductors due to its flexibility, simplicity, and controllability in creating various types of nano/microstructures that are suitable for a wide range of applications. Significant advancements were made recently in applying this technique to altering optical properties of metals and semiconductors. As a result, highly absorptive metals and semiconductors were created, dubbed as the “black metals” and “black silicon”. Furthermore, various colors other than black have been created through structural coloring on metals. Direct femtosecond laser processing is also capable of producing novel materials with wetting properties ranging from superhydrophilic to superhydrophobic. In the extreme case, superwicking materials were created that can make liquids run vertically uphill against the gravity over an extended surface area. Though impressive scientific achievements have been made so far, direct femtosecond laser processing is still a young research field and many exciting findings are expected to emerge on its horizon.

Direct femtosecond laser surface nano/microstructuring and its applications

The miniaturization of machine components is perceived by many as a requirement for the future technological development of a broad spectrum of products. Miniature components can provide smaller footprints, lower power consumption and higher heat transfer, since their surface-to-volume ratio is very high. To create these components, micro-meso-scale fabrication using miniaturized mechanical material removal processes has a unique advantage in creating 3D components using a variety of engineering materials. The motivation for micro-mechanical cutting stems from the translation of the knowledge obtained from the macro-machining domain to the micro-domain. However, there are challenges and limitations to micro-machining, and simple scaling cannot be used to model the phenomena of micro-machining operations. This paper surveys the current efforts in mechanical micro-machining research and applications, especially for micro-milling operations, and suggests areas from macro-machining that should be examined and researched for application to the improvement of micro-machining processes.

Investigation of micro-cutting operations

Humans can feel, weigh and grasp diverse objects, and simultaneously infer their material properties while applying the right amount of force—a challenging set of tasks for a modern robot1. Mechanoreceptor networks that provide sensory feedback and enable the dexterity of the human grasp2 remain difficult to replicate in robots. Whereas computer-vision-based robot grasping strategies3–5 have progressed substantially with the abundance of visual data and emerging machine-learning tools, there are as yet no equivalent sensing platforms and large-scale datasets with which to probe the use of the tactile information that humans rely on when grasping objects. Studying the mechanics of how humans grasp objects will complement vision-based robotic object handling. Importantly, the inability to record and analyse tactile signals currently limits our understanding of the role of tactile information in the human grasp itself—for example, how tactile maps are used to identify objects and infer their properties is unknown6. Here we use a scalable tactile glove and deep convolutional neural networks to show that sensors uniformly distributed over the hand can be used to identify individual objects, estimate their weight and explore the typical tactile patterns that emerge while grasping objects. The sensor array (548 sensors) is assembled on a knitted glove, and consists of a piezoresistive film connected by a network of conductive thread electrodes that are passively probed. Using a low-cost (about US$10) scalable tactile glove sensor array, we record a large-scale tactile dataset with 135,000 frames, each covering the full hand, while interacting with 26 different objects. This set of interactions with different objects reveals the key correspondences between different regions of a human hand while it is manipulating objects. Insights from the tactile signatures of the human grasp—through the lens of an artificial analogue of the natural mechanoreceptor network—can thus aid the future design of prosthetics7, robot grasping tools and human–robot interactions1,8–10. Tactile patterns obtained from a scalable sensor-embedded glove and deep convolutional neural networks help to explain how the human hand can identify and grasp individual objects and estimate their weights.

Learning the signatures of the human grasp using a scalable tactile glove.

Environmental monitoring has become essential in order to deal with environmental resources efficiently and safely in the realm of green technology. Environmental monitoring sensors are required for detection of environmental changes in industrial facilities under harsh conditions, (e.g. underground or subsea pipelines) in both the temporal and spatial domains. The utilization of optical fiber sensors is a promising scheme for environmental monitoring of this kind, owing to advantages including resistance to electromagnetic interference, durability under extreme temperatures and pressures, high transmission rate, light weight, small size, and flexibility. In this paper, the optical fiber sensors employed in environmental monitoring are summarized for understanding of their sensing principles and fabrication processes. Numerous specific applications in petroleum engineering, civil engineering, and agricultural engineering are explored, followed by discussion on the potentials of OFS in manufacturing.

A review on optical fiber sensors for environmental monitoring

This paper investigates the mechanistic modeling of micro-milling forces, with consideration of the effects of ploughing, elastic recovery, run-out, and dynamics. A ploughing force model that takes the effect of elastic recovery into account is developed based on the interference volume between the tool and the workpiece. The elastic recovery is identified with experimental scratch tests using a conical indenter. The dynamics at the tool tip is indirectly identified by performing receptance coupling analysis through the mathematical coupling of the experimental dynamics with the analytical dynamics. The model is validated through micro end milling experiments for a wide range of cutting conditions.

Modeling of dynamic micro-milling cutting forces

Modeling of minimum uncut chip thickness in micro machining of aluminum

Tool wear monitoring of micro-milling operations

In microend milling, due to the comparable size of the edge radius to chip thickness, chip formation mechanisms are different. Also, the design of microend mills with features of a large shank, taper, and reduced diameter at the cutting edges introduces additional dynamics and faults or errors at the cutting edges. A dynamic microend milling cutting force and vibration model has been developed to investigate the microend milling dynamics caused by the unique mechanisms of chip formation as well as the unique microend mill design and its associated fault system. The chip thickness model has been developed considering the elastic-plastic nature in the ploughing process. A slip-line field modeling approach is taken for a cutting force model development that accounts for variations in the effective rake angle and dead metal cap. The process fault parameters associated with microend mills have been defined and their effects on chip load have been derived. Finally, a dynamic model has been developed considering the effects of both the unique microend mill design and fault system and factors that become significant at high spindle speeds including rotary inertia and gyroscopic moments.

Martin B.G. Jun

Papers

A review on optical fiber sensors for environmental monitoring

Modeling of dynamic micro-milling cutting forces

Modeling of minimum uncut chip thickness in micro machining of aluminum

Tool wear monitoring of micro-milling operations

Investigation of the Dynamics of Microend Milling—Part I: Model Development