The scanning tunneling microscope is proposed as a method to measure forces as small as 10-18 N. As one application for this concept, we introduce a new type of microscope capable of investigating surfaces of insulators on an atomic scale. The atomic force microscope is a combination of the principles of the scanning tunneling microscope and the stylus profilometer. It incorporates a probe that does not damage the surface. Our preliminary results in air demonstrate a lateral resolution of 30 A and a vertical resolution less than 1 A.

https://link.aps.org/pdf/10.1103/PhysRevLett.56.930

Atomic force microscope

/pdf/self-assembled-monolayers-of-thiolates-on-metals-as-a-form-1neb0hj3k4.pdf

Self-assembled monolayers of thiolates on metals as a form of nanotechnology.

In this work we briefly describe the most relevant features of WSXM, a freeware scanning probe microscopy software based on MS-Windows. The article is structured in three different sections: The introduction is a perspective on the importance of software on scanning probe microscopy. The second section is devoted to describe the general structure of the application; in this section the capabilities of WSXM to read third party files are stressed. Finally, a detailed discussion of some relevant procedures of the software is carried out.

https://nanoed.tul.cz/pluginfile.php/1608/mod_resource/content/1/view.pdf

WSXM: a software for scanning probe microscopy and a tool for nanotechnology.

Surface microscopy using vacuum tunneling is demonstrated for the first time. Topographic pictures of surfaces on an atomic scale have been obtained. Examples of resolved monoatomic steps and surface reconstructions are shown for (110) surfaces of CaIrSn 4 and Au.

https://link.aps.org/pdf/10.1103/PhysRevLett.49.57

Surface studies by scanning tunneling microscopy

1. Introduction 2. Theoretical foundations 3. Propagation and focusing of optical fields 4. Spatial resolution and position accuracy 5. Nanoscale optical microscopy 6. Near-field optical probes 7. Probe-sample distance control 8. Light emission and optical interaction in nanoscale environments 9. Quantum emitters 10. Dipole emission near planar interfaces 11. Photonic crystals and resonators 12. Surface plasmons 13. Forces in confined fields 14. Fluctuation-induced phenomena 15. Theoretical methods in nano-optics Appendices Index.

/pdf/principles-of-nano-optics-1hz998yqo8.pdf

Principles of nano-optics

We present a new approach for computer-aided detection and diagnosis in mammography based on Cognition Network Technology (CNT). Originally designed for image processing, CNT has been extended to also perform context- and knowledge-driven analysis of tabular data. For the first time using this technology, an application was created and evaluated for fully automatic searching of patient cases from a reference database of verified findings. The application aims to support radiologists in providing cases of similarity and relevance to a given query case. It adopts an extensible and knowledge-driven concept as a similarity measure. As a preprocessing step, all input images from more than 400 patients were fully automatically segmented and the resulting objects classified—this includes the complete breast shape, the position of the mammilla, the pectoral muscle, and various potential candidate objects for suspicious mass lesions. For the similarity search, collections of object properties and metadata from many patients were combined into a single table analysis project. Extended CNT allows for a convenient implementation of knowledge-based structures, for example, by meaningfully linking detected objects in different breast views that might represent identical lesions. Objects from alternative segmentation methods are also be considered, so as to collectively become a sufficient set of base-objects for identifying suspicious mass lesions. For 80% of 112 patient cases with suspicious lesions, the system correctly identified at least one corresponding mass lesion as an object of interest. In this database, consisting of 1,024 images from a total of 303 patients, an average of 0.66 false-positive objects per image were detected. An additional testing database contained 480 images from 120 patients, 15 of whom were annotated with suspicious mass lesions. Here, 47% (7 out of 15) of these were detected automatically with 1.13 false-positive objects per image. A diagnosis is predicted for each patient case by applying a majority vote from the reference findings of the ten most similar cases. Two separate evaluation scenarios suggest a fraction of correct predictions of respectively 79 and 76%. Cognition Network Technology was extended to process table data, making it possible to access and relate records from different images and non-image sources, such as demographic patient data or parameters from clinical examinations. A prototypal application enables efficient searching of a patient and image database for similar patient cases. Using concepts of knowledge-driven configuration and flexible extension, the application illustrates a path to a new generation of future CAD systems.

Cognition Network Technology prototype of a CAD system for mammography to assist radiologists by finding similar cases in a reference database.

Apparatus for detecting data in a sensor signal generated by a read sensor (10) in a local probe data storage device comprises a differentiation (110) for subtracting a value of the sensor signal from the succeeding value of the sensor signal to generate a ternary difference signal ; and a convertor (120) connected to the differentiator for converting the difference signal into a binary output signal indicative of the detected data. A local probe data storage device comprising such apparatus is also described.

Data detection for local probe data storage devices

Both object-oriented analysis and the faster pixel-oriented analysis are used to recognize patterns in an image of stained tissue. Object-oriented image analysis is used to segment a small portion of the image into object classes. Then the object class to which each pixel in the remainder of the image most probably belongs is determined using decision trees with pixelwise descriptors. The pixels in the remaining image are assigned object classes without segmenting the remainder of the image into objects. After the small portion is segmented into object classes, characteristics of object classes are determined. The pixelwise descriptors describe which pixels are associated with particular object classes by matching the characteristics of object classes to the comparison between pixels at predetermined offsets. A pixel heat map is generated by giving each pixel the color assigned to the object class that the pixelwise descriptors indicate is most probably associated with that pixel.

Learning Pixel Visual Context from Object Characteristics to Generate Rich Semantic Images

An investigation and/or manipulation device for a sample which is located in a container fluid includes an investigation and/or manipulation tool which is mounted at a first of a cantilever and which during investigation and/or manipulation of the sample immerses into the container fluid. The opposite side of the cantilever is at least partly not immersed into the container fluid during investigation.

Investigation and/or manipulation device for a sample in fluid

The present invention provides data storage devices, systems and methods. An example device includes: a storage medium for storing data in the form of marks; and at least one probe. The probe(s) and storage medium are operable to move relative to each other, with each probe comprising a tip facing the storage medium and having a force creating unit associated thereto. The force creating units are operable to create a force acting between the tip and said storage medium. The data storage device is operable to erase an indentation mark in the storage medium by way of controlling the force creating unit for creating at least one erase force pulse with a force rise time being less than or equal to the order of 1 microsecond.

Gerd Binnig

Papers

Cognition Network Technology prototype of a CAD system for mammography to assist radiologists by finding similar cases in a reference database.

Data detection for local probe data storage devices

Learning Pixel Visual Context from Object Characteristics to Generate Rich Semantic Images

Investigation and/or manipulation device for a sample in fluid

Data storage device and control