Application Progress of Deep Learning in Imaging Examination of Breast Cancer

Breast cancer is the most common malignant tumor in women and its early detection is decisive. Breast imaging plays an important role in early detection of breast cancer as well as monitoring and evaluation during treatment, but manual detection of medical images is usually time-consuming and labor-intensive. Recently, deep learning algorithms have made significant progress in early breast cancer diagnosis. By combing the relevant literature in recent years, a systematic review of the application of deep learning techniques in breast cancer diagnosis with different imaging modalities is conducted, aiming to provide a reference for in-depth research on deep learning-based breast cancer diagnosis. Firstly, four breast cancer imaging modalities, namely mammography, ultrasonography, magnetic resonance imaging and positron emission tomography, are outlined and briefly compared, and the public datasets corresponding to multiple imaging modalities are listed. Focusing on the different tasks (lesion detection, segmentation and classification) of deep learning architectures based on the above four different imaging modalities, a systematic review of the algorithms is conducted, and the performance of each algorithm, improvement ideas, and their advantages and disadvantages are compared and analyzed. Finally, the problems of the existing techniques are analyzed and the future development direction is prospected with respect to the limitations of the current work

Development of Standard Solutions CAI System with UML and XML

Abstract. CAI software products based on TRIZ were successfully applied in superior firms in the world. The Standard Solutions CAI system is one of branch of CAI software. Standard Solutions is important tool for product design. Standard Solutions for innovation firstly models a technical or process problem by Substance-Field (Su-F) Analysis, then synthesizes and converts the problem to acquire a solution. This paper researched on Standard Solutions arithmetic which can be applicable in CAI software product based on Standard Solutions, and established the flow of software. During the development of CAI software product, static models built based on UML were used to construct the configuration of system. For the components of system, dynamic models were used to describe the behaviors of system components. The Standard Solutions CAI software was coded with VC++ language. The interfacial view of this software, which is friendly for users, was created by VC++ combines with XML+XSL. Standard Solutions have great help to innovation design, farther more, its CAI software system help designer adequately apply the theory of Standard Solutions

Flexible Product Platform Based on Design Parameters

International audienceIn the times of mass customization mode, enterprises face more changeable market demand. The traditional product platform can not meet the needs of all customer, therefore the flexible product platform is particularly important. But the method of parametric design is needed to make product platform to be changed rapidly based on flexible product platform. This paper connects parametric design and flexible product platform , and a design process based on flexible product platform with parametric design is developed. Finally the process is applied to the design of belt conveyor, and the flexible product platform with parametric design is set up

Recent Developments in Rhodamine-Based Chemosensors: A Review of the Years 2018–2022

Chemosensors based on traditional fluorescent dyes have always contributed to the development of chemical sensor areas. In this review, the rhodamine-based chemosensors’ improvements and applications from 2018 to 2022 are discussed, mainly focusing on cations (metal ions and H+), anions (CN−, F−, etc.), and small bio-functional molecules’ (thiols, amino acids, etc.) detection. Specifically, this review highlights the detection target, detection limit, detection solution system, detection mechanism, and performance of the rhodamine-based sensors. Although these rhodamine-based sensors are well developed, their repeatability and sensitivity still need significant improvement. This review is expected to bring new clues and bright ideas to researchers for further advances in rhodamine-based chemosensors in the future

A new nortriterpenoid saponin from <i>Sinofranchetia chinensis </i>Hemsl

677-680A new 30-nortriterpenoid saponin, 3-O-α<span style="font-size:12.0pt; font-family:" times="" new="" roman";mso-ansi-language:nl"="" lang="NL">--arabinopyranosyl-30-norhederagenin 28-O-α--hamnopyranosyl(1→4)-β<span style="font-size:12.0pt; font-family:" times="" new="" roman";mso-ansi-language:nl"="" lang="NL">--glucopyranosyl (1→6)-β--glucopyranoside 1, named sinofoside A with two known ones were isolated from Sinofranchetia chinensis. Their structrues were established by means of chemical and spectroscopic evidence (FAB MS,1H NMR, 13C NMR, DEPT, COSY, HMBC and NOE). </span

Fabrication and Microwave Absorption Properties of Core-Shell Structure Nanocomposite Based on Modified Anthracite Coal

Microwave-absorbing materials have attracted extensive attention due to the development of electronic countermeasures. In this study, novel nanocomposites with core–shell structures based on the core of Fe-Co nanocrystals and the shell of furan methylamine (FMA)-modified anthracite coal (Coal-F) were designed and fabricated. The Diels-Alder (D-A) reaction of Coal-F with FMA creates a large amount of aromatic lamellar structure. After the high-temperature treatment, the modified anthracite with a high degree of graphitization showed an excellent dielectric loss, and the addition of Fe and Co effectively enhanced the magnetic loss of the obtained nanocomposites. In addition, the obtained micro-morphologies proved the core–shell structure, which plays a significant role in strengthening the interface polarization. As a result, the combined effect of the multiple loss mechanism promoted a remarkable improvement in the absorption of incident electromagnetic waves. The carbonization temperatures were specifically studied through a setting control experiment, and 1200 °C was proved to be the optimum parameter to obtain the best dielectric loss and magnetic loss of the sample. The detecting results show that the 10 wt.% CFC-1200/paraffin wax sample with a thickness of 5 mm achieves a minimum reflection loss of −41.6 dB at a frequency of 6.25 GHz, indicating an excellent microwave absorption performance

Flexible Copper Nanowire/Polyvinylidene Fluoride Membranous Composites with a Frequency-Independent Negative Permittivity

With the increasing popularity of wearable devices, flexible electronics with a negative permittivity property have been widely applied to wearable devices, sensors, and energy storage. In particular, a low-frequency dispersion negative permittivity in a wide frequency range can effectively contribute to the stable working performance of devices. In this work, polyvinylidene fluoride (PVDF) was selected as the flexible matrix, and copper nanowires (CuNWs) were used as the conductive functional filler to prepare a flexible CuNWs/PVDF composite film with a low-frequency dispersion negative permittivity. As the content of CuNWs increased, the conductivity of the resulting composites increased sharply and presented a metal-like behavior. Moreover, the negative permittivity consistent with the Drude model was observed when CuNWs formed a percolative network. Meanwhile, the negative permittivity exhibited a low-frequency dispersion in the whole test frequency range, and the fluctuation of the permittivity spectra was relatively small (−760 to −584) at 20 kHz–1 MHz. The results revealed that the high electron mobility of CuNWs is reasonable for the low-frequency dispersion of negative permittivity. CuNWs/PVDF composite films with a frequency-independent negative permittivity provide a new idea for the development of flexible wearable electronic devices