Wavelet Transform and Terahertz Local Tomography

Robotic assembly of smartphone back shells with eye-in-hand visual servoing

The analysis of dynamic deformation processes is an important task in civil and in mechanical engineering. One main emphasis is set on the derivation of the objects transmission function, represented by systems of ordinary or partial differential equations (“white box”-models). The parametric identification of the initial and boundary conditions and relevant material parameters is one of the new challenges in the application of least-square algorithms. Embedding the investigation of the deformation process in a combination of a theoretical and an experimental system analysis suitable methods are provided with adaptive KALMAN-filtering as central identification tool. In this paper the approach of a full system analysis is shown quantifying a dynamic “white-box”-model for the calculation of thermal deformations of bar-shaped machine elements. The task was motivied from mechanical engineering searching new methods for the precise prediction and computational compensation of thermal influences in the heating and cooling phases of machine tools (i.e. robot arms, etc.). The quantification of thermal deformations under variable dynamic loads requires the modelling of the non-stationary spatial temperature distribution inside the object. Based upon FOURIERS law of heat flow the high-grade non-linear temperature gradient is represented by a system of partial differential equations within the framework of a dynamic Finite Element topology. It is shown that adaptive KALMAN-filtering is suitable to quantify relevant disturbance influences and to identify thermal parameters (i.e. thermal diffusivity) with a deviation of only 0,2%. As result an identified (and verified) parametric model for the realistic prediction respectively simu-lation of dynamic temperature processes is presented. Classifying the thermal bend as the main deformation quantity of bar-shaped machine tools, the temperature model is extended to a temperature deformation model. In lab tests with an aluminium column control measurements show that the identified model can be used to predict the columns bend with a mean deviation smaller than 10 mgon. Consequently the deformation model is a precise predictor and suitable for realistic simulations of thermal deformations under variable dynamic loads. In future our activities will be primarily focussed on applications in industrial manufacturing. 1. Parametric identification of dynamic deformation processes The creation of a realistic parametric dynamic deformation model is directly associated with the task to combine systems of differential equations (theoretical physical model) with empirical measurements. Consequently basic principles of system theory can be adapted to the geodetic deformation analysis. The parametric identification of a dynamic “white box”-model 3rd IAG / 12th FIG Symposium, Baden, May 22-24, 2006

Quality control is extremely important for manufacturing compatible parts to supply products that meet production requirements. It provides to track and control the stages of the process and minimizes waste by supporting high levels of productivity. Most of the manufacturers prefer a video measurement system (VMS), which offers non-contact high accurate measurement devices, for evaluating machined parts and products. However, due to the advanced technology and low competition the cost of the non-contact measurement devices is high. Besides some facilities and some research laboratories couldn’t reach these high-cost devices. Today, with the help of evolving technology and open-source image processing libraries, it is possible to offer cost-effective and accurate non-contact measurement systems. This study aims to put forward a VMS to measure parts/products in two dimensions with swift and accurate results. The proposed system has an error below 1% and the linear regression coefficient (r2) was found over 0.95. It works in real-time and minimum frequency was found 10 Hz for repetitive measurements, real-time measurement applications. The proposed cost-effective device can be adapted into various quality control applications in industrial manufacturing

Chromium (Cr) is an essential industrial component and has many applications in industrial manufacturing. Anthropogenic activities can lead to the release of hexavalent chromium [Cr(VI)] as well as trivalent chromium [Cr(III)]. Cr(VI) is 1,000 times more toxic than Cr(III), and very detrimental to most organisms even at low concentrations. Chlamydomonas debaryana, a freshwater algae, appeared to be Cr(VI) resistant and was able to survive in Cr(VI) concentrations of up to 80 mg/L for an extended period in packed aquifer media columns. This micro-green algae strain was isolated alongside Cr(VI) reducing bacteria (CRB) at a Cr(VI) contaminated site in South Africa. In this study, the growth response of C. debaryana in the presence of Cr(VI) was compared to that of Chlamydomonas reinhardtii, to assess the Cr(VI) tolerance of C. debaryana. At 50 mg/L Cr(VI) concentration the maximum chlorophyll a increase was 25.3 % for C. debaryana and 34.2 % for C. reinhardtii. However, after 3.5 d the chlorophyll a content decreased only 38.1 % for C. debaryana compared to a 100 % decrease for C. reinhardtii. Indicating that C. debaryana is only slightly more resistant than C. reinhardtii. Zero Cr(VI) removal was observed with the algae: C. debaryana could not reduce Cr(VI) to Cr(III) or adsorb Cr(VI) anions from the solution. C. debaryana as well as C. reinhardtii, algae cells are inhibited when directly exposed to Cr(VI) in continuously mixed batch reactors. C. debaryana might be better suited to use in cooperation with CRB for Cr(VI) treatment in a biofilm reactor. This research can lead to an improved treatment set up for Cr(VI) pollution that requires fewer chemical and energy inputs and produces less secondary waste.

PolyJet 3D printing technology has emerged as a versatile additive manufacturing process that enables high-resolution, multi-material fabrication with applications in both biomedical and industrial engineering. This study explores the capabilities of PolyJet 3D printing, highlighting its role in producing customized prosthetics, bio-models, and surgical tools in the biomedical field, as well as functional prototypes, tooling, and composite parts in industrial applications. The ability to print intricate geometries with a wide range of digital materials, including biocompatible resins and high-strength polymers, makes PolyJet an essential technology for precision manufacturing. A comparative analysis with other 3D printing techniques, such as Fused Deposition Modeling (FDM) and Stereolithography (SLA), reveals the advantages of PolyJet in achieving superior surface quality, dimensional accuracy, and multi-material integration. Despite challenges such as material costs and post-processing requirements, PolyJet technology continues to advance in medical and industrial sectors, offering innovative solutions for personalized healthcare and high-performance engineering. Keywords: PolyJet 3D Printing, Biomedical Engineering, Industrial Prototyping, Functional Prototyping, Biocompatible Resins, Smart Manufacturing.

Carbon dots (CDs) are fluorescent carbon nanomaterials typically less than 10 nm in size with excellent water solubility, low toxicity, high biocompatibility, favorable optical properties, and modifiable surface. CDs have great promise in various fields, including bioimaging, sensing, and drug delivery. With the emergence of artificial intelligence (AI) technologies, particularly machine learning (ML) and deep learning (DL) algorithms, new avenues for synthesis optimization, performance improvement, and accurate detection and diagnosis using CDs in biomedical engineering have been opened up. This article aims to present a comprehensive review of the applications of AI in CD research, from material design and performance optimization to material characterization and data analysis. It also addresses the possible areas of application for AI-assisted CDs in biomedical engineering, highlighting the importance and future directions of this interdisciplinary area of research. In addition, the potential role of CDs in advancing AI technologies such as optoelectronic storage devices and neuromorphic computing is explored, as well as the lasting impact of the convergence of CDs and AI on the future course of technological advancement.

Artificial intelligence (AI) has emerged as a transformative force in biomedical engineering, catalyzing a shift toward data‐driven, intelligent research paradigms. With its advanced capabilities in computation, pattern recognition, and large‐scale data analysis, AI significantly enhances the efficiency, precision, and reproducibility of biomedical research. In particular, the convergence of AI with biomedical engineering has given rise to the emerging field of Digital Biomedical Engineering, which emphasizes the integration of AI technologies, big data analytics, and computational modeling to enable smart, predictive, and personalized solutions across life sciences. This review provides a comprehensive overview of the current landscape of AI applications in biomedical engineering, highlighting advances in medical image analysis, biosignal processing, biomaterials design, and drug development. It also emphasizes how AI improves diagnostic precision, accelerates material and drug discovery, and fosters personalized and predictive medicine. Additionally, it discusses the limitations and regulatory challenges of AI adoption, while outlining future directions to guide research innovation and clinical translation in the era of digital biomedicine.

通过微细加工技术制成的生物芯片可进行生命科学和医学中所涉及的各种生物化学反应,探测基因表达方式,检测基因突变和多态性,以及研究基因功能,然后借助于计算机技术将这些信息综合处理,从而可实现疾病的检测、诊断、治疗,新药的开发,食品卫生的检测,法医学的鉴定等功能.本文将着重介绍生物芯片技术及在生物医学领域中的应用.

Bioinspired polymers have emerged as a promising field in biomaterials research, offering innovative solutions for various applications in biomedical engineering. This manuscript provides an overview of the advancements and potential of bioinspired polymers in tissue engineering, regenerative medicine, and biomedicine. The manuscript discusses their role in enhancing mechanical properties, mimicking the extracellular matrix, incorporating hydrophobic particles for self-healing abilities, and improving stability. Additionally, it explores their applications in antibacterial properties, optical and sensing applications, cancer therapy, and wound healing. The manuscript emphasizes the significance of bioinspired polymers in expanding biomedical applications, addressing healthcare challenges, and improving outcomes. By highlighting these achievements, this manuscript highlights the transformative impact of bioinspired polymers in biomedical engineering and sets the stage for further research and development in the field.

Micro/nanoporous membranes (M/N-PMs) present quite practical and potential value for extensive biological and medical applications involving separation, patterning, tissue reconstruction, high-throughput manipulation/analysis, and biosensing. In article number 2001545 by Wenming Liu and co-workers, the recent advances in fundamentals of micro/nanoporous membranesM/N-PMs, as well as their applications in biomedical engineering are systematically summarized, providing insights into membrane design, microdevice establishment, and further performance.

Auxetic textiles are intriguing materials with unusual capabilities. These materials exhibit a negative Poisson’s ratio with extraordinary performance in toughness, resilience, shear resistance, and acoustic properties mainly due to their special structure and associated deformation mechanics. Auxetic materials can also have applications around energy absorption and can effectively be used for vibration damping and shock absorbency. The exceptional behaviour of auxetic textiles can be obtained by utilising specific fibrous materials and introducing auxetic geometry and structures differently during weaving, knitting, and nonwoven manufacturing. This issue of Textile Progress highlights the fundamental aspects of various auxetic structures and their properties in general and a detailed analysis of auxetic textile structures and composites, their manufacturing processes, modelling, characterisation, and applications. These materials can potentially revolutionise their applications in sports, automotive, construction industry, biomedical engineering, aerospace, marine, and defence personal protective equipment. Fundamental understanding of auxetic geometry, followed by developing and analysing these geometries by analytical and computational modelling, translating the geometry into appropriate textile structures for actual fabric production, characterisation of auxetic fabrics and their composites, and finally, some innovative applications in technical textiles are some of the fascinating issues addressed in this review.

High-power fiber lasers have been widely used in various industrial manufacturing and military defense applications. During the development of fiber lasers in the past decades, the thermal effect has always been one of the biggest obstacles. It is crucial to study the temperature characteristics and overcome the thermal restrictions for a better output performance. With the systematic design and optimization in this article, optical frequency domain reflectometry (OFDR) can achieve in situ distributed temperature measurement of the fiber core in high-power fiber lasers. This allows a better study of the temperature characteristics and thermal effects. The fiber-core distributed temperature of a kilowatt-level fiber oscillator is first demonstrated based on this method here. The splicing point between the high reflectivity fiber Bragg grating (HR-FBG) and gain fiber withstands the highest temperature, reaching 101.6 °C at a 1.47 kW output. In addition, the temperature of the gain fiber gradually decreases from 92 °C to 30 °C along the pumping direction. The internal temperatures of the combiner and HR-FBG are also measured to evaluate their performances in the high-power regime. The temperature distributions in the experiment agree well with the theoretical simulation.

Engineering a novel adenine-sulfotransferase for efficient synthesis of PAPS and chondroitin sulfate in microbial cells.

\nHumidity is a key parameter in controlling drying processes and ambient conditions in many industrial manufacturing, storage and test applications. Air humidity is routinely measured at temperatures above 100 °C and at conditions that are often challenging due to temporal and local variations. Calibrations of humidity sensors do not provide appropriate representativeness of measurement conditions because they are limited to temperatures below 100 °C and static conditions. A European metrology research project HIT (“Metrology for Humidity at High Temperatures and Transient conditions”) is developing improved humidity measurement and calibration techniques to temperatures up to 180 °C and non-static conditions. This paper summaries developments of the project: calibration and test facilities for industrial hygrometers, studies on humidity control in specific microbial transient processes and a new measurement approach for water activity measurements.

The use of artificial neural networks (ANNs) in power system problems is increasing attention due to their ability to learn and handle the nonlinearities and uncertainties of the systems. Since the last decade, different ANNs identification and filtering techniques have been applied in power systems and adaptive linear neuron networks (ADALINE) are actually widely used. More recently artificial neural networks have been introduced as a complement or an alternative to traditional control algorithms. The use of neural networks in control applications including process control, robotics, industrial manufacturing and aerospace applications, among others has recently experienced rapid growth. This paper proposes a new control method for shunt active power filter, which is based on ANN. An adaptive linear neuron (ADALINE) will be presented to estimate the reference compensation currents. The resultant compensation currents eliminate harmonics and reactive power compensation with a quick dynamic response. Theortical and expermental results in a good agreement