Single-nanowire spectrometers.

Medicinal Chemistry as a Scientific Discipline in Industry and Academia: Personal Reflections

Klebsiella pneumoniae carbapenemase (KPC)-producing bacteria is a group of highly dangerous antibiotic resistant Gram-negative Enterobacteriaceae. They cause infections associated with significant morbidity and mortality. Therefore, the rapid detection of KPC-producing bacteria plays a key role in clinical microbiology. Matrix assisted laser desorption/ionization time-of- flight (MALDI-TOF) is a rapidly evolving technology that finds application in various clinical, scientific, and industrial disciplines. In the present study, we demonstrated three different procedures of carbapenemase-producing K. pneumoniae (KPC) detection. The most basic model of MALDI-TOF instrument MS Microflex LT was used, operating in the linear ion-positive mode, commonly used in modern clinical laboratories. The first procedure was based on indirect monitoring of carbapenemase production with direct detection of hydrolyzed carbapenem antibiotic degradation products in the mass spectrum. The second procedure was based on direct detection of blaKPC accompanying peak with an 11,109 Da in the mass spectrum of carbapenemase-producing K. pneumoniae (KPC), which represents the cleaved protein (pKpQIL_p019) expressed by pKpQIL plasmid. In addition, several unique peaks were detected in the carbapenemase-producing K. pneumoniae (KPC) mass spectrum. The third procedure was the identification of carbapenemase-producing K. pneumoniae (KPC) based on the protein fingerprint using local database created from the whole mass spectra. By comparing detection procedures, we determined that the third procedure was very fast and relatively easy. However, it requires previous verification of carbapenemase-producing K. pneumoniae (KPC) using other methods as genetic blaKPC identification, detection of carbapenem degradation products, and accompanying peak with 11,109 Da, which represents cleaved pKpQIL_p019 protein expressed by pKpQIL plasmid. Detection of carbapenemase-producing K. pneumoniae using MALDI-TOF provides fast and accurate results that may help to reduce morbidity and mortality in hospital setting when applied in diagnostic situations.

Engineered hetero structured arrays of ZnO NanoX (X = discs, rods and wires) and CdTe quantum dots for advanced electron transport applications

Standardization and quantification of backscattered electron imaging in scanning electron microscopy

With the rise of novel computing techniques such as big data and artificial intelligence, many scientific and industrial disciplines are faced with exponentially increasing demands for data storage and compute resources. Traditional data compression algorithms are either generically applicable but lossless, limiting performance (e.g. zip), or lossy but designed for specific applications (e.g. jpg, mp3). Machine learning can be deployed to identify the most significant features of any given dataset and favour these features in a compression algorithm. Baler is a novel framework for developing, testing and deploying autoencoder-based data compression algorithms. In this talk, we report on recent developments to the Baler framework, including the implementation of Baler on FPGAs and how Baler has been used to compress data from atomic physics (Mössbauer imaging).

Nanoparticles, or ultrafine particles, are defined as particles with diameters ranging from 1 to 100 nanometers. As the core units of nanotechnology, these structures serve as the building blocks for integrating nanoscale materials into larger, functional systems. Over the past decade, nanotechnology has emerged as a transformative and interdisciplinary field, bridging advancements across a broad spectrum of domains, including medicine, materials science, energy, mechanics, plastics, optics, electronics, and aerospace. This paper provides an overview of the fundamental principles of nanotechnology, explores the unique properties of nanostructures, and highlights their current and potential applications across various scientific and industrial disciplines. By examining both foundational knowledge and emerging innovations, the study underscores nanotechnology’s expanding role in addressing complex challenges and shaping future technological development.

Efficient numerical linear algebra is a core ingredient in many applications across almost all scientific and industrial disciplines. With this survey we want to illustrate that numerical linear algebra has played and is playing a crucial role in enabling and improving data science computations with many new developments being fueled by the availability of data and computing resources. We highlight the role of various different factorizations and the power of changing the representation of the data as well as discussing topics such as randomized algorithms, functions of matrices, and high‐dimensional problems. We briefly touch upon the role of techniques from numerical linear algebra used within deep learning.

In the history of decommissioning, the histories of the individual scientific and industrial disciplines that compound decommissioning have played a significant role. The developments of these have shown that the responsible scientists and engineers could adapt and re-form their backgrounds when faced with the challenges of an integrated discipline. This chapter is a tribute to hundreds of scientists, contractors and operators who have embarked on nuclear decommissioning at a time it was a somehow empirical enterprise and have vigorously helped to push knowledge and experience forward and to establish a new, yet sound discipline. The chapter provides curricula of a few people the author came to know well personally, who were active for many years in nuclear decommissioning and left an historical mark including communities of practices and schools of thought. But apologies are due to their uncountable colleagues who are not mentioned here.

Nanobiotechnology introduces superior strides in diverse scientific and industrial disciplines. The green synthesis of nanomaterials possesses several advantages including low-cost, better reducing and stabilizing potential, near-zero contamination, as well as being an eco-friendly procedure. Biologically prepared nanomaterials expressed their high potential to be applied in numerous disciplines. Biomedical applications involved anticancer, antioxidant, anticoagulant, anti-inflammatory, wound healing, antiparasitic, and antimicrobial potentials. Additionally, biologically synthesized nanomaterials have potential applications in the agricultural sector, food packaging industries, wastewater treatment, management of environmental noxious contaminants such as toxic dye effluents, organic pollutants, phenolic compounds, pathogenic microorganisms, etc. This chapter mainly focuses upon the potential applications of biologically fabricated nanomaterials in different sectors. The issues related to the current challenges, opportunities, safety, and toxicity aspects are also presented in order to develop the best commercialization for the biogenic nanomaterials.

There is a great need for gridded daily precipitation datasets to support a wide variety of disciplines in science and industry. Production of such datasets faces many challenges, from station data ingest to gridded dataset distribution. The quality of the dataset is directly related to its information content, and each step in the production process provides an opportunity to maximize that content. The first opportunity is maximizing station density from a variety of sources and assuring high quality through intensive screening, including manual review. To accommodate varying data latency times, the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) Climate Group releases eight versions of a day’s precipitation grid, from 24 h after day’s end to 6 months of elapsed time. The second opportunity is to distribute the station data to a grid using methods that add information and minimize the smoothing effect of interpolation. We use two competing methods, one that utilizes the information in long-term precipitation climatologies, and the other using weather radar return patterns. Last, maintaining consistency among different time scales (monthly vs daily) affords the opportunity to exploit information available at each scale. Maintaining temporal consistency over longer time scales is at cross purposes with maximizing information content. We therefore produce two datasets, one that maximizes data sources and a second that includes only networks with long-term stations and no radar (a short-term data source). Further work is under way to improve station metadata, refine interpolation methods by producing climatologies targeted to specific storm conditions, and employ higher-resolution radar products.

Enzymes enter the field of functional genomics

COMETT-sponsored University Enterprise Training Partnership (UETPs) fall into two distinct categories. Regional UETPs operate within geographical regions, while sectoral UETPs sponsor activities within a specific industry or scientific discipline. This article describes the activities of the UETP Environmental Engineering Education and the following article looks at the environmental engineering activities carried out by a related sectoral UETP, the European Polytechnic Environmental Association.

The conference will serve as a platform for researchers and practictioners to share the latest ideas, best practices and cutting edge technology in the field of computer science, biomedical engineering, medicine, and other disciplines in both academia and industry

The Co-Development of Industrial Sectors and Academic Disciplines

Focuses on the study of industrial relations in U.S.-based universities. Traditional social science disciplines; Doctoral level of research and instruction; Trend of doctoral degrees granted in industrial sociology and labor economics. (Abstract copyright EBSCO.)