Abstract: Surface-enhanced Raman scattering (SERS), a variant of Raman spectroscopy, is a powerful analytical technique that uses plasmonics to obtain detailed chemical information of molecules or molecular assemblies adsorbed or attached to nanostructured metallic surfaces. It is being considered for numerous sensing applications including health, food, environmental monitoring, safety etc. Plasmonics, exploits the interaction between light and metallic nanostructures at the metal-dielectric interface. The metal-dielectric interfaces are engineered to optimize for high enhancement factors and molecular specificity with high accuracy and sensitivity. In this review we have focused on the basics of plasmonics, fundamentals of SERS, different methods adopted for fabrication of various types of SERS substrates, applications of SERS in bio-medicine, a brief description of different variants of Raman spectroscopy and a concise introduction on quantum sensing. Fundamental mechanisms of SERS and factors contributing to SERS enhancement have also been reviewed in this article. Latest developments in the field of novel SERS substrates have been explored including different kinds of plasmonic/non-plasmonic materials, different sizes, shapes, and architectures of SERS substrate to achieve high sensitivity and specificity as well as tunability or flexibility. Different forms of Raman spectroscopy have been discussed in terms of advantages and challenges of each technique. With artificial intelligence and machine learning expanding its dominance in almost every field, it is inevitable to discuss the importance of signal detection schemes and data analytics, and its implementation in the detection/quantification of analytes using SERS-based point-of-care technologies. The objective of this review is to provide a comprehensive overview of SERS by highlighting challenges and shortfalls in implementing it and providing a deeper insight of its principle, mechanism, advantages, and limitations of current technology. Different fundamental approaches are discussed, such as label-free and functional assays. We have also reviewed the main advantages and challenges of SERS-based biosensing and presented a brief outlook.

Abstract: Climate change and sea level rise have the potential to significantly alter existing natural groundwater levels and pore water chemistry in soil deposits that are near the ocean. As ocean levels rise, a salinity front advances through the groundwater, and extreme events such as hurricanes or winter storms cause the introduction of saline water further inland at the surface. After a high-water event, standing surface water left in pools evaporates, leading to high-salinity water pools or salt deposits at the surface. Existing animal burrows, desiccation cracking, and plant root structures (for plants that are alive or dead) facilitate the exchange of salts and other contaminants in a complex regime. The current study describes the process of instrumentation of a natural terrestrial site to monitor seasonal variations in temperature in the soil profile, fluctuations in groundwater level, changes in soil pore pressure, and changes in soil salinity. The goal of this instrumentation program is to develop a more specific understanding of the effect of changes in salinity due to flooding and sea level rise on the physical, chemical, mechanical, and biological properties of soils. For this study, a project site was selected at the St. Jones Reserve, located along the St. Jones River and the Delaware Bay in the state of Delaware, in the USA. The site is located south of the Dover Air Force Base and is part of a roughly 700-acre sanctuary, which includes the Delaware National Estuarine Research Reserve, and the St. Jones Center for Estuarine Studies. In the field at the site, a series of instruments and data logging systems were installed along a transect that follows a salinity gradient from non-saline to saline pore water. This site has been heavily instrumented with various instruments by the current team as well as other researchers, to assess seasonal variations in temperature, pore pressure, volumetric water content, and salinity. This study will provide preliminary data from the initial monitoring stages, along with background knowledge in regard to sensor selection, fabrication of sensor arrays, and installation procedures of the data logging system for this site.

Abstract: The sensing instrumentation and testing operations routinely implemented in-situ to monitor the condition of both paved (flexible, rigid) and unpaved roads are critically reviewed: image acquisition, appraisal of surface profile and skid resistance, measurement of stress, strain and deflection, execution of tomography tests, evaluation of environmental parameters as well as determination of traffic volume. Further, this state-of-the-art review sheds light on the financial aspects and cost spectra of the different diagnostic procedures. Finally, a systematic literature review highlights trends in recent research and documents that scientific studies have mainly focused on remote imaging, deflection and tomography measurements.

Abstract: Induction surface hardening (ISH) processes are widely used in the heat treatment of numerous industrial components, especially in the automotive industry. Since this industry operates under very demanding quality standards, it is crucial for these heat treatment processes to meet rigorous specifications to ensure the safety and reliability of the produced components. This implies the precise and repeatable control of certain parameters throughout the manufacturing process of each of the parts treated, through precise and reliable instrumentation in electromagnetically harsh environments. The main objective of this work is to define the monitoring process for an industrial IHS application, determining the control needs and the methods of measurement, recording, and verification of the parameters that ensure the quality of the process. This paper describes the monitoring process of induction surface hardening, emphasizing the use of sensors and modern measurement and control systems. A comprehensive monitoring system supported by a programmable logic controller (PLC) and mixed acquisition and instrumentation systems (analog and digital) implemented with a high-performance Field Programmable Gate Array (FPGA) will be presented.

Abstract: Proper signal measurement and processing are crucial in electroencephalography (EEG)-based brain-computer interfaces (BCIs), as they form the basis of brain insight and precise BCI control. Currently, extensive papers have reported their progress and successful applications in this field. Nevertheless, a systematic review of progress and challenges in this field is still lacking, and the research challenges have not been thoroughly discussed. Herein, a systematic review of instrumentation, measurement, and signal processing in EEG-based BCIs is proposed. First, EEG signals and the application of EEG-based BCIs are introduced. Then, the components and products related to the measurement, processing, and control of EEG signals are analyzed. Specifically, detailed discussions are provided on the measurement methods and results. Moreover, typical EEG paradigms and the processing methods of EEG signals are analyzed. Finally, four major challenges in this field are proposed and discussed: BCIs for acquiring high-quality EEG signals, EEG-based BCIs for long-term tasks, EEG-based BCIs for mobile or dynamic scenarios, and EEG-based BCIs with user-centered designs. This study offers practitioners a comprehensive guide for the measurement and processing of EEG signals, encompassing instrument selection, methodology implementation, current challenges, and future considerations.

Abstract: Abstract Sediment plumes are a key issue in assessing the environmental impact of seabed mining. The Metals Company carried out a pilot Nodule Collector test in the NORI-D license area in late 2022. The equipment test was closely monitored in the nearfield from the Allseas test mining vessel and in the far field from a dedicated monitoring vessel. The monitoring program was designed to quantify the concentration of sediment returned to the sea at a mid-water discharge point, as well as the sediment disturbed by the Prototype Collector Vehicle at the seabed. The monitoring efforts were aimed at providing baseline data as well as observing the concentration, movement and settling of the plume. All monitoring efforts were supported by numerical modelling, which was used to inform the best monitoring locations as well as the conditions expected during the testing of the collector vehicle. Following a comprehensive planning phase, decisions on monitoring methods and equipment and their deployment were described in detailed SOPs for all field work to ensure consistency of all measurements. This included details of instrument configurations and deployment strategies for fixed and mobile monitoring platforms. However, complex field operations are almost impossible to plan down to the minute and a degree of flexibility is required to ensure optimal use of the campaign. The realized monitoring strategy reflected the basic guiding principles detailed in the SOPs adapted to logistical circumstances encountered in the field, This is particularly important to allow comparisons between different types of analyses, including the interpretation of analyses of individual water samples. In this paper we will present the monitoring strategy and plan developed by DHI in collaboration with The Metals Company. We will also present the different components of the monitoring (mobile assets such as AUV/ROV), fixed stations (mooring lines and landers), water and sediment sampling that were used during the campaign. Recent experiences of tracking and observing plumes with acoustic instrumentation mounted on remotely operated vehicles (ROV), autonomous underwater vehicles (AUV), static seabed landers, and oceanographic moorings will be presented. Specifically, this presentation will discuss:The value of predictive modelling prior to the start of trials, with the objective of monitoring where significant plume was to be expectedHow differences between predictive modelling and real-time observations influenced short-term monitoring strategiesKey challenges related to instrument performance at extreme depths, mobile monitoring platforms, and simultaneous monitoring operations

Abstract: Abstract Recently, ion mobility spectrometry‐mass spectrometry (IMS‐MS) has become more readily incorporated into various omics‐based workflows. These growing applications are due to developments in instrumentation within the last decade that have enabled higher‐resolution ion mobility separations. Two such platforms are the cyclic (cIMS) and structures for lossless ion manipulations (SLIM), both of which use traveling wave ion mobility spectrometry (TWIMS). High‐resolution separations achieved with these techniques stem from the drastically increased pathlengths, on the order of 10 s of meters to >1 km, in both cIMS‐MS and SLIM IMS‐MS, respectively. Herein, we highlight recent developments and advances, for the period 2019–2023, in high‐resolution traveling wave‐based IMS‐MS through instrumentation, calibration strategies, hyphenated techniques, and applications. Specifically, we will discuss applications including CCS calculations in multipass IMS‐MS separations, coupling of IMS‐MS with chromatography, imaging, and cryogenic infrared spectroscopy, and isomeric separations of glycans, lipids, and other small metabolites.

Abstract: On February 18th, 2021, the Mars 2020 entry system successfully delivered the Perseverance rover to the surface of Mars at Jezero Crater. The entry capsule carried instrumentation installed on the heatshield and backshell, named “Mars Entry, Descent, and Landing Instrumentation 2.” The instruments were used to measure the aerodynamic and aerothermodynamic performance of the entry vehicle. Five sensors at two locations (three sensors at one location and two sensors at the second location), including a thermocouple plug, heat flux gauge, and a radiometer, were co-located on the backshell. The sensors were exposed to roughly the same aerodynamic heating but measured these environments in different ways, each with its own set of modeling and measurement error complications. This paper develops a method for blending each of these measurements together in a single algorithm to produce estimates of the aerothermodynamic environments at each backshell location. The approach makes use of the Kalman–Schmidt filter/smoother methodology, where systematic measurement error parameters are modeled as multiplicative states that are estimated by the filter along with the aerothermal states. The results of the sensor fusion approach are expected to be used to inform and improve aerothermal modeling for future Mars entry capsules.

Abstract: Applications that involve subsurface characterization and monitoring such as landslide detection or geotechnical condition monitoring typically require continuous and high-quality geoscience data to be collected from remote areas where sampling frequency and power consumption pose major challenges. New advanced platforms are required which seamlessly blend accuracy, affordability, and practicality in sensor data collection and transfer. Here, we introduce and evaluate an agnostic platform, tailored for proficient data acquisition via its four-channel differential analog-to-digital converters (ADC), thereby enabling the integration of four sensors with differential outputs for comprehensive data collection. Utilizing the ESP32 Wemos board as its cornerstone CPU, the platform presents a dual-faceted capability to efficiently stream geoscience data to the cloud where signal strength is sufficient, safeguarding data integrity and providing near-real-time accessibility, and to store it locally when the site does not allow connectivity. Surpassing current systems, this platform delivers a sampling rate of 3.2 kHz samples per second (800 samples per second per channel) and provides a robust bandwidth response critical for geotechnical monitoring, while maintaining a highly cost-effective production framework for scalable monitoring. The platform’s utility is validated through its application in subsurface ground characterization, employing the Nakamura method to determine initial layer depths and then monitoring through time to analyze property changes related to ground saturation, a primary catalyst for slope instabilities. The findings demonstrate the devised platform as a potent, economically viable tool, promising substantial applicability across various research domains necessitating precise data capture and transmission.

Abstract: This article details the rise of surgical robots in the human surgical sphere as well as their use in veterinary medicine. Sections will describe in detail the equipment required for these procedures and the advantages and disadvantages of their use. Specific attention is given to the articulated instrumentation, which affords psychomotor benefits not only for surgical precision but also for surgeon ergonomics. A discussion of the possible indications and current use of robotics in veterinary medicine and the challenges to integrating robotics is also provided.

Abstract: Ultrasonic scanning is a non-destructive method employed in several fields, for instance, in medicine. Ultrasonic testing is also relevant for detecting flaws in products and structures. One application example is the inspection of welded structures. This chapter gives a brief overview of the importance of ultrasonic scanning in the characterization of welded structures, starting with general introductory content on ultrasonic scanning. Then, the non-destructive characterization of welded parts is described, from the basic principles to the instrumentation. The several ultrasonic techniques employed for welded parts will also be described and analyzed. Finally, a brief overview of the relevant standards is given.

Abstract: The proteome, or collection of proteoforms expressed in a biological system, is dynamic and heterogeneous. As our appreciation for the complexity of the proteome has evolved, so have the technologies we use to interrogate its composition. More than three decades ago, a rapid expansion in the field of proteomics was driven by the advent of soft ionization techniques focusing on capturing protein sequence information using mass spectrometry (MS). As tools to automate peptide and protein sequencing with tandem MS (MS/MS) matured, our field recognized the limits of qualitatively cataloguing gene products. This realization drove a multi-pronged expansion of MS-centric technologies that seek to capture various aspects of proteins, including their abundance, modification states, conformation and structure, and spatiotemporal relationships. Here we review innovations in MS-based instrumentation that continue to expand our ability to survey the proteome with ever increasing sensitivity, speed, and flexibility. The march of progress in MS instrumentation has been steady over the better half of the past century, but our discussion here focuses on developments within the past five years that have ushered in an exciting era in proteomics, where MS is poised to be the dominant platform for exploring biological phenotypes in basic and translational sciences for the foreseeable future.

Abstract: Atomic force microscopy (AFM) is a part of the scanning probe microscopy family. It provides a platform for high-resolution topographical imaging, surface analysis as well as nanomechanical property mapping for stiff and soft samples (live cells, proteins, and other biomolecules). AFM is also crucial for measuring single-molecule interaction forces and important parameters of binding dynamics for receptor-ligand interactions or protein-protein interactions on live cells. However, performing AFM measurements and the associated data analytics are tedious, laborious experimental procedures requiring specific skill sets and continuous user supervision. Significant progress has been made recently in artificial intelligence (AI) and deep learning (DL), extending into microscopy. In this review, we summarize how researchers have implemented machine learning approaches so far to improve the performance of atomic force microscopy (AFM), make AFM data analytics faster, and make data measurement procedures high-throughput. We also shed some light on the different application areas of AFM that have significantly benefited from applications of machine learning frameworks and discuss the scope and future possibilities of these crucial approaches.

Abstract: This yearly report on new products introduced in the preceding year, since March 2023, covers sample preparation instrumentation, supplies, and accessories.

Abstract: This chapter introduces the instrumentation amplifier. This is perhaps the most important of all amplifiers in electrical measurement systems. The common mode rejection ratio is redefined and its relationship to the signal-to-noise ratio is emphasized. Instrumentation amplifiers are implemented with op amps, and the most common implementation circuits are illustrated.

Abstract: Versatility, sensitivity and accuracy have made the real-time polymerase chain reaction (qPCR) a crucial tool for research as well as diagnostic applications. However, for point-of-care (PoC) use traditional qPCR faces two main challenges: long run times mean results are not available for half an hour or more and the requisite high-temperature denaturation requires more robust and pow-er-demanding instrumentation. This study addresses both issues and revised primer and probe designs, modified buffers and low ∆T protocols which, together, speed up qPCR on conventional qPCR instruments and will allow the development of robust, point-of-care devices. Our approach, called "FlashPCR", also allows efficient reverse transcription as part of a one-step RT-qPCR pro-tocol, making it universally applicable for both rapid research and diagnostic applications.

Abstract: Eddy current (EC) detection technique has been applied for the inspection of small-diameter pipelines whereas it retains the limitation in detecting defects on the outer wall of the pipeline. This article proposes new instrumentation of cross electromagnetic EC sensing for internal pipeline inspection. The technique integrates the principles of remote field EC (RFEC) and near field EC and involves exciting two types of magnetic fields inside the pipeline. The first magnetic field is oriented perpendicular to the pipe wall, which allows for the detection of inner wall defects. The second magnetic field propagates along the pipeline direction, enabling the detection of outer wall defects. By combining these two magnetic fields, the proposed technique enables simultaneous detection of both inner and outer wall defects in small-diameter buried pipelines. A detection platform for an experimental laboratory system has been built, and an internally integrated system developed for pipelines with an 8-in diameter. By conducting inspections on various pipelines, defects on both the inner and outer walls were successfully detected. Results have validated the reliability and efficiency of the proposed detector.

Abstract: Abstract A re-programmable Zynq system-on-chip (SoC) FPGA-based water-immersible 2-channel ultrasonic instrumentation has been designed and developed and it is mounted inside the IP67-grade enclosures, which is suitable for ultrasonic pipe inspection and gauging applications. The novel, compact Zynq SoC FPGA-based ultrasonic instrumentation system, powered by lithium-ion batteries for its operation over five hours, exhibits its adaptability for challenging environments, including its ability to travel through pipes carrying oil or water. One of the salient features of the 2-channel system is the capability to acquire echo signals using 12-bit/100 MSPS digitizer to provide highly accurate values of the inner diameter (ID) and wall thickness (WT) of the pipe under test. The system has been utilised to acquire and store 256 MB of A-Scan data in the DDR3 memory module of FPGA. Subsequent to five hours of
acquisition, data was transferred to the computer to reconstruct B-Scan cross-sectional images for 300 mm nominal bore (NB) Stainless Steel (SS), and Carbon Steel (CS) pipes machined with volumetric and planar standard flaws. The B-Scan images could reveal both types of defects along with the location and size of these flaws. Such ultrasonic instrumentation has become an advanced tool to acquire a large volume of gauging data for pipes operating in harsh conditions, making it a vital asset for the inspection of pipes
containing crude oil or processed water for petrochemical and nuclear industries. This paper provides brief details about the ultrasonic PIG instrument, with few inspection results obtained for SS and CS pipes.

Abstract: Abstract The accuracy of Artificial Intelligence (AI) in malware detection is dependent on the features it is trained with, where the quality and authenticity of these features is dependent on the dataset and the analysis tool. Evasive malware, that alters its behavior in analysis environments, is challenging to extract authentic features from where widely used static and dynamic analysis tools have several limitations. However, Dynamic Binary Instrumentation (DBI) allows deep and precise control of the malware sample, thereby facilitating the extraction of authentic behavior from evasive malware. Considering the limitations of malware analysis for use with AI, this research had two primary objectives: investigation of the evasive techniques used by modern malware and the creation of Peekaboo, a DBI tool to extract authentic data from live malware samples. Peekaboo instruments and defeats evasive techniques that target analysis tools and virtual environments. A dataset of 20,500 samples was assembled and each sample was run for up to 15 minutes to observe not only the anti-analysis techniques used but also its complete behavior. Peekaboo outperforms other tools on several fronts, it is the only tool to measure start and completion rates, capture the executed Assembly (ASM) instructions, record all network traffic and implements the largest coverage against evasive techniques.

Abstract: The instrumentation plan for the ELT foresees the ArmazoNes high Dispersion Echelle Spectrograph (ANDES). The ANDES-project and consortium entered phase B in January 2022 and underwent several (internal and external) revisions by now to ensure that the requirements and eventually the challenging goals can be met by the physical design of the spectrograph.

Among its main scientific goals are the detection of atmospheres of exoplanets and the determination of fundamental physical constants. For this, high radial velocity precision and accuracy are required. Even though the ANDES-spectrograph is designed for maximum intrinsic stability, a calibration and thus a calibration unit is mandatory. To allow for maximum flexibility and modularity the calibration unit is physically split into three calibration units.

We show the design of the calibration units and their individual components, where possible. This includes the electronics, the mechanics, the software supporting and controlling the light guiding and calibration sources.

Abstract: This work is the first to solve the data-driven modeling problem for quantum instrumentation and enables the model built is interpretable. First, a data-driven physical iteration (DPI) modeling approach is proposed to solve the modeling problem of a complex physical system with nonlinear characteristics based on the dynamic behavior of a quantum system described by the phenomenological rate equation. Second, the proposed DPI modeling approach incorporates the fast sampling technique, which is proved feasible by the Taylor mean value theorem, to solve the modeling problem of a nonautonomous system. Third, the convergence of the proposed approach is proved by the least squares criterion and the law of large numbers. Finally, the DPI modeling approach is deployed in the optically pumped magnetometer (OPM) and spin-exchange relaxation-free comagnetometer (SERFCM), the physical parameters of the system are estimated while the quantum instrumentation modeling is completed. Numerical simulations and practical experiments support the theoretical results.