Empirical validation of Conformal Prediction for trustworthy skin lesions classification.

Background And Objective: Uncertainty quantification is a pivotal field that contributes to realizing reliable and robust systems. It becomes instrumental in fortifying safe decisions by providing complementary information, particularly within high-risk applications. existing studies have explored various methods that often operate under specific assumptions or necessitate substantial modifications to the network architecture to effectively account for uncertainties.

DOPESLAM: High-Precision ROS-Based Semantic 3D SLAM in a Dynamic Environment.

Recent advancements in deep learning techniques have accelerated the growth of robotic vision systems. One way this technology can be applied is to use a mobile robot to automatically generate a 3D map and identify objects within it. This paper addresses the important challenge of labeling objects and generating 3D maps in a dynamic environment.

Experimental comparison of direct and indirect aptamer-based biochemical functionalization of electrolyte-gated graphene field-effect transistors for biosensing applications.

Aptamer-based electrolyte-gated graphene field-effect transistor (EGFET) biosensors have gained considerable attention because of their rapidity and accuracy in terms of quantification of a wide range of biomarkers. Functionalization of the graphene channel of EGFETs with aptamer biorecognition elements (BREs) is a crucial step in fabrication of EGFET aptasensors. This paper presents a comprehensive comparison of commonly used biochemical functionalization approaches applied for preparation of sensing films in EGFET aptasensors, namely indirect and direct immobilization of BREs.

A Critical Analysis of Industrial Human-Robot Communication and Its Quest for Naturalness Through the Lens of Complexity Theory.

Human-robot communication is one of the actively researched fields to enable efficient and seamless collaboration between a human and an intelligent industrial robotic system. The field finds its roots in human communication with the aim to achieve the "naturalness" inherent in the latter. Industrial human-robot communication pursues communication with simplistic commands and gestures, which is not representative of an uncontrolled real-world industrial environment.

Synthesizing Rolling Bearing Fault Samples in New Conditions: A Framework Based on a Modified CGAN.

Bearings are vital components of rotating machines that are prone to unexpected faults. Therefore, bearing fault diagnosis and condition monitoring are essential for reducing operational costs and downtime in numerous industries. In various production conditions, bearings can be operated under a range of loads and speeds, which causes different vibration patterns associated with each fault type.

On-chip-based electrochemical biosensor for the sensitive and label-free detection of Cryptosporidium.

Cryptosporidium, an intestinal protozoan pathogen, is one of the leading causes of death in children and diarrhea in healthy adults. Detection of Cryptosporidium has become a high priority to prevent potential outbreaks. In this paper, a simple, easy to fabricate, and cost-effective on-chip-based electrochemical biosensor has been developed for the sensitive and label-free detection of Cryptosporidium oocysts in water samples.

Portable on-chip colorimetric biosensing platform integrated with a smartphone for label/PCR-free detection of Cryptosporidium RNA.

Cryptosporidium, a protozoan pathogen, is a leading threat to public health and the economy. Herein, we report the development of a portable, colorimetric biosensing platform for the sensitive, selective and label/PCR-free detection of Cryptosporidium RNA using oligonucleotides modified gold nanoparticles (AuNPs). A pair of specific thiolated oligonucleotides, complementary to adjacent sequences on Cryptosporidium RNA, were attached to AuNPs.

Comprehensive review of conventional and state-of-the-art detection methods of Cryptosporidium.

Cryptosporidium is a critical waterborne protozoan pathogen found in water resources that have been a major cause of death and serious illnesses worldwide, costing millions of dollars annually for its detection and treatment. Over the past several decades, substantial efforts have been made towards developing techniques for the detection of Cryptosporidium. Early diagnostic techniques were established based on the existing tools in laboratories, such as microscopes.

Micron-sized particle separation with standing surface acoustic wave-Experimental and numerical approaches.

Traditional cell/particle isolation methods are time-consuming and expensive and can lead to morphology disruptions due to high induced shear stress. To address these problems, novel lab-on-a-chip-based purification methods have been employed. Among various methods introduced for the separation and purification of cells and synthetics particles, acoustofluidics has been one of the most effective methods.

A Camera Intrinsic Matrix-Free Calibration Method for Laser Triangulation Sensor.

Laser triangulation sensors (LTS) are widely used to acquire depth information in industrial applications. However, the parameters of the components, e.g.

Low-Cost Graphene-Based Digital Microfluidic System.

In this work, the laser-scribing technique was used as a low-cost, rapid and facile method for fabricating digital microfluidic (DMF) systems. Laser-scribed graphene (LSG) electrodes are directly synthesized on flexible substrates to pattern the DMF electrode arrays. This facilitates the DMF electrodes' fabrication process by eliminating many microfabrication steps.

Deep Learning Sensor Fusion for Autonomous Vehicle Perception and Localization: A Review.

Autonomous vehicles (AV) are expected to improve, reshape, and revolutionize the future of ground transportation. It is anticipated that ordinary vehicles will one day be replaced with smart vehicles that are able to make decisions and perform driving tasks on their own. In order to achieve this objective, self-driving vehicles are equipped with sensors that are used to sense and perceive both their surroundings and the faraway environment, using further advances in communication technologies, such as 5G.

Parametric study on the geometrical parameters of a lab-on-a-chip platform with tilted planar electrodes for continuous dielectrophoretic manipulation of microparticles.

Advances in lab-on-a-chip (LOC) devices have led to significant improvements in the on-chip manipulation, separation, sorting, and isolation of particles and cells. Among various LOC-based approaches such as inertia-based methods, acoustophoresis, and magnetophoresis, the planar-slanted-electrode dielectrophoresis (DEP) method has demonstrated great potential as a label-free, cost-effective, and user-friendly approach. However, the devices built based on this method suffer from low flow throughput compared to devices functioning based on other LOC-based manipulation approaches.

High Throughput Screening of Cell Mechanical Response Using a Stretchable 3D Cellular Microarray Platform.

Cells in vivo are constantly subjected to multiple microenvironmental mechanical stimuli that regulate cell function. Although 2D cell responses to the mechanical stimulation have been established, these methods lack relevance as physiological cell microenvironments are in 3D. Moreover, the existing platforms developed for studying the cell responses to mechanical cues in 3D either offer low-throughput, involve complex fabrication, or do not allow combinatorial analysis of multiple cues.

Fabrication of SnO Composite Nanofiber-Based Gas Sensor using the Electrospinning Method for Tetrahydrocannabinol (THC) Detection.

This paper presents the development of a metal oxide semiconductor (MOS) sensor for the detection of volatile organic compounds (VOCs) which are of great importance in many applications involving either control of hazardous chemicals or noninvasive diagnosis. In this study, the sensor is fabricated based on tin dioxide (SnO) and poly(ethylene oxide) (PEO) using electrospinning. The sensitivity of the proposed sensor is further improved by calcination and gold doping.

A Nanostructured Microfluidic Artificial Olfaction for Organic Vapors Recognition.

Selective and sensitive detection of volatile organic compounds (VOCs) is of great importance in applications involving monitoring of hazardous chemicals or non-invasive diagnosis. Here, polymethyl methacrylate nanoparticles with acetone recognition sites are synthesized and integrated into a 3D-printed microfluidic platform to enhance the selectivity of the device. The proposed microfluidic-based olfaction system includes two parylene C-coated microchannels, with or without polymer nanoparticles.

Graphene-Coated Spandex Sensors Embedded into Silicone Sheath for Composites Health Monitoring and Wearable Applications.

This study presents a low-cost, tunable, and stretchable sensor fabricated based on spandex (SpX) yarns coated with graphene nanoplatelets (GnP) through a dip-coating process. The SpX/GnP is wrapped into a stretchable silicone rubber (SR) sheath to protect the conductive layer against harsh conditions, which allows for fabricating washable wearable sensors. Dip-coating parameters are optimized to obtain the maximum GnP coating rate.

Label-Free Capacitive Biosensor for Detection of .

, an intestinal protozoan pathogen, is one of the leading causes of diarrhea in healthy adults and death in children. Detection of oocysts has become a high priority to prevent potential outbreaks. In this paper, a label-free interdigitated-based capacitive biosensor has been introduced for the detection of oocysts in water samples.

3D Printing-Based Integrated Water Quality Sensing System.

The online and accurate monitoring of drinking water supply networks is critically in demand to rapidly detect the accidental or deliberate contamination of drinking water. At present, miniaturized water quality monitoring sensors developed in the laboratories are usually tested under ambient pressure and steady-state flow conditions; however, in Water Distribution Systems (WDS), both the pressure and the flowrate fluctuate. In this paper, an interface is designed and fabricated using additive manufacturing or 3D printing technology-material extrusion (Trade Name: fused deposition modeling, FDM) and material jetting-to provide a conduit for miniaturized sensors for continuous online water quality monitoring.

Integration of biosensors into digital microfluidics: Impact of hydrophilic surface of biosensors on droplet manipulation.

Several studies have been performed on the integration of biosensors into digital microfluidics (DMF). Despite the general success in their detection capabilities, there are still two challenges associated with the integration of biosensors into DMF: (1) complete removal of the droplet containing the analytes from the sensing surface; and (2) biochemical regeneration of the biosensor involving detaching the target analyte from the receptor after each round of sensing. The latter is case dependent and the solution can vary from one application to another.

Microfluidics Integrated Biosensors: A Leading Technology towards Lab-on-a-Chip and Sensing Applications.

A biosensor can be defined as a compact analytical device or unit incorporating a biological or biologically derived sensitive recognition element immobilized on a physicochemical transducer to measure one or more analytes. Microfluidic systems, on the other hand, provide throughput processing, enhance transport for controlling the flow conditions, increase the mixing rate of different reagents, reduce sample and reagents volume (down to nanoliter), increase sensitivity of detection, and utilize the same platform for both sample preparation and detection. In view of these advantages, the integration of microfluidic and biosensor technologies provides the ability to merge chemical and biological components into a single platform and offers new opportunities for future biosensing applications including portability, disposability, real-time detection, unprecedented accuracies, and simultaneous analysis of different analytes in a single device.

Droplet sensing by measuring the capacitance between coplanar electrodes in a digital microfluidic system.

In this paper, we report a novel method of droplet sensing in a two-plate digital microfluidic system (DMS) based on coplanar capacitance measurement. The total capacitance between the two adjacent electrodes on the lower plate depends on the position of the droplet. Both numerical and experimental results show that the capacitance is maximal at the midpoint between two electrodes.

Capacitance-based droplet position estimator for digital microfluidic devices.

Digital microfluidic (DMF) devices manipulate minuscule droplets through basic fluidic operations including droplet transport, mixing and splitting commonly known as the building blocks for complete laboratory analyses on a single device. A DMF device can house various chemical species and confine chemical reactions within the volume of a droplet much like a micro-reactor. The automation of fluidic protocols requires a feedback controller whose sensor is capable of locating droplets independent of liquid composition (or previous knowledge of liquid composition).

In situ characterization of microdroplet interfacial properties in digital microfluidic systems.

Real-time characterization of digital microfluidic lab-on-a-chip devices is important for biological and chemical applications in which the properties of the microdroplet are time variant. In this paper, a method for in situ characterization of microdroplet interfacial properties is introduced. The proposed characterization method relies on two submodules, namely the contact angle and capacitance sampling submodules, in a digital microfluidic system.

Decision making under uncertainty--an example for seismic risk management.

Decision-making techniques are used to select the "best" alternatives under multiple and often conflicting criteria. Multicriteria decision making (MCDM) necessitates to incorporate uncertainties in the decision-making process. The major thrust of this article is to extend the framework proposed by Yager for multiple decisionmakers and fuzzy utilities (payoffs).