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The capability of borospherene to detect radioactive pollutants (radon and radium) is investigated utilizing density functional theory and nonequilibrium Green's function regime. The quantum transport is evaluated by calculating the density of states, chemical potential, transmission and molecular energy spectra, highest occupied molecular orbital (HOMO)–lowest unoccupied molecular orbital (LUMO) gap, electron densities, current–voltage curve, and differential and quantum conductance. LUMO-mediated transmission is observed in all the cases. The conduction considerably declines in B40 molecular junction doped with radioactive pollutants in comparison to pure B40 molecular junction. This decrease in conduction is due to reduced electron density and higher chemical potential in doped B40 junctions. Due to different values of current and differential conductance, we propose utilization of B40 in detecting the presence of radioactive pollutants in underground water. Also, all molecular junctions assay lifting of Coulomb blockade at equilibrium state; thus, these devices can be effectively utilized in single-electron transistor applications.
‘Keep calm and carry on’ was a wartime message to the British public that has achieved renewed fame in the last few years. The strategy was simple: in times of extreme difficulty a cool head combined with stoicism is an appropriate response to ensure a successful outcome. The latest major challenge to society (COVID-19) met with a very different response, and only history will reveal whether ‘Stay home and worry’ will be equally effective. In devising blueprints or strategies it is extremely important to have a clear idea of what you are trying to achieve, whether it be maintaining world freedom or stopping a pandemic. In the case of livestock agriculture, it is helping to feed a rapidly growing global population in harmony with the needs of current and future generations. I hope that I have stated this clearly, and calmly. If so, I ask you to picture a scene. We are on a Calm Farm. Dairy animals go about their daily lives contented, unhurried and focused on the simple feeding and socialising activities that are so important to them. Unstressed, their productive capacities and abilities to avoid and, when necessary, cope with physiological and pathological challenges are maximised. They are not alone: the exact same characteristics also apply to the farmer and husbandry staff that we meet. How is this calm farming approach relevant to the aspirations we had when we established the EU COST Action DairyCare? Our objective was to harness the power of computing technologies to assist our management of dairy livestock. A simple rearrangement leads us to Computing Assisted Livestock Management, CALM. In this short Research Reflection I shall assess how far we have come towards the achievement of sensible goals related to technological assessment of dairy animal wellbeing, and speculate on what more things both can and need to be done to finish the job. It is a personal account. DairyCare was a major collaboration involving several hundred active researchers. To involve them all would be impossible, and I do not pretend to speak for them all. As will become evident, the wide skills base that was assembled was so successful in its primary objectives that different skills, chiefly in economics, are now needed to exploit all of the technological advance that has been achieved. DairyCare succeeded in a second direction. Whilst the focus was technology development, by assembling a large cohort of biologists with animal welfare interests, it soon became apparent that technology should run alongside and help to enable improved management practices. This Special Issue is, therefore, in two sections. The first is dedicated to technology development and the second to a novel management practice that has the potential to significantly improve the wellbeing of cows and calves: cow-calf contact rearing. That section is introduced by my DairyCare colleague, Sigrid Agenäs.
Diversity of production systems and specific socio-economic barriers are key reasons explaining why the implementation of new technologies in small ruminants, despite being needed and beneficial for farmers, is harder than in other livestock species. There are, however, helpful peculiarities where small ruminants are concerned: the compulsory use of electronic identification created a unique scenario in Europe in which all small ruminant breeding stock became searchable by appropriate sensing solutions, and the largest small ruminant population in the world is located in Asia, close to the areas producing new technologies. Notwithstanding, only a few research initiatives and literature reviews have addressed the development of new technologies in small ruminants. This Research Reflection focuses on small ruminants (with emphasis on dairy goats and sheep) and reviews in a non-exhaustive way the basic concepts, the currently available sensor solutions and the structure and elements needed for the implementation of sensor-based husbandry decision support. Finally, some examples of results obtained using several sensor solutions adapted from large animals or newly developed for small ruminants are discussed. Significant room for improvement is recognized and a large number of multiple-sensor solutions are expected to be developed in the relatively near future.
This Research Reflection addresses the possibilities for Welfare Quality® to evolve from an assessment method based on data gathered on punctual visits to the farm to an assessment method based on sensor data. This approach could provide continuous and objective data, while being less costly and time consuming. Precision Livestock Farming (PLF) technologies enabling the monitorisation of Welfare Quality® measures are reviewed and discussed. For those measures that cannot be assessed by current technologies, some options to be developed are proposed. Picturing future dairy farms, the need for multipurpose and non-invasive PLF technologies is stated, in order to avoid an excessive artificialisation of the production system. Social concerns regarding digitalisation are also discussed.
The current contribution presents a new sinkage sensor specified for an unmanned ground vehicle to find the exact sinkage zone of a wheel interacting with the soil particles. This sensor will be wrapped around the wheel, and consequently, contact analog outputs will be used in soil deposition and bulldozing effect prediction. Furthermore, the new sensor will be used for a novel soil flow calculation estimating the total mass variation of the control volume of soil particles beneath the wheel. Accordingly, the spiral model simulating the displacement of the particle is implemented to calculate the soil deposition.
The various vision-based tactile sensors have been developed for robotic perception in recent years. In this paper, the novel soft robotic finger embedded with the visual sensor is proposed for perception. It consists of a colored soft inner chamber, an outer structure, and an endoscope camera. The bending perception algorithm based on image preprocessing and deep learning is proposed. The boundary of color regions and the position of marker dots are extracted from the inner chamber image and label image, respectively. Then the convolutional neural network with multi-task learning is trained to obtain bending states of the finger. Finally, the experiments are implemented to verify the effectiveness of the proposed method.
This paper introduces a new RGBD-Simultaneous Localization And Mapping (RGBD-SLAM) based on a revisited keyframe SLAM. This solution improves the localization by combining visual and depth data in a local bundle adjustment. Then, it presents an extension of this RGBD-SLAM that takes advantage of a partial knowledge of the scene. This solution allows using a prior knowledge of the 3D model of the environment when this latter is available which drastically improves the localization accuracy. The proposed solutions called RGBD-SLAM and Constrained RGBD-SLAM are evaluated on several public benchmark datasets and on real scenes acquired by a Kinect sensor. The system works in real time on a standard central processing units and it can be useful for certain applications, such as localization of lightweight robots, UAVs, and VR helmet.
Iron oxide nanoparticles presenting colloidal stability in water were prepared through precipitation and then surface-functionalized with varying citric acid (CA) concentrations (0.10, 0.25, 0.50, and 0.70 g/mL). CA introduced functionality and minimized agglomeration. Iron oxide nanoparticles with colloidal stability in water at physiological pH were obtained after functionalization with 0.25–0.70 g/mL CA, whereas iron oxide nanoparticles without stability in water were obtained after functionalization with 0.10 g/mL CA. An electrode for glucose detection was fabricated by self-assembling colloidal-stable γ-Fe2O3 NP–CA in water on indium tin oxide (ITO) glass, followed by a glucose oxidase (GOx) and Nafion layer. The optimal functionalization of the γ-Fe2O3 NPs was obtained at a CA concentration of 0.25 g/mL. The electrochemical properties and electrocatalytic behavior of the modified electrode designated as Nafion/GOx/γ-Fe2O3 NP–0.25 CA/ITO were then evaluated. The electrode showed high sensitivity for glucose detection of 995.57 and 5.81 µA/(mM cm2) within the linear ranges of 0.1–5.0 µM and 5.0 µM–20.0 mM, respectively. The modified electrode also demonstrated a low limit of detection, good repeatability of 2.5% (n = 10), and sufficient reproducibility of 3.2% (n = 5).
In mobile robot localization with multiple sensors, myriad problems arise as a result of inadequacies associated with each of the individual sensors. In such cases, methodologies built upon the concept of multisensor fusion are well-known to provide optimal solutions and overcome issues such as sensor nonlinearities and uncertainties. Artificial neural networks and fuzzy logic (FL) approaches can effectively model sensors with unknown nonlinearities and uncertainties. In this article, a robust approach for localization (positioning) of a mobile robot in indoor as well as outdoor environments is proposed. The neural network is utilized as a pseudo-sensor that models the global positioning system (GPS) and is used to predict the robot’s position in case of GPS signal loss in indoor environments. The data from proprioceptive sensors such as inertial sensors and GPS are fused using the Kalman and the complementary filter-based fusion schemes in the outdoor case. To eliminate the position inaccuracies due to wheel slippage, an expert FL system (FLS) is implemented and cascaded with the sensor fusion module. The proposed technique is tested both in simulation and in real scenarios of robot movements. The simulations and results from the experimental platform validate the efficacy of the proposed algorithm.
This paper proposes a differential sensor based on a pair of open split ring resonators (OSRR) operating in reflection. The output signal is thus the differential reflection coefficient of both resonators, intimately related to their dielectric loading. Thus, for identical loads in both sensing resonators, the individual reflection coefficients are equal, thereby providing an ideally null output signal. By contrast, when unequal dielectric loads truncate the symmetry, the reflection coefficients are different, resulting in a differential output signal related to the level of asymmetry. In order to ease the measurement of the output signal, a rat-race hybrid coupler is used. The OSRR sensing loads are connected to the coupled ports of the hybrid coupler, whereas the input signal is injected to the Δ-port, and the output signal is collected at the isolated port (Σ-port). By this means, the output signal, i.e. the differential reflection coefficient between both sensing loads, is obtained from the transmission coefficient of a simple two-port structure. For experimental validation purposes, the sensor is applied to the measurement of isopropanol content in aqueous solutions, and for that purpose, the sensitive regions are equipped with microfluidic channels.
In demand of simpler and alternative ground flutter test, a new technique that emulates flutter on the ground has recently emerged. In this paper, an improvement of the test technique is made and verified through the experimental work. The technique utilizes general ground vibration test (GVT) devices. The key idea is to emulate the distributed unsteady aerodynamic force by using a few concentrated actuator forces; referred to as emulated flutter test (EFT) technique. The EFT module contains two main logics; namely, real-time aerodynamic equivalent force calculator and multi-input-multi-output (MIMO) force controller. The module is developed to emulate the subsonic, linear flutter on a specified target structure, which is a thin aluminum clamped-plate with aspect ratio (AR) of 2.25. In this study, doublet hybrid method (DHM) was applied to model the subsonic aerodynamic force, which restricts the application to a 2-dimensional structure. Given that, correlation of several experimental works, such as wind-tunnel flutter test, EFT using laser displacement sensor (LDS), and EFT using accelerometer, on the target structure are investigated to verify the technique. In addition to the flutter boundary, flutter mode shape and trend of aerodynamic damping effect are also presented in this work. Together with these various kinds of test results, application of more compact actuator and an accelerometer as a sensor, makes the current technique the most advanced ground flutter emulation test method.
This review deals with the prospects and achievements of individual dairy cow management (IDCM) and the obstacles and difficulties encountered in attempts to successfully apply IDCM into routine dairy management. All aspects of dairy farm management, health, reproduction, nutrition and welfare are discussed in relation to IDCM. In addition, new IDCM R&D goals in these management fields are suggested, with practical steps to achieve them. The development of management technologies is spurred by the availability of off-the-shelf sensors and expanded recording capacity, data storage, and computing capabilities, as well as by demands for sustainable dairy production and improved animal wellbeing at a time of increasing herd size and milk production per cow. Management technologies are sought that would enable the full expression of genetic and physiological potential of each cow in the herd, to achieve the dairy operation's economic goals whilst optimizing the animal's wellbeing. Results and conclusions from the literature, as well as practical experience supported by published and unpublished data are analyzed and discussed. The object of these efforts is to identify knowledge and management routine gaps in the practical dairy operation, in order to point out directions and improvements for successful implementation of IDCM in the dairy cows' health, reproduction, nutrition and wellbeing.
Chapter 4 examines commercial imperatives for collections of sensor data by exploring the rapid development of smart home insurance business models. A brief history of smart home insurance is provided to situate three conceptualised models of smart home data exchange partnership involving insurers and smart home device or system providers. The models are entitled the Partnered Data Acquisition, Partnered Intermediary and Platform Entity models. Each model involves a partnership arrangement between an established insurer and a smart home device or system provider. However, while each model seeks to capitalise value from smart home sensor data, each model does so in different ways, across three spectra, namely, collection of data, connection to mutually beneficial services and condition setting. An analysis of relevant privacy policies is undertaken to highlight each model’s operational data structure, the sensor data collected and its foundational characteristics. In turn, this analysis highlights the commercial uses of smart home sensor data involving new logics, business relationships and intended service outcomes.
C-reactive protein (CRP) and cardiac troponin I (cTnI) biomolecules represent the earliest enzymes that appear in the blood when a cardiac injury occurs. Real-time and selective detection of these biomarkers is essential for the prediction and detection of cardiovascular diseases at an early stage. Here we report on the label-free specific detection of both proteins at picomolar concentrations using fabricated nanowire-based biosensors. We demonstrate a novel functionalization technique based on the attachment of dibenzocyclooctyne (DBCO)-linked troponin-specific aptamers to azide-functionalized silicon (Si) nanowire (NW) surface. Due to the fast and reliable immobilization of cTnI-specific aptamers and CRP-specific antibodies on the Si NWs, the fabricated devices can rapidly detect target biomolecules demonstrating high sensitivity. We confirm the attachment of proteins to the surface of Si NWs by atomic force microscopy (AFM). Moreover, we demonstrate that nanowire structures of different sizes enable the detection of biomarkers in a wide concentration range (from 1 pg/ml to 1 µg/ml), corresponding to CRP and cTnI elevation levels during the early stage of disease formation.
This paper discusses new components and approaches to make stretchable optical fiber sensors better meet the power and washability requirements of wearables. First, an all-polymer quick connector allows the light source and photosensor to be quickly detached for washing. Second, the paper investigates the possibility of driving the sensors using ambient light instead of an onboard light source. While optical strain sensors and touch sensors have advantages over electronic ones in wet environments, and the intrinsic stretchability of the fibers is useful for soft robotics and highly conformal wearables, the typical light-emitting diode (LED) light source consumes more power than an electronic resistive or capacitive strain sensor. In this work, ambient light of uniform but unknown intensity is demonstrated to drive an elastomeric optical touch sensor in a differential configuration.
Pneumonia has contributed greatly to child mortality, especially among children under the ages of five in sub-Saharan Africa, killing more children than the number of children dying from HIV/AIDS. The current methods of diagnosing pneumonia involved physical examination and chest x-ray which are limited by low accuracy, high error margins, higher cost, and stands the risks of inducing cancer. In this work, a low-cost, non-invasive biomedical device was designed and developed to improve accuracy in diagnosing pneumonia. The device functions to detect fluid in a lung consolidated by pneumonia. Dry grouting sponge was used as a phantom for a healthy lung, while a wet sponge was used to mimic a pneumonia-consolidated lung. Surface exciter was used to produce sound waves which travelled through one side of the phantom and are detected on the other end using an electronic stethoscope. The signals detected were digitally analyzed using MATLAB and AUDACITY software. The differences in resonant frequencies from the power spectrum analysis of sound waves as they travelled through the sponges were used to distinguish between a pneumonia-consolidated lung and a healthy lung.
Using water as an example, it is shown that monitoring the change in the loss tangent is a high sensitive method that allows determining the activation energy of relaxation processes in nanostructured water with high accuracy. The use of sensors, the electrodes of which are not in direct contact with the liquid under study is shown to be reasonable. The conditions for obtaining reliable information on the properties of water and its solutions are also justified, namely: measurements should be carried out using pulse methods for several seconds, and then measurements should be stopped to avoid contamination of the solutions studied by electrolysis products. The method of monitoring the magnitude of the loss tangent at fixed frequencies allows the acidity of solutions (pH value) to be controlled at the same time without using specialized instruments for acidity studying.
We demonstrate the fabrication, by exclusive means of inkjet-printing, of capacitive relative humidity sensors on flexible, plastic substrate. These sensors can be successfully used for the measurement of relative-humidity in both air and common soil. We also show that the same technique may be used for the fabrication of the same type of sensors on the surface of the leaves of Elægnus Ebbingei (silverberry).Our results demonstrate the suitability of leaves as substrate for printed electronics and pave the way to the next generation of sensors to be used in fields such as agriculture and flower farming.
Light Detection and Ranging (LiDAR) is a primary sensor for autonomous vehicles to recognize surroundings. It detects near-infrared (NIR) light pulses, typically at 905nm, which is emitted and reflected by surrounding objects. Here, the fact of the matter is that conventional black or dark-tone cars with extremely low NIR reflection are hard to be detected by LiDAR and endanger the future highway. In this work, we propose to use platelet-shaped effect pigments with visible absorption and NIR reflectivity. Copper(Ⅱ) oxide and Silicon dioxide multilayer are theoretically investigated with different numbers of layers and thicknesses. The optimized structures appear various dark-tone colors with high NIR-reflectivity over 90%.
Propagating inhomogeneous electromagnetic waves called surface plasmon polaritons (SPPs) can be excited by free-space beams on corrugated conducting surfaces at resonance angles determined by corrugation period, permittivity, and optical frequency. SPPs are coupled to and co-propagate with surface charge displacements. Complete electrical isolation of individual conducting corrugations prevents the charge displacement necessary to sustain an SPP, such that excitation resonances of traveling SPPs are absent. However, SPPs can be excited via electric induction if a smooth conducting surface exists below and nearby the isolated conducting corrugations. The dependence of SPP excitation resonances on that separation is experimentally investigated here at long-wave infrared wavelengths. We find that excitation resonances for traveling SPPs broaden and disappear as the dielectric’s physical thickness is increased beyond ~1% of the free-space wavelength. The resonance line width increases with refractive index and optical thickness of the dielectric.