Physical Interface Research Articles

The importance of incorporating geology, soil, and landscape knowledge in freshwater farm planning in Aotearoa New Zealand

Over half of Aotearoa New Zealand’s (NZ’s) land area is under agriculture or forestry production. Long term monitoring has shown declines in freshwater quality in regions with the most intensive agriculture. The New Zealand government has historically focused on reducing the impact of agriculture on water quality through its Resource Management Act 1991. Lack of improvement in freshwater quality has resulted in the 2020 Essential Freshwater package of reforms which will require all pastoral farms >20 ha in size and all arable farms > 5 ha in size to develop a Freshwater Farm Plan (FFP) by a certified Freshwater Farm Planner. As far as we are aware, New Zealand is the first country in the world to mandate compulsory FFPs. This paper describes the key geological, soil, and landscape factors that need to be considered in an FFP for it to be successful in meeting the 2020 Essential Freshwater objectives. We argue that a greater emphasis should be placed on understanding a farm’s natural resources, as they provide the physical interface between the farming system and both the freshwater and atmospheric ecosystems. Documenting our learning in this area could assist other countries considering Freshwater Farm Planning as a strategy to reduce the impact of agriculture on freshwater quality.

Utilising the co-occurrence of user interface interactions as a risk indicator for smartphone addiction

The push to a connected world where people carry an always-online device which has been designed to maximise instant gratification and prompts users via notifications has lead to a surge of potentially problematic behaviour as a result. This has lead to a rising interest in addressing and understanding the addictiveness of smartphone usage, as well as for particular applications (apps). However, capturing addiction from usage involves not only assessment of potential addiction risk but also requires understanding of the complex interactions that define user behaviour and how these can be effectively isolated and summarised. In this paper, we examine the correlation of physical user interface (UI) interactions (e.g. taps and scrolls) and smartphone addiction risk using a large dataset of those smartphone events (65,093,343, N=301,024 sessions) collected from 64 users over an 8-week period with an accompanying smartphone addiction survey. Our novel method which reports on the probability of a users addiction risk and in a model case we show how it was be used to identify 57 of 64 users correctly. This supports our observations of UI events during sessions of usage being indicative of addiction risk while improving previous approaches which rely on summative data such as screen on time. Within this we also find that users only exhibit addictive behaviour in a subset of all sessions while using their smartphone.

Pectin Stabilized Fish Gelatin Emulsions: Physical Stability, Rheological, and Interaction Properties.

Pectin, a kind of natural polysaccharide, shows the attractive potential as a natural stabilizer for protein emulsion. The aim of this study is to investigate the effect of pectin on the physical stability, rheology, interface, and interaction properties of the fish gelatin (FG) emulsion, as pectin was utilized to improve the stability of FG, fish oil emulsion. During the study, when pH < 6, the FG-pectin emulsion displayed better storage stability and salinity tolerance. Analyzing the result, pectin could avoid phase separation at the freeze-thaw process and prevent the liquid-gel transition of FG emulsions during storage. On the other hand, when pH ≥ 6, the emulsion displayed high viscosity due to the complex flocculation and stratified during long-term storage. Electrostatic interactions, hydrophobic interactions, and hydrogen bonding of the FG-pectin complexes in the emulsion were all reduced. Overall, pectin improved the stability of FG emulsions through electrostatic repulsion, hydrophobic interactions, and steric hindrance.

Balancing energy and protein homeostasis at ER-mitochondria contact sites.

The endoplasmic reticulum (ER) is the largest organelle of the cell and participates in multiple essential functions, including the production of secretory proteins, lipid synthesis, and calcium storage. Sustaining proteostasis requires an intimate coupling with energy production. Mitochondrial respiration evolved to be functionally connected to ER physiology through a physical interface between both organelles known as mitochondria-associated membranes. This quasi-synaptic structure acts as a signaling hub that tunes the function of both organelles in a bidirectional manner and controls proteostasis, cell death pathways, and mitochondrial bioenergetics. Here, we discuss the main signaling mechanisms governing interorganellar communication and their putative role in diseases including cancer and neurodegeneration.

The Computational Science of Klaus Hasselmann

We review the work of Klaus Hasselmann, one of three recipients of the Nobel Prize in Physics 2021, from the perspective of computational science and engineering (CSE). In addition to highlighting Hasselmann’s extensive contributions to climate science, we shine a light on his groundbreaking work in ocean surface wave dynamics and prediction, which preceded his career in climate research. Early on, Hasselmann also gained a strong interest in elementary particle physics, which led him to develop, in his spare time, a unified theory of particles and fields, and which we outline here. With this review we hope to entice computational scientists to delve deeper into Hasselmann’s extraordinarily broad work at the interface of climate physics, mathematics, and scientific computing, and to appreciate the central role that CSE continues to play in climate research.

A Hybrid Learning and Optimization Framework to Achieve Physically Interactive Tasks With Mobile Manipulators

This paper proposes a hybrid learning and optimization framework for mobile manipulators for complex and physically interactive tasks. The framework exploits an admittance-type physical interface to obtain intuitive and simplified human demonstrations and Gaussian Mixture Model (GMM)/Gaussian Mixture Regression (GMR) to encode and generate the learned task requirements in terms of position, velocity, and force profiles. Next, using the desired trajectories and force profiles generated by GMM/GMR, the impedance parameters of a Cartesian impedance controller are optimized online through a Quadratic Program augmented with an energy tank to ensure the passivity of the controlled system. Two experiments are conducted to validate the framework, comparing our method with two approaches with constant stiffness (high and low). The results showed that the proposed method outperforms the other two cases in terms of trajectory tracking and generated interaction forces, even in the presence of disturbances such as unexpected end-effector collisions.

Design and Implementation of a Rehabilitation Upper-limb Exoskeleton Robot Controlled by Cognitive and Physical Interfaces.

This paper presents an upper limb exoskeleton that allows cognitive (through electromyography signals) and physical user interaction (through load cells sensors) for passive and active exercises that can activate neuroplasticity in the rehabilitation process of people who suffer from a neurological injury. For the exoskeleton to be easily accepted by patients who suffer from a neurological injury, we used the ISO9241-210:2010 as a methodology design process. As the first steps of the design process, design requirements were collected from previous usability tests and literature. Then, as a second step, a technological solution is proposed, and as a third step, the system was evaluated through performance and user testing. As part of the technological solution and to allow patient participation during the rehabilitation process, we have proposed a hybrid admittance control whose input is load cell or electromyography signals. The hybrid admittance control is intended for active therapy exercises, is easily implemented, and does not need musculoskeletal modeling to work. Furthermore, electromyography signals classification models and features were evaluated to identify the best settings for the cognitive human–robot interaction.

Soft Robotic Suits: State of the Art, Core Technologies, and Open Challenges

Wearable robots are undergoing a disruptive transition, from the rigid machines that populated the science-fiction world in the early eighties to lightweight robotic apparel, hardly distinguishable from our daily clothes. In less than a decade of development, soft robotic suits have achieved important results in human motor assistance and augmentation. In this paper, we start by giving a definition of soft robotic suits and proposing a taxonomy to classify existing systems. We then critically review the modes of actuation, the physical human-robot interface and the intention-detection strategies of state of the art soft robotic suits, highlighting the advantages and limitations of different approaches. Finally, we discuss the impact of this new technology on human movements, for both augmenting human function and supporting motor impairments, and identify areas that are in need of further development.

Superhydrophobic Terrestrial Cyanobacteria and Land Plant Transition.

Plants and other organisms have evolved structures and mechanisms for colonizing land since the Early Ordovician. In this context, their surfaces, the crucial physical interface with the environment, are mainly considered barriers against water loss. It is suggested that extreme water repellency (superhydrophobicity) was an additional key innovation for the transition of algae from water to land some 400 mya. Superhydrophobicity enhances gas exchange on land and excludes aquatic competitors in water films. In a different context, in material science and surface technology, superhydrophobicity has also become one of the most important bioinspired innovations enabling the avoidance of water films and contamination. Here, we present data for an extremely water-repellent cyanobacterial biofilm of the desiccation tolerant Hassallia byssoidea providing evidence for a much earlier prokaryotic Precambrian (ca. 1–2 bya) origin of superhydrophobicity and chemical heterogeneities associated with land transition. The multicellular cyanobacterium is functionally differentiated in a submerged basal hydrophilic absorbing portion like a “rhizoid” and an upright emersed superhydrophobic “phyllocauloid” filament for assimilation, nitrogen fixation, and splash dispersed diaspores. Additional data are provided for superhydrophobic surfaces in terrestrial green algae and in virtually all ancestral land plants (Bryophytes, ferns and allies, Amborella, Nelumbo), slime molds, and fungi. Rethinking of superhydrophobicity as an essential first step for life in terrestrial environments is suggested.

Geometry, analysis, and morphogenesis: Problems and prospects

The remarkable range of biological forms in and around us, such as the undulating shape of a leaf or flower in the garden, the coils in our gut, or the folds in our brain, raise a number of questions at the interface of biology, physics, and mathematics. How might these shapes be predicted, and how can they eventually be designed? We review our current understanding of this problem, which brings together analysis, geometry, and mechanics in the description of the morphogenesis of low-dimensional objects. Starting from the view that shape is the consequence of metric frustration in an ambient space, we examine the links between the classical Nash embedding problem and biological morphogenesis. Then, motivated by a range of experimental observations and numerical computations, we revisit known rigorous results on curvature-driven patterning of thin elastic films, especially the asymptotic behaviors of the solutions as the (scaled) thickness becomes vanishingly small and the local curvature can become large. Along the way, we discuss open problems that include those in mathematical modeling and analysis along with questions driven by the allure of being able to tame soft surfaces for applications in science and engineering.

Assessing the Effect of Scaling High-Aspect-Ratio ISFET with Physical Model Interface for Nano-Biosensing Application

In this paper, technology computer-aided design (TCAD) simulations of ion-sensitive field-effect transistors (ISFETs) are implemented using a physical model interface (PMI). Our simulations are based on a combination of analytical and numerical methods which are combined in a single simulation framework. ISFETs with different Si channel widths, such as 10nm, 40nm and 50nm have been simulated for this work. Our results reveal a correlation between the device dimensions and ISFET sensitivity (α). Also, the variations of H+ ions, OH- ions and surface potential (Ψ0) with respect to distance from the electrolyte/oxide interface are analyzed

Soft Robot Skin With Conformal Adaptability for On-Body Tactile Perception of Collaborative Robots

Robot skin, as the physical interface between collaborative robots (cobots) and the external environments, could mediate on-body tactile signals for cobots to respond timely once a collision occurs during tasks and thus avoid damages to both cobots and surroundings. To achieve effective on-body tactile perception, robot skin should possess adequate conformal adaptability to be covered on various complex contours on the cobot, such as joints, while maintaining accurate and rapid sensing performance. In this letter, a soft robot skin consisting of an array of force-sensing units and a substrate with a serpentine structure was developed, both of which were made of porous material. The serpentine structure endows the developed skin with stretchable attributes. Thus, the skin could be conformally attached to complex surfaces of a cobot with less local stress, which was validated by finite element analysis. Taking the advantage of porous microstructure, the sensing units embedded in the substrate have exhibited high sensitivity and fast response time under external force, which are essential factors in real-time collision detection. Finally, experimental validation was carried out to verify the feasibility of deploying the developed soft robot skin on a robot arm to provide on-body tactile perception for a cobot.

TelePhysicalOperation: Remote Robot Control Based on a Virtual “Marionette” Type Interaction Interface

Teleoperation permits to control robots from a safe distance while performing tasks in a remote environment. Kinematic differences between the input device and the remotely controlled manipulator or the existence of redundancy in the remote robot may pose challenges in moving intuitively the remote robot as desired by the human operator. Motivated by the above challenges, this work introduces TelePhysicalOperation, a novel teloperation concept, which relies on a virtual physical interaction interface between the human operator and the remote robot in a manner that is equivalent to a “Marionette” based interaction interface. With the proposed approach, the user can virtually “interact” with the remote robot, through the application of virtual forces, which are generated by the operator tracking system and can be then selectively applied to any body part of the remote robot along its kinematic chain. This leads to the remote robot generating motions that comply with the applied virtual forces, thanks to the underlying control architecture. The proposed method permits to command the robot from a distance by exploring the intuitiveness of the “Marionette” based physical interaction with the robot in a virtual/remote manner. The details of the proposed approach are introduced and its effectiveness is demonstrated through a number of experimental trials executed on the CENTAURO, a hybrid leg-wheel platform with an anthropomorphic upper body.

A robust and eco-friendly waterborne anti-corrosion composite coating with multiple synergistic corrosion protections

Environmentally friendly waterborne coatings have received significant attention recently due to their lower volatile organic compounds (VOCs) emission than solvent-based coatings, but their practical applications are severely limited by poor barrier properties. Herein, a novel and robust waterborne OBN-PA-Zn-D/WEP anti-corrosion composite coating was successfully fabricated by utilizing hydroxyl-functionalized h-BN (OBN) nanosheets , phytic acid (PA), Zn 2+ and dicyandiamide. Due to the π-π interactions between OBN and organic-inorganic PA-Zn-D complex, the dispersibility of OBN-PA-Zn-D nanosheets was improved, which was beneficial for enhancing the physical barrier properties of OBN-PA-Zn-D/WEP composite coating. After adding dicyandiamide, the interface compatibility between OBN-PA-Zn-D nanosheets and the waterborne resin matrix was significantly improved, greatly reducing the defects inside the OBN-PA-Zn-D/WEP composite coating. In addition, PA and Zn 2+ formed protective layer in the defect area to inhibit the corrosion of anode and cathode . Therefore, under the effect of multiple synergistic corrosion protections , the eco-friendly waterborne OBN-PA-Zn-D/WEP composite coating exhibited unique anti-corrosion performance that was greatly improved compared with the conventional waterborne epoxy coatings . • A robust and eco-friendly waterborne anti-corrosion composite coating was prepared. • OBN-PA-Zn-D/WEP composite coating provided strong corrosion protection. • Physical barrier, corrosion inhibition and interface enhancement synergistically enhance anti-corrosion ability.

Designing Physical Human-Robot Interaction Interfaces: A Scalable Method for Simulation Based Design.

Designing the physical coupling between the human body and the wearable robot is a challenging endeavor. The typical approach of tightening the wearable robot against the body, and softening the interface materials does not work well. It makes the task of simultaneously improving comfort, and anchoring the robot to the body at the physical human robot interaction interface (PHRII), difficult. Characterizing this behavior experimentally with sensors at the interface is challenging due to the soft-soft interactions between the PHRII materials and the human tissue. Therefore, modeling the interaction between the wearable robot and the hand is a necessary step to improve design. In this paper, we introduce a methodology to systematically improve the design of the PHRII by combining experimentally measured characteristics of the biological tissue with a novel dynamic modeling tool. Using a novel and scalable simulation framework, HuRoSim, we quantified the interaction between the human hand and an exoskeleton. In the first of our experiments, we use HuRoSim to predict complex interactions between the hand and the coupled exoskeleton. In our second experiment, we then demonstrate how HuRoSim can be coupled with experimental measurements of the stiffness of the dorsal surface of the hand to optimize the design of the PHRII. This approach of data-driven modeling of the interaction between the body and a wearable robot, such as a hand exoskeleton, can be generalized to other forms of wearable devices as well, demonstrating a scalable and systematic method for improving the design of the PHRII for future devices coupled to the body.

Benchmarking exchange-correlation functionals in the spin-polarized inhomogeneous electron gas under warm dense conditions

Warm dense matter is a highly active research area both at the frontier and interface of material science and plasma physics. We assess the performance of commonly used exchange-correlation (XC) approximation (LDA, PBE, PBEsol, and AM05) in the spin-polarized inhomogeneous electron gas under warm dense conditions based on exact path-integral quantum Monte-Carlo calculations. This extends our recent analysis on the relevance of inhomogeneities in the spin-unpolarized warm dense electron gas [Z.~Moldabekov et al., J. Chem. Phys. 155, 124116 (2021)]. We demonstrate that the predictive accuracy of these XC functionals deteriorates with (1) a decrease in density (corresponding to an increase in the inter-electronic correlation strength) and (2) an increase of the characteristic wave number of the density perturbation. We provide recommendations for the applicability of the considered XC functionals at conditions typical for warm dense matter. Furthermore, we hint at future possibilities for constructing more accurate XC functionals under these conditions.

Editorial: Scaling the Turbulence Edifice.

Turbulence is unique in its appeal across physics, mathematics and engineering. And yet a microscopic theory, starting from the basic equations of hydrodynamics, still eludes us. In the last decade or so, new directions at the interface of physics and mathematics have emerged, which strengthens the hope of ‘solving’ one of the oldest problems in the natural sciences. This two-part theme issue unites these new directions on a common platform emphasizing the underlying complementarity of the physicists’ and the mathematicians’ approaches to a remarkably challenging problem.This article is part of the theme issue ‘Scaling the turbulence edifice (part 1)’.

Novel Hybrid Model for Intrusion Prediction on Cyber Physical Systems’ Communication Networks based on Bio-inspired Deep Neural Network Structure

There are growing concerns on the security of communication networks of Cyber Physical Systems (CPSs). In a typical Cyber Physical System (CPS), the plant, actuators, sensors and controller interface through a communication network, which enable computing and data transmission in the CPS. Consequently, the communication network is vulnerable to sophisticated attacks. Attacks on CPSs communication networks can cause damage to critical resources and infrastructure. In this sense, it is crucial to accurately predict these attacks in order to minimise their impact on the target CPSs networks. In this paper, we propose a novel hybrid approach for intrusion prediction on CPSs communication networks. We use a bio-inspired hyperparameter search technique to generate an improved deep neural network structure based on the core hyperparameters of a neural network. Furthermore, we derive a prediction model based on the improved neural network structure and evaluate its performance using two well-known datasets, namely, the CICIDS2017 and UNSW-NB15 datasets. Results obtained from rigorous experimentation show that our model can predict diverse attack types with high accuracy, low error and false positive rates, and outperforms state-of-the-art comparative models.

A comparison of different methods for modelling the physical human-exoskeleton interface

A comparison of different methods for modelling the physical human-exoskeleton interface

Membranes– future for sustainable gas and liquid separation?

Today, chemical engineers seek innovative and emerging technologies for the improved separation of liquids and gases in different fields of chemistry, foods, biotechnology, environmental-related areas, among others. These potential technologies must meet the key requirements of selective separation as well as overcome the main constraints of typical separation methods. In addition to this, such emerging technologies should also meet the key principles of “green chemistry”, aimed at preserving the environment while utilizing eco-friendly feedstocks and processes. In this sense, membrane technologies, which use a perm selective physical interface (so-called membrane), have been investigated as promising separation techniques over the last decades. The membrane, as the key element for the separation, has been the main scope of study in membrane science and technology over recent years. Depending on the membrane process, the membrane can synergistically offer both productivity (in terms of permeability) and selectivity towards specific liquid and gas phases. This graphical review timely brings a short but concise overview of the current role of specific membrane technologies (ultrafiltration, nanofiltration, pervaporation, membrane distillation and membrane gas separation) in various fields according to their advantages, as well as their applicability. Lately, the ongoing progress and future trends in each membrane technology will be given.