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Long or Post COVID-19 is a condition of collected symptoms persisted after recovery from COVID-19. Host genetic factors play a crucial role in developing Long COVID-19, and GWAS studies identified several SNPs/genes in various ethnic populations. In African-American population two SNPS, rs10999901 (C>T, p = 3.6E-08, OR = 1.39, MAF-0,27, GRCH38, chr10:71584799 bp) and rs1868001 (G>A, p = 6.7E-09, OR = 1.40, MAF-0.46, GRCH38, chr10:71587815 bp) and in Hispanic population, rs3759084 (A>C, p = 9.7E-09, OR = 1.56, MAF-0.17, chr12: 81,110,156 bp) are strongly associated with Long COVID-19. All these three SNPs reside in noncoding regions implying their regulatory function in the genome. In silico dissection suggests that rs10999901 and rs1868001 physically interact with the CDH23 and C10orf105 genes. Both SNPs act as distant enhancers and bind with several transcription factors (TFs). Further, rs10999901 SNP is a CpG that is methylated in CD4++ T cells and monocytes and loses its methylation due to transition from C>T. rs3759084 is located in the promoter (− 687 bp) of MYF5, acts as a distant enhancer, and physically interacts with PTPRQ. These results offer plausible explanations for their association and provide the basis for experiments to dissect the development of symptoms of Long COVID-19. [ABSTRACT FROM AUTHOR]

Abstract Human–robot physical interaction contains crucial information for optimizing user experience, enhancing robot performance, and objectively assessing user adaptation. This study introduces a new method to evaluate human–robot interaction and co-adaptation in lower limb exoskeletons by analyzing muscle activity and interaction torque as a two-dimensional random variable. We introduce the interaction portrait (IP), which visualizes this variable’s distribution in polar coordinates. We applied IP to compare a recently developed hybrid torque controller (HTC) based on kinematic state feedback and a novel adaptive model-based torque controller (AMTC) with online learning, proposed herein, against a time-based controller (TBC) during treadmill walking at varying speeds. Compared to TBC, both HTC and AMTC significantly lower users’ normalized oxygen uptake, suggesting enhanced user-exoskeleton coordination. IP analysis reveals that this improvement stems from two distinct co-adaptation strategies, unidentifiable by traditional muscle activity or interaction torque analyses alone. HTC encourages users to yield control to the exoskeleton, decreasing overall muscular effort but increasing interaction torque, as the exoskeleton compensates for user dynamics. Conversely, AMTC promotes user engagement through increased muscular effort and reduces interaction torques, aligning it more closely with rehabilitation and gait training applications. IP phase evolution provides insight into each user’s interaction strategy formation, showcasing IP analysis’s potential in comparing and designing novel controllers to optimize human–robot interaction in wearable robots.

Human–robot physical interaction contains crucial information for optimizing user experience, enhancing robot performance, and objectively assessing user adaptation. This study introduces a new method to evaluate human–robot interaction and co-adaptation in lower limb exoskeletons by analyzing muscle activity and interaction torque as a two-dimensional random variable. We introduce the interaction portrait (IP), which visualizes this variable’s distribution in polar coordinates. We applied IP to compare a recently developed hybrid torque controller (HTC) based on kinematic state feedback and a novel adaptive model-based torque controller (AMTC) with online learning, proposed herein, against a time-based controller (TBC) during treadmill walking at varying speeds. Compared to TBC, both HTC and AMTC significantly lower users’ normalized oxygen uptake, suggesting enhanced user-exoskeleton coordination. IP analysis reveals that this improvement stems from two distinct co-adaptation strategies, unidentifiable by traditional muscle activity or interaction torque analyses alone. HTC encourages users to yield control to the exoskeleton, decreasing overall muscular effort but increasing interaction torque, as the exoskeleton compensates for user dynamics. Conversely, AMTC promotes user engagement through increased muscular effort and reduces interaction torques, aligning it more closely with rehabilitation and gait training applications. IP phase evolution provides insight into each user’s interaction strategy formation, showcasing IP analysis’s potential in comparing and designing novel controllers to optimize human–robot interaction in wearable robots. [ABSTRACT FROM AUTHOR]

Ocean pollution by microplastics represents a threat to phytoplankton health, yet there is few knowledge on physical interactions between microplastics and microalgal cell surfaces. We studied the contact between environmentally aged microplastics and four microalgal species by atomic force microscopy. After seven days, microalgae showed malformations at specific sites, and these malformations varied with species. Depending on whether the cell had a porous or a smooth surface, microplastics adsorbed to the cell surface via embedding or denting, leading to minor defects or noticeable wrinkles in cell walls. Results also showed that microplastics penetrate into microalgae. Such cellular engulfment of microplastics was less present in typical diatoms because diatoms bear a porous frustule capable of trapping tiny particles. Moreover, we observed a novel type of deformation, bowl-shaped depressions, only in non-porous microalgae. The geometric features of malformations are correlated with the shape and size of microplastics. Our findings reveal for the first time the species-specific deformation in microalgae due to microplastic exposure. [ABSTRACT FROM AUTHOR]

This mini-review presents the fabrication methods for polysaccharide composite materials that employ self-assembled chitin nanofibers (ChNFs) as functional components. Chitin is one of the most abundant polysaccharides in nature. However, it is mostly not utilized because of its poor feasibility and processability. Self-assembled ChNFs are efficiently obtained by a regenerative bottom-up process from chitin ion gels using an ionic liquid, 1-allyl-3-methylimodazolium bromide. This is accomplished by immersing the gels in methanol. The resulting dispersion is subjected to filtration to isolate the regenerated materials, producing ChNF films with a morphology defined by highly entangled nanofibers. The bundles are disintegrated by electrostatic repulsion among the amino groups on the ChNFs in aqueous acetic acid to produce thinner fibers known as scaled-down ChNFs. The self-assembled and scaled-down ChNFs are combined with other chitin components to fabricate chitin-based composite materials. ChNF-based composite materials are fabricated through combination with other polysaccharides. [ABSTRACT FROM AUTHOR]

As a form of multiple-robot interaction, robot-robot interactions effectively provide indirect information, unlike direct interactions between people and robots. Even though numerous studies have affirmed this approach's effectiveness and the development of conversational mechanisms for robot-robot interaction, their physical interaction design has received inadequate attention. This study focuses on the impact of the speed of robots' touching behaviours because people might perceive such relationships between robots differently due to various motion speeds, even with identical motions. We explored this issue by conducting two web-survey experiments and investigated the human perceptions of a robot's touching motion and the perceived relationship between two robots when one robot touches the other at different speeds. Experiment 1 identified two peak speeds at which people perceived a robot's touch as patting (a friendly touch) or slapping (an aggressive touch). Experiment 2 demonstrated similar peak speeds, where people perceived the robots' relationships as either positive or negative in response to patting or slapping behaviours. We maintain that understanding the relationships between motion speeds and perceived friendliness between robots will significantly improve the design of physical interactions between robots. [ABSTRACT FROM AUTHOR]

Heterogeneous multi-agent systems can be deployed to complete a variety of tasks, including some that are impossible using a single generic modality. This paper introduces an approach to solving the problem of cooperative behavior planning in small heterogeneous robot teams where members can both function independently as well as physically interact with each other in ways that give rise to additional functionality. This approach enables, for the first time, the cooperative completion of tasks that are infeasible when using any single modality from those agents comprising the team. [ABSTRACT FROM AUTHOR]

Abstract The heart is a muscular organ that pumps blood throughout the body and is one of the most vital organs in human body. While cardiomyocytes are essential for maintaining the normal function of the heart, a variety of cardiovascular diseases such as coronary artery occlusion, arrhythmia, and myocarditis can lead to cardiomyocyte death, resulting in deterioration of heart function. The adult mammalian heart is incapable of regenerating sufficient cardiomyocytes following cardiac injuries, eventually leading to heart failure and death. Cardiac macrophages are ubiquitously distributed in the healthy heart and accumulated at the site of injury. Macrophages play essential roles in regulating homeostasis and proliferation of cardiomyocyte, promoting electrical conduction, and removing dead cardiomyocytes and debris through direct and indirect cell–cell crosstalk. In this review, we summarize the latest insights into the role of macrophages in maintaining cardiac homeostasis and the macrophage-cardiomyocyte crosstalk in both healthy and injured scenarios. Video Abstract

Heterogeneous multi-agent systems can be deployed to complete a variety of tasks, including some that are impossible using a single generic modality. This paper introduces an approach to solving the problem of cooperative behavior planning in small heterogeneous robot teams where members can both function independently as well as physically interact with each other in ways that give rise to additional functionality. This approach enables, for the first time, the cooperative completion of tasks that are infeasible when using any single modality from those agents comprising the team.

Polytetrafluoroethylene (PTFE) is widely used as a fundamental core material for high-frequency and high-speed signal transmission fields due to its excellent dielectric properties. However, the high coefficient of thermal expansion (CTE) characteristic of PTFE severely limits its practical application. The CTE of PTFE can be reduced by filling with SiO2, which is always accompanied by a rapid deterioration of dielectric properties due to the poor interfacial compatibility between SiO2 and PTFE matrix. In this paper, the challenge of synergistic regulation of dielectric and CTE properties for PTFE-based composites is overcome by constructing an interfacial structure with physical interactions. Micro-mesoporous SiO2 (mSiO2) is prepared and introduced as a filler, compared with smooth surface SiO2 (sSiO2), the presence of micro-mesoporous in mSiO2 allows PTFE molecular chains to be adsorbed on the surface or in the pore channels of mSiO2, which improves the interfacial combination of the mSiO2/PTFE composites through the physical interaction between mSiO2 and PTFE. The results show that mSiO2/PTFE composite exhibits a lower CTE (58 ppm °C−1) while maintaining a lower dielectric constant (εr, 2.29, 30 GHz) with dielectric loss (tan δ, 2.31 × 10−3, 30 GHz) at a filler addition of 30 vol%, as compared with that of the sSiO2/PTFE composites. This work provides a new strategy for fabricating PTFE-based composites with low CTE as well as low εr and tan δ.

Customer experience has been a central component in hospitality management literature since it is pivotal to the success of the service industry. Customer experience facilitates service providers with an effective tool for competitive advantage, differentiation, and generating valuable customer relationships. Based on the customer experience concept and its demonstrated relevance, the study investigates the customer experience dimensions: physical interaction, human interaction, and digital interaction. The moderating role that hotel image has in the relationship between customer experience and brand loyalty is also explored in this study, along with the impact of customer experience and its aspects on brand loyalty. 360 customers/guests were surveyed via both online and offline questionnaires as part of this study using a purposive sampling technique. Using structural equation modelling, the proposed relationships were tested, which suggests that the dimensions of customer experience influence brand loyalty. The main dimension impacting brand loyalty is the human interaction dimension, followed by physical and digital interaction. These results contribute handsomely to experiential marketing literature by adding new insights into the existing body of knowledge and also building a further understanding of the customer experience management concept that assists in managerial decision-making. By emphasising their customers' experiences, this study adds to the knowledge already known about the interaction management approach in the hospitality sector. It makes suggestions for how to consider it when increasing brand loyalty. This study will be immensely useful for marketing practitioners and provide avenues for further research. [ABSTRACT FROM AUTHOR]

The heart is a muscular organ that pumps blood throughout the body and is one of the most vital organs in human body. While cardiomyocytes are essential for maintaining the normal function of the heart, a variety of cardiovascular diseases such as coronary artery occlusion, arrhythmia, and myocarditis can lead to cardiomyocyte death, resulting in deterioration of heart function. The adult mammalian heart is incapable of regenerating sufficient cardiomyocytes following cardiac injuries, eventually leading to heart failure and death. Cardiac macrophages are ubiquitously distributed in the healthy heart and accumulated at the site of injury. Macrophages play essential roles in regulating homeostasis and proliferation of cardiomyocyte, promoting electrical conduction, and removing dead cardiomyocytes and debris through direct and indirect cell–cell crosstalk. In this review, we summarize the latest insights into the role of macrophages in maintaining cardiac homeostasis and the macrophage-cardiomyocyte crosstalk in both healthy and injured scenarios. 5ukxqsQ-VeR5zvcGq9fC9m Video Abstract [ABSTRACT FROM AUTHOR]

Intoxication is one of the most common causes of accidental death globally. Although some antidotes capable of neutralizing the toxicity of certain xenobiotics have become well established, the current reality is that clinicians primarily rely on nonspecific extracorporeal techniques to remove toxins. Nano‐intervention strategies in which nanoantidotes neutralize toxicity in situ via physical interaction, chemical bonding, or biomimetic clearance have begun to show clinical potential. However, most nanoantidotes remain in the proof‐of‐concept stage, and the difficulty of constructing clinical relevance models and the unclear pharmacokinetics of nanoantidotes hinder their translation to clinic. This Concept reviews the detoxification mechanisms of polymer nanoantidotes and predicts the opportunities and challenges associated with their clinical application. [ABSTRACT FROM AUTHOR]

Data physicalisations, or physical visualisations, represent data physically, using variable properties of physical media. As an emerging area, Data physicalisation research needs conceptual foundations to support thinking about and designing new physical representations of data and evaluating them. Yet, it remains unclear at the moment (i) what encoding variables are at the designer's disposal during the creation of physicalisations, (ii) what evaluation criteria could be useful, and (iii) what methods can be used to evaluate physicalisations. This article addresses these three questions through a narrative review and a systematic review. The narrative review draws on the literature from Information Visualisation, HCI and Cartography to provide a holistic view of encoding variables for data. The systematic review looks closely into the evaluation criteria and methods that can be used to evaluate data physicalisations. Both reviews offer a conceptual framework for researchers and designers interested in designing and evaluating data physicalisations. The framework can be used as a common vocabulary to describe physicalisations and to identify design opportunities. We also proposed a seven-stage model for designing and evaluating physical data representations. The model can be used to guide the design of physicalisations and ideate along the stages identified. The evaluation criteria and methods extracted during the work can inform the assessment of existing and future data physicalisation artefacts. [ABSTRACT FROM AUTHOR]

COVID-19 has been affecting all components of our daily routines since December 2019. One of the affected industries from COVID-19 based prevention measurements is football. Most of the leagues stopped temporarily and then re-started without spectators which caused important economic loss in this industry. The aim of this paper was to investigate if the players avoided physical interactions from their opponents after the leagues re-started. The data covers 6 European football leagues with 5689 matches from the seasons in the years of 2018-2021. The examined parameters in the study were foul, challenge, air challenge, tackle, number of possessions, ball possession time and average time of possession. The results showed that the players might have been avoided physical interactions to protect themselves from a possible contagion. Providing more hygiene conditions and also awareness studies are needed to prevent possible negative effects of COVID-19 on the football industry.

In this paper, the problem of a fully actuated hexarotor performing a physical interaction with the environment through a rigidly attached tool is considered. A nonlinear model predictive impedance control (NMPIC) method is proposed to achieve the goal in which the controller is able to simultaneously handle the constraints and maintain the compliant behavior. The design of NMPIC is the combination of a nonlinear model predictive control and impedance control based on the dynamics of the system. A disturbance observer is exploited to estimate the external wrench and then provide compensation for the model which was employed in the controller. Moreover, a weight adaptive strategy is proposed to perform the online tuning of the weighting matrix of the cost function within the optimal problem of NMPIC to improve the performance and stability. The effectiveness and advantages of the proposed method are validated by several simulations in different scenarios compared with the general impedance controller. The results also indicate that the proposed method opens a novel way for interaction force regulation. [ABSTRACT FROM AUTHOR]

Amine-functionalized graphene oxides (AFGOs) are potential candidates for CO 2 capture applications, as the amine functional groups could act as effective sites, promoting CO 2 adsorption strength and selectivity. However, the CO 2 adsorption mechanism on AFGO appears to be ambiguous, particularly with no explicit identification of the chemically bonded species. In this work, density functional theory and microkinetic simulations were carried out to investigate the physical and chemical adsorption mechanisms and behavior between AFGO and CO 2. Our findings indicate that the van der Waals and hydrogen bonding (HB) interactions constitute physical binding modes between the aminated GO and CO 2. The chemical adsorption pathways on AFGO materials have been revealed by the transition state search method, in which the relevant CO 2 adsorption species, including carbamic acid and carbamate, and their formation conditions were theoretically identified on AFGOs. The chemisorption mechanisms have been recognized to be the nucleophilic interaction between GO-supported amines and CO 2 , simultaneously assisted by the cooperative effect of multiple HB interactions. More specifically, the surface hydroxyl groups and water molecules can serve as proton transfer media and offer HB interactions, thus regulating the reaction activity and chemical adsorption species. This theoretical work presents a new insight into CO 2 -AFGO interaction mechanisms, which is valuable for designing aminated GO adsorbents. [Display omitted] • CO 2 capture adsorption on aminated GO surfaces were systematically investigated by DFT approach. • The vdW and HB interactions were found to be the primary physical binding modes. • Chemisorption mechanism was explicitly recognized with both carbamic acid and carbamate as adsorption species. • Surface hydroxyls and water molecules play a critical role in regulating the chemisorption. [ABSTRACT FROM AUTHOR]

Calcium-alumino-silicate-hydrate (C-A-S-H) and calcium hydroxide (CH) are the two primary hydration products that play crucial roles in the mechanical properties of cementitious materials, particularly in the viscoelastic behavior known as creep. This study used hydrated C 3 S and a mixture of the synthesized C-A-S-H and CH to identify the interactions between CH and C-A-S-H. The interactions that dominate the mechanical properties mainly operate from physical and chemical perspectives. CH exhibited a filling effect on C-A-S-H in the physical interactions, demonstrating multi-scale particle packing efficiency. The particle size of CH per unit volume of the mixture was proposed as a critical parameter for the filling effect. Regarding chemical interactions, the synthetic system exhibits interactions primarily through van der Waals forces through compaction. In contrast, the interaction in the hydration system primarily originates from the strong atomic bonding between C-A–S–H and CH at the nanoscale. • C3S hydration and mimic system were designed to investigated the interaction between CH and C-A-S-H. • CH exhibits the role of multi-scale filling in C-A-S-H, which has a significant impact on micromechanical properties. • At 40-60 % CH content, optimal initial packing density of CH and C-A-S-H affects final micromechanical properties. • The cohesive forces in the mimic and hydration systems are van der Waals and strong atomic forces, respectively. [ABSTRACT FROM AUTHOR]

The presence of dyes, pharmaceuticals, and surfactants in the environment results from extensive industrial and societal progress, prompting the need to explore efficient and safe techniques for their removal. Common concentrations in wastewater can range from micrograms to milligrams per liter, which is concerning due to their persistence and potential health impacts. The sustainable approach of using a nonconventional, eco-friendly mineral-organic composite might address this environmental issue. This study focuses on utilizing a composite of bentonite (BEN) and lignite (LIG) as a sorbent for dyes: Rhodamine b (RB), Remazol brilliant blue r (RBBR), pharmaceuticals: ibuprofen (IB), sulfamethoxazole (STX), and surfactant: sodium dodecylbenzenesulfonate (SDBS) from both synthetic solutions and real wastewater. BEN was chosen for its high cation exchange capacity, while LIG was selected for its ability to adsorb both anionic and cationic formsdiverse functional groups. The composite with BEN to LIG ratio of 20:80 (BL 20:80) demonstrated superior sorption capacity. The adsorption performance is quantified, showing removal efficiencies of up to 18.9 mg RBBR/g, 22.8 mg RB/g, 1.77 mg IB/g, 1.47 mg STX/g, and 4.7 mg SDBS/g. Sorption efficiency is influenced by factors such as the initial sorbate concentration, the pH of the solution, the form of sorbates, and the adsorbents textural, physicochemical (point of zero charge pH ZPC), ion-exchange capacity, hydrophobicity/hydrophilicity) properties. Generally, STX and RB is favored by slightly acidic conditions (pH 4–7), while RBBR and IB are favored by alkaline conditions (pH > 7). The complex physical sorption mechanism includes hydrogen bonding, electrostatic and dispersion forces, as well as π-π interactions. Nuclear magnetic resonance spectroscopy (NMR) suggests that a significant portion of the hydrogen bonding interactions contributes to RB adsorption. The sorption results indicate that the specially-designed mineral composite can effectively remove various chemically distinct organic compounds from real wastewater. Subsequent investigations will focus on the granulated BL 20:80 composite and its applicability in dynamic column systems. This aligns with the ongoing development of purification technologies. [Display omitted] • The mineral-based sorbents effectively uptake the dyes, pharmaceuticals, and surfactant. • Physical sorption processes are responsible for the tested organic compounds' sorption. • Mineral composite analysis enable to reveal of sorption properties of this material. [ABSTRACT FROM AUTHOR]

In the health care system and Internet of Things (IoT) platform, medical care robotics is becoming one of the quickest expanding areas of robot technology. The integration of robotics and human knowledge identifies human muscle rigidity from the healthcare data obtained from the wearable sensor. In an IoT platform, Electromyography is a method used for evaluating and tracking the electrical activity of muscles. The transferring of human muscle rigidity to a robot facilitates the robot to obtain resistive management initiatives in a useful and effective way while carrying out physical interaction activities in unstructured surroundings. The major challenges to overcome the unpredictability during physical interaction allow a robot to realize the individual behaviour with adaptability and versatility of muscles. Therefore, in this article, Human‐Robot Approximation Characteristics Framework (HRACF) has been proposed for developing physiological communication between humans and robots. HRACF permits robots to understand differential resistive abilities of muscles from human presentations. The pulses collected from Electromyography are used to retrieve human arm muscle rigidity during activity presentation. The characteristics of motion and rigidity are concurrently modelled using an estimation and approximation model with a logistic regression obtained by IoT devices. The analysed human arm muscle rigidity is then connected to the robot impedance regulator. HR model uses an optimized resistive approximator to measure the creative variables of the robot and continue driving to monitor the quoted pathways at the time of interaction. The relationship between motion data and rigidity data is systematically coded in the HR model. HRACF makes it possible to detect uncertainties through space and time that facilitates the robot to meet rigidity specification to 98[Nm/Rad] and error rate to 0.15% during physical interaction. [ABSTRACT FROM AUTHOR]

In the latest years, there has been a rise in social robotics’ interest as a support tool in various scopes. For instance, social robots have been used in Autism treatments, improving social skills, social interaction, and children’s daily activities performance. Although several studies elucidate the benefits of social robots in the ASD community, few focus on evaluating and promoting physical interaction. Thus, this study presents the development and assessment of a social robotic platform based on soft actuation to promote physical interaction. A total of 35 children diagnosed with autism were involved in this study. The primary outcomes show that physical interaction does not significantly influence the patient’s performance in the activity. However, the clinicians remark that encouragement and motivation increase when the children were allowed to interact with the robot physically. Also, 52.9% of the control group children elucidate the intention of physically interact with the robot, suggesting this behavior is an essential way of communication. [ABSTRACT FROM AUTHOR]

In this paper, the problem of a fully actuated hexarotor performing a physical interaction with the environment through a rigidly attached tool is considered. A nonlinear model predictive impedance control (NMPIC) method is proposed to achieve the goal in which the controller is able to simultaneously handle the constraints and maintain the compliant behavior. The design of NMPIC is the combination of a nonlinear model predictive control and impedance control based on the dynamics of the system. A disturbance observer is exploited to estimate the external wrench and then provide compensation for the model which was employed in the controller. Moreover, a weight adaptive strategy is proposed to perform the online tuning of the weighting matrix of the cost function within the optimal problem of NMPIC to improve the performance and stability. The effectiveness and advantages of the proposed method are validated by several simulations in different scenarios compared with the general impedance controller. The results also indicate that the proposed method opens a novel way for interaction force regulation.

The presence of unknown physical interaction between the patients’ body and surgical tool in laparoscopic surgery requires a secure end-effector positioning while assuring a reliable constraint motion. In this work, a task-space control approach based on fuzzy approximation is proposed for a teleoperated surgery scenario utilizing a serial redundant robot manipulator (7 degrees of freedom), the motions of which are constrained with respect to a point known as remote center of motion (RCM). The dynamical uncertainties due to the physical interaction are considered and estimated to maintain operational accuracy by introducing the decoupled adaptive fuzzy approximation technique. Experiments verify the presented approach’s effectiveness. Results indicate that with the proposed control method, the accuracy of the surgical operation is improved while the safety can be ensured for teleoperated surgery with RCM constraint. [ABSTRACT FROM AUTHOR]

Physical interaction in peer learning has been proven to improve students' learning processes, which is pertinent in facilitating a fulfilling learning experience in learning theory. However, observation and interviews are often used to investigate peer group learning dynamics from a qualitative perspective. Hence, more data-driven analysis needs to be performed to investigate the physical interaction in peer learning. This paper complements existing works by proposing a framework for exploring students' physical interaction in peer learning based on the graph analytics modeling approach focusing on both centrality and community detection, as well as visualization of the graph model for more than 50 students taking part in group discussions. The experiment was conducted during a mathematics tutorial class. The physical interactions among students were captured through an online Google form and represented in a graph model. Once the model and graph visualization were developed, findings from centrality analysis and community detection were conducted to identify peer leaders who can facilitate and teach their peers. Based on the results, it was found that five groups were formed during the physical interaction throughout the peer learning process, with at least one student showing the potential to become a peer leader in each group. This paper also highlights the potential of the graph analytics approach to explore peer learning group dynamics and interaction patterns among students to maximize their teaching and learning experience. [ABSTRACT FROM AUTHOR]

Abstract We report response of photoluminescence (PL) from GaN nanowires without protection in solutions. The distinct response is not only toward pH but toward ionic concentration under same pH. The nanowires appear to be highly stable under aqueous solution with high ionic concentration and low pH value down to 1. We show that the PL has a reversible interaction with various types of acidic and salt solutions. The quantum states of nanowires are exposed to the external environment and have a direct physical interaction which depends on the anions of the acids. As the ionic concentration increases, the PL intensity goes up or down depending on the chemical species. The response results from a competition of change in surface band bending and charge transfer to redox level in solution. That of GaN films is reported for comparison as the effect of surface band bending can be neglected so that there are only slight variations in PL intensity for GaN films. Additionally, such physical interaction does not impact on the PL peaks in acids and salts, whereas there is a red shift on PL when the nanowires are in basic solution, say NH4OH, due to chemical etching occurred on the nanowires.

Proteins are the building blocks for almost all the functions in cells. Understanding the molecular evolution of proteins and the forces that shape protein evolution is essential in understanding the basis of function and evolution. Previous studies have shown that adaptation frequently occurs at the protein surface, such as in genes involved in host–pathogen interactions. However, it remains unclear whether adaptive sites are distributed randomly or at regions associated with particular structural or functional characteristics across the genome, since many proteins lack structural or functional annotations. Here, we seek to tackle this question by combining large-scale bioinformatic prediction, structural analysis, phylogenetic inference, and population genomic analysis of Drosophila protein-coding genes. We found that protein sequence adaptation is more relevant to function-related rather than structure-related properties. Interestingly, intermolecular interactions contribute significantly to protein adaptation. We further showed that intermolecular interactions, such as physical interactions, may play a role in the coadaptation of fast-adaptive proteins. We found that strongly differentiated amino acids across geographic regions in protein-coding genes are mostly adaptive, which may contribute to the long-term adaptive evolution. This strongly indicates that a number of adaptive sites tend to be repeatedly mutated and selected throughout evolution in the past, present, and maybe future. Our results highlight the important roles of intermolecular interactions and coadaptation in the adaptive evolution of proteins both at the species and population levels. [ABSTRACT FROM AUTHOR]

Abstract Background Predicting physical interaction between proteins is one of the greatest challenges in computational biology. There are considerable various protein interactions and a huge number of protein sequences and synthetic peptides with unknown interacting counterparts. Most of co-evolutionary methods discover a combination of physical interplays and functional associations. However, there are only a handful of approaches which specifically infer physical interactions. Hybrid co-evolutionary methods exploit inter-protein residue coevolution to unravel specific physical interacting proteins. In this study, we introduce a hybrid co-evolutionary-based approach to predict physical interplays between pairs of protein families, starting from protein sequences only. Results In the present analysis, pairs of multiple sequence alignments are constructed for each dimer and the covariation between residues in those pairs are calculated by CCMpred (Contacts from Correlated Mutations predicted) and three mutual information based approaches for ten accessible surface area threshold groups. Then, whole residue couplings between proteins of each dimer are unified into a single Frobenius norm value. Norms of residue contact matrices of all dimers in different accessible surface area thresholds are fed into support vector machine as single or multiple feature models. The results of training the classifiers by single features show no apparent different accuracies in distinct methods for different accessible surface area thresholds. Nevertheless, mutual information product and context likelihood of relatedness procedures may roughly have an overall higher and lower performances than other two methods for different accessible surface area cut-offs, respectively. The results also demonstrate that training support vector machine with multiple norm features for several accessible surface area thresholds leads to a considerable improvement of prediction performance. In this context, CCMpred roughly achieves an overall better performance than mutual information based approaches. The best accuracy, sensitivity, specificity, precision and negative predictive value for that method are 0.98, 1, 0.962, 0.96, and 0.962, respectively. Conclusions In this paper, by feeding norm values of protein dimers into support vector machines in different accessible surface area thresholds, we demonstrate that even small number of proteins in pairs of multiple alignments could allow one to accurately discriminate between positive and negative dimers.

Tissue engineering is a triad involves three components of different types of cells, growth factor, small biomolecules and scaffold for the purpose of tissue restore, repair and regeneration. In tissue engineering, attachment, growth, proliferation and differentiation of cells require careful control of external factors such as the physical properties of the scaffold as extra cellular matrix (ECM), type and amount of biologically active molecules like small biomolecules, peptides and proteins. Therefore, the interaction of the synthetic and natural scaffolds with the cells must reflect the cellular microenvironment in the body. In this study, we describe a variety of in situ forming injectable hydrogels synthesis with the medical application and tissue regeneration that are crosslinked by chemical bonding or physical interactions. These types of hydrogels have attracted a lot of attention in tissue engineering applications because they can easily transfer the cells or delivered the biomolecules to the damaged tissue. Lack of severe toxicity, minimal injury and pain during surgery could be the other advantages of the injectable hydrogels. A wide variety of chemical methods have been used to crosslink the injectable hydrogels such as click chemistry, Michael addition, Schiff-base, enzymatic reaction and, etc. Some hydrogels can also be cross-linked using physical interactions such as ionic interactions, hydrogen bonding, supramolecular interaction, etc., without external factors in the physiological conditions of the body. In this study, in addition to various methods of synthesis, the practical aspects of hydrogels in regenerative medicine and their achievements in tissue engineering are discussed.

Objective: The last decades have seen a surge of robots for physical training and work assistance. How to best control these interfaces is unknown, although arguably the interaction should be similar to human movement assistance. Methods: We compare the behaviour and assessment of subjects tracking a moving target with assistance from (i) trajectory guidance (as typically used in robots for physical training), (ii) a human partner, and (iii) the reactive robot partner of Takagi et al. Results: Trajectory guidance was recognised as robotic, while the robot partner was felt as human-like. However, trajectory guidance was preferred to assistance from a human partner, which was recognised as less predictable. The robot partner also was felt to be more predictable and helpful than a human partner, and was preferred. Conclusions: While subjects like to rely on predictable interaction, such as in trajectory guidance, the control reactivity of the robot partner is essential for perceiving an interaction as human-like.

It is well-known that the co-inoculation of Saccharomyces cerevisiae and non- Saccharomyces strains can modulate and improve the aromatic quality of wine through their multi-level interactions. However, the individual contribution of metabolic interaction (MI) and physical interaction (PI) on wine volatiles remains poorly understood. In this work, we utilized a double-compartment bioreactor to examine the aromatic effect of MI and PI by comparing the volatiles production in Torulaspora delbrueckii and Saccharomyces cerevisiae single fermentations to their mixed fermentations with or without physical separation. Results showed that the PI between T. delbrueckii and S. cerevisiae increased the production of most aroma compounds, especially for acetate esters and volatile fatty acids. In comparison, the MI only promoted a few volatile compounds, including ethyl decanoate, isoamyl acetate, and isobutanol. Noticeably, the MI significantly decreased the levels of ethyl dodecanoate, 2-phenylethyl alcohol, and decanoic acid, which exhibited opposite profiles in PI. Our results indicated that the PI was mainly responsible for the improved volatiles in T. delbrueckii/S. cerevisiae mixed fermentation, while the MI can be targeted to modulate the specific aroma compounds. A thorough understanding of the PI and MI aromatic effect will empower winemakers to accurately and directionally control the volatile profile of the wine, promoting the application of multi-starters to produce diverse styles of wines. • The individual contribution of MI and PI on volatiles was revealed by a double-compartment bioreactor. • The PI elevated most volatile compounds, responsible for the aroma enhancement in the mixed culture. • The MI only promoted a few volatile compounds, such as isoamyl acetate, ethyl decanoate, and isobutanol. • The MI can reduce the contents of ethyl acetate, 2-phenylethyl alcohol, and decanoic acid. [ABSTRACT FROM AUTHOR]

Glimepiride is often combined with metformin HCl as an oral antidiabetic in type II diabetes mellitus, which provides a complementary and synergistic effect with multiple targets for insulin secretion. Glimepiride includes class II of BCS, which solubility practically insoluble in water but high permeability, which will impact the drug's small bioavailability. In contrast, metformin HCl includes class III of BCS, which has a high solubility in water, but low permeability is absorbed approximately 50-60% in the digestive tract given orally. The co-crystallization method can be used to improve the glimepiride solubility properties and the permeability properties of metformin HCl by interrupting glimepiride with metformin HCl physically. This study aims to identify the physical interactions between glimepiride and metformin HCL using a thermal analysis of Differential Scanning Calorimetry (DSC) and then confirmed by a computational approach. Identifying the physical interactions between glimepiride and metformin HCL was carried out by plotting the melting points generated from the endothermic peaks of the DSC thermogram at various compositions versus the mole ratios of the two were further confirmed by the computational approach using PatchDock. The results of the phase diagram analysis of the binary system between glimepiride and metformin HCl show a congruent pattern, which indicates the formation of co-crystal or molecular compounds at a 1 : 1 mole ratio at 228°C. Computational approach results showed that the interaction between glimepiride and metformin HCl did not form new compounds but heterosinton formation that was stable in molecular dynamics simulations.

Robots still struggle to dynamically traverse complex 3D terrain with many large obstacles, an ability required for many critical applications. Body–obstacle interaction is often inevitable and induces perturbation and uncertainty in motion that challenges closed-form dynamic modeling. Here, inspired by recent discovery of a terradynamic streamlined shape, we studied how two body shapes interacting with obstacles affect turning and pitching motions of an open-loop multi-legged robot and cockroaches during dynamic locomotion. With a common cuboidal body, the robot was attracted towards obstacles, resulting in pitching up and flipping-over. By contrast, with an elliptical body, the robot was repelled by obstacles and readily traversed. The animal displayed qualitatively similar turning and pitching motions induced by these two body shapes. However, unlike the cuboidal robot, the cuboidal animal was capable of escaping obstacle attraction and subsequent high pitching and flipping over, which inspired us to develop an empirical pitch-and-turn strategy for cuboidal robots. Considering the similarity of our self-propelled body–obstacle interaction with part–feeder interaction in robotic part manipulation, we developed a quasi-static potential energy landscape model to explain the dependence of dynamic locomotion on body shape. Our experimental and modeling results also demonstrated that obstacle attraction or repulsion is an inherent property of locomotor body shape and insensitive to obstacle geometry and size. Our study expands the concept and usefulness of terradynamic shapes for passive control of robot locomotion to traverse large obstacles using physical interaction. Our study is also a step in establishing an energy landscape approach to locomotor transitions. [ABSTRACT FROM AUTHOR]

When considering the accuracy of tracking control, physical interaction such as structural uncertainties and external dynamics is the main challenge in actual engineering scenarios, especially for the complex robot system. In this article, a neural network‐based sliding mode tracking control scheme (SMCR) is presented for the developed four wheel‐legged robot (BIT‐NAZA) under the uncertain interaction. First, a non‐singular fast terminal function based on the kinematic model is proposed for path tracking, which improves the motion quality during the approach movement and the sliding mode movement. At the same time, it can reduce the influence of uncertain disturbances on the premise of ensuring the path tracking control accuracy via neural networks. Finally, some demonstrations using the autonomous platform of the BIT‐NAZA robot are employed to evaluate the robustness and effectiveness of the hybrid algorithm. [ABSTRACT FROM AUTHOR]

Sex change in teleost fishes is commonly regulated by social factors. In species that exhibit protogynous sex change, such as the orange‐spotted grouper Epinephelus coioides, when the dominant males are removed from the social group, the most dominant female initiates sex change. The aim of this study was to determine the regulatory mechanisms of socially controlled sex change in E. coioides. We investigated the seasonal variation in social behaviours and sex change throughout the reproductive cycle of E. coioides, and defined the behaviour pattern of this fish during the establishment of a dominance hierarchy. The social behaviours and sex change in this fish were affected by season, and only occurred during the prebreeding season and breeding season. Therefore, a series of sensory isolation experiments was conducted during the breeding season to determine the role of physical, visual and olfactory cues in mediating socially controlled sex change. The results demonstrated that physical interactions between individuals in the social groups were crucial for the initiation and completion of sex change, whereas visual and olfactory cues alone were insufficient in stimulating sex change in dominant females. In addition, we propose that the steroid hormones 11‐ketotestosterone and cortisol are involved in regulating the initiation of socially controlled sex change. [ABSTRACT FROM AUTHOR]