Tailoring Light–Matter Interactions in Overcoupled Resonator for Biomolecule Recognition and Detection

Plasmonic nanoantennas provide unique opportunities for precise control of light–matter coupling in surface-enhanced infrared absorption(SEIRA)spectroscopy,but most of the resonant systems realized so far suffer from the obstacles of low sensitivity,narrow bandwidth,and asymmetric Fano resonance perturbations.Here,we demonstrated an overcoupled resonator with a high plasmon-molecule coupling coefficient(μ)(OC-Hμresonator)by precisely controlling the radiation loss channel,the resonator-oscillator coupling channel,and the frequency detuning channel.We observed a strong dependence of the sensing performance on the coupling state,and demonstrated that OC-Hμresonator has excellent sensing properties of ultra-sensitive(7.25%nm^(−1)),ultra-broadband(3–10μm),and immune asymmetric Fano lineshapes.These characteristics represent a breakthrough in SEIRA technology and lay the foundation for specific recognition of biomolecules,trace detection,and protein secondary structure analysis using a single array(array size is 100×100μm^(2)).In addition,with the assistance of machine learning,mixture classification,concentration prediction and spectral reconstruction were achieved with the highest accuracy of 100%.Finally,we demonstrated the potential of OC-Hμresonator for SARS-CoV-2 detection.These findings will promote the wider application of SEIRA technology,while providing new ideas for other enhanced spectroscopy technologies,quantum photonics and studying light–matter interactions.

Catalyst–Support Interaction in Polyaniline‑Supported Ni_(3)Fe Oxide to Boost Oxygen Evolution Activities for Rechargeable Zn‑Air Batteries

Catalyst–support interaction plays a crucial role in improving the catalytic activity of oxygen evolution reaction(OER).Here we modulate the catalyst–support interaction in polyaniline-supported Ni_(3)Fe oxide(Ni_(3)Fe oxide/PANI)with a robust hetero-interface,which significantly improves oxygen evolution activities with an overpotential of 270 mV at 10 mA cm^(-2)and specific activity of 2.08 mA cm_(ECSA)^(-2)at overpotential of 300 mV,3.84-fold that of Ni_(3)Fe oxide.It is revealed that the catalyst–support interaction between Ni_(3)Fe oxide and PANI support enhances the Ni–O covalency via the interfacial Ni–N bond,thus promoting the charge and mass transfer on Ni_(3)Fe oxide.Considering the excellent activity and stability,rechargeable Zn-air batteries with optimum Ni_(3)Fe oxide/PANI are assembled,delivering a low charge voltage of 1.95 V to cycle for 400 h at 10 mA cm^(-2).The regulation of the effect of catalyst–support interaction on catalytic activity provides new possibilities for the future design of highly efficient OER catalysts.

T cell interactions with microglia in immune-inflammatory processes of ischemic stroke

The primary mechanism of secondary injury after cerebral ischemia may be the brain inflammation that emerges after an ischemic stroke,which promotes neuronal death and inhibits nerve tissue regeneration.As the first immune cells to be activated after an ischemic stroke,microglia play an important immunomodulatory role in the progression of the condition.After an ischemic stroke,peripheral blood immune cells(mainly T cells)are recruited to the central nervous system by chemokines secreted by immune cells in the brain,where they interact with central nervous system cells(mainly microglia)to trigger a secondary neuroimmune response.This review summarizes the interactions between T cells and microglia in the immune-inflammatory processes of ischemic stroke.We found that,during ischemic stroke,T cells and microglia demonstrate a more pronounced synergistic effect.Th1,Th17,and M1 microglia can co-secrete proinflammatory factors,such as interferon-γ,tumor necrosis factor-α,and interleukin-1β,to promote neuroinflammation and exacerbate brain injury.Th2,Treg,and M2 microglia jointly secrete anti-inflammatory factors,such as interleukin-4,interleukin-10,and transforming growth factor-β,to inhibit the progression of neuroinflammation,as well as growth factors such as brain-derived neurotrophic factor to promote nerve regeneration and repair brain injury.Immune interactions between microglia and T cells influence the direction of the subsequent neuroinflammation,which in turn determines the prognosis of ischemic stroke patients.Clinical trials have been conducted on the ways to modulate the interactions between T cells and microglia toward anti-inflammatory communication using the immunosuppressant fingolimod or overdosing with Treg cells to promote neural tissue repair and reduce the damage caused by ischemic stroke.However,such studies have been relatively infrequent,and clinical experience is still insufficient.In summary,in ischemic stroke,T cell subsets and activated microglia act synergistically to regulate inflammatory progression,mainly by secreting inflammatory factors.In the future,a key research direction for ischemic stroke treatment could be rooted in the enhancement of anti-inflammatory factor secretion by promoting the generation of Th2 and Treg cells,along with the activation of M2-type microglia.These approaches may alleviate neuroinflammation and facilitate the repair of neural tissues.

Risk identification and safety assessment of human-computer interaction in integrated avionics based on STAMP

To solve the problem of risk identification and quantitative assessment for human-computer interaction(HCI)in complex avionics systems,an HCI safety analysis framework based on system-theoretical process analysis(STPA)and cognitive reliability and error analysis method(CREAM)is proposed.STPACREAM can identify unsafe control actions and find the causal path during the interaction of avionics systems and pilot with the help of formal verification tools automatically.The common performance conditions(CPC)of avionics systems in the aviation environment is established and a quantitative analysis of human failure is carried out.Taking the head-up display(HUD)system interaction process as an example,a case analysis is carried out,the layered safety control structure and formal model of the HUD interaction process are established.For the interactive behavior“Pilots approaching with HUD”,four unsafe control actions and35 causal scenarios are identified and the impact of common performance conditions at different levels on the pilot decision model are analyzed.The results show that HUD's HCI level gradually improves as the scores of CPC increase,and the quality of crew member cooperation and time sufficiency of the task is the key to its HCI.Through case analysis,it is shown that STPACREAM can quantitatively assess the hazards in HCI and identify the key factors that impact safety.

Identification and distribution of 13003 landslides in the northwest margin of Qinghai-Tibet Plateau based on human-computer interaction remote sensing interpretation

The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Tibet Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It means the landslides mobility in the region is relatively low,and the authors speculate that landslides in this region more possibly triggered by earthquakes or located in meizoseismal area.

Human-artificial intelligence interaction in gastrointestinal endoscopy

The number and variety of applications of artificial intelligence(AI)in gastr-ointestinal(GI)endoscopy is growing rapidly.New technologies based on machine learning(ML)and convolutional neural networks(CNNs)are at various stages of development and deployment to assist patients and endoscopists in preparing for endoscopic procedures,in detection,diagnosis and classification of pathology during endoscopy and in confirmation of key performance indicators.Platforms based on ML and CNNs require regulatory approval as medical devices.Interactions between humans and the technologies we use are complex and are influenced by design,behavioural and psychological elements.Due to the substantial differences between AI and prior technologies,important differences may be expected in how we interact with advice from AI technologies.Human-AI interaction(HAII)may be optimised by developing AI algorithms to minimise false positives and designing platform interfaces to maximise usability.Human factors influencing HAII may include automation bias,alarm fatigue,algorithm aversion,learning effect and deskilling.Each of these areas merits further study in the specific setting of AI applications in GI endoscopy and professional societies should engage to ensure that sufficient emphasis is placed on human-centred design in development of new AI technologies.

Verification of the Interaction between SET and eEF1A1 in Human Liver Cells by Co-immunoprecipitation

[Objective] The aim was to investigate the possible interaction between SET and eEF1A1 in human liver cells. [Method] Firstly the total proteins of human L-02 liver cells were extracted under non-denaturing conditions; then,mouse anti-human SET and rabbit anti-human eEF1A1 antibodies were used to perform the co-immunoprecipitation respectively; subsequently,the immunoprecipitations was correspondingly detected with rabbit anti-human eEF1A1 and mouse anti-human SET antibodies by Western Blot. [Result] EEF1A1 was detected in protein complex from the immunoprecipitations by using anti-SET antibody,and SET also was detected in immunoprecipitations by using anti-eEF1A1 antibody. [Conclusion] The interaction between SET and eEF1A1 in human liver cells was confirmed.

Biological Interaction and Imaging of Ultrasmall Gold Nanoparticles

Ultrasmall gold nanoparticles(AuNPs)typically includes atomically precise gold nanoclusters(AuNCs)and AuNPs with a core size below 3 nm.Serving as a bridge between small molecules and traditional inorganic nanoparticles,the ultrasmall AuNPs show the unique advantages of both small molecules(e.g.,rapid distribution,renal clearance,low non-specific organ accumulation)and nanoparticles(e.g.,long blood circulation and enhanced permeability and retention effect).The emergence of ultrasmall AuNPs creates significant opportunities to address many challenges in the health field including disease diagnosis,monitoring and treatment.Since the nano–bio interaction dictates the overall biological applications of the ultrasmall AuNPs,this review elucidates the recent advances in the biological interactions and imaging of ultrasmall AuNPs.We begin with the introduction of the factors that influence the cellular interactions of ultrasmall AuNPs.We then discuss the organ interactions,especially focus on the interactions of the liver and kidneys.We further present the recent advances in the tumor interactions of ultrasmall AuNPs.In addition,the imaging performance of the ultrasmall AuNPs is summarized and discussed.Finally,we summarize this review and provide some perspective on the future research direction of the ultrasmall AuNPs,aiming to accelerate their clinical translation.

Human Interaction Dynamics for Its Use in Mobile Robotics:Impedance Control for Leader-follower Formation

A complete characterization of the behavior in human-robot interactions(HRI) includes both: the behavioral dynamics and the control laws that characterize how the behavior is regulated with the perception data. In this way, this work proposes a leader-follower coordinate control based on an impedance control that allows to establish a dynamic relation between social forces and motion error. For this, a scheme is presented to identify the impedance based on fictitious social forces, which are described by distance-based potential fields.As part of the validation procedure, we present an experimental comparison to select the better of two different fictitious force structures. The criteria are determined by two qualities: least impedance errors during the validation procedure and least parameter variance during the recursive estimation procedure.Finally, with the best fictitious force and its identified impedance,an impedance control is designed for a mobile robot Pioneer 3AT,which is programmed to follow a human in a structured scenario.According to results, and under the hypothesis that moving like humans will be acceptable by humans, it is believed that the proposed control improves the social acceptance of the robot for this kind of interaction.

Machine learning with active pharmaceutical ingredient/polymer interaction mechanism:Prediction for complex phase behaviors of pharmaceuticals and formulations

The high throughput prediction of the thermodynamic phase behavior of active pharmaceutical ingredients(APIs)with pharmaceutically relevant excipients remains a major scientific challenge in the screening of pharmaceutical formulations.In this work,a developed machine-learning model efficiently predicts the solubility of APIs in polymers by learning the phase equilibrium principle and using a few molecular descriptors.Under the few-shot learning framework,thermodynamic theory(perturbed-chain statistical associating fluid theory)was used for data augmentation,and computational chemistry was applied for molecular descriptors'screening.The results showed that the developed machine-learning model can predict the API-polymer phase diagram accurately,broaden the solubility data of APIs in polymers,and reproduce the relationship between API solubility and the interaction mechanisms between API and polymer successfully,which provided efficient guidance for the development of pharmaceutical formulations.

Fabrication of an electrochemical sensor for determination of doxorubicin in human plasma and its interaction with DNA

In this work, an electrochemical sensor was fabricated for determination of an anthracycline, doxorubicin(DOX) as a chemotherapy drug in plasma based on multi-walled carbon nanotubes modified platinum electrode(Pt/MWCNTs). DOX was effectively accumulated on the surface of modified electrode and generated a pair of redox peaks at around 0.522 and 0.647 V(vs. Ag/Ag Cl) in Britton Robinson(B-R) buffer(p H 4.0, 0.1 M). The electrochemical parameters including p H, type of buffer, accumulation time, amount of modifier and scan rate were optimized. Under the optimized conditions, there was a linear correlation between cathodic peak current and concentration of DOX in the range of 0.05–4.0 μg/m L with the detection limit of 0.002 μg/m L. The number of electron transfers(n) and electron transfer-coefficient(α) were estimated as 2.0 and 0.25, respectively. The constructed sensor displayed excellent precision, sensitivity, repeatability and selectivity in the determination of DOX in plasma. Moreover, cyclic voltammetry studies of DOX in the presence of DNA showed an intercalation mechanism with binding constant(K_b) of 1.12×10~5L/mol.

Strong metal–support interaction boosts the electrocatalytic hydrogen evolution capability of Ru nanoparticles supported on titanium nitride

Ruthenium(Ru)has been regarded as one of the most promising alternatives to substitute Pt for catalyzing alkaline hydrogen evolution reaction(HER),owing to its inherent high activity and being the cheapest platinum-group metal.Herein,based on the idea of strong metal–support interaction(SMSI)regulation,Ru/TiN catalysts with different degrees of TiN overlayer over Ru nanoparticles were fabricated,which were applied to the alkaline electrolytic water.Characterizations reveal that the TiN overlayer would gradually encapsulate the Ru nanoparticles and induce more electron transfer from Ru nanoparticles to TiN support by the Ru–N–Ti bond as the SMSI degree increased.Further study shows that the exposed Ru–TiN interfaces greatly promote the H_(2) desorption capacity.Thus,the Ru/TiN-300 with a moderate SMSI degree exhibits excellent HER performance,with an overpotential of 38 mV at 10 mA cm^(−2).Also,due to the encapsulation role of TiN overlayer on Ru nanoparticles,it displays super long-term stability with a very slight potential change after 24 h.This study provides a deep insight into the influence of the SMSI effect between Ru and TiN on HER and offers a novel approach for preparing efficient and stable HER electrocatalysts through SMSI engineering.

Review of human-animal interactions and their impact on animal productivity and welfare

Humans and animals are in regular and at times close contact in modern intensive farming systems.The quality of human-animal interactions can have a profound impact on the productivity and welfare of farm animals.Interactions by humans may be neutral,positive or negative in nature.Regular pleasant contact with humans may result in desirable alterations in the physiology,behaviour,health and productivity of farm animals.On the contrary,animals that were subjected to aversive human contact were highly fearful of humans and their growth and reproductive performance could be compromised.Farm animals are particularly sensitive to human stimulation that occurs early in life,while many systems of the animals are still developing.This may have long-lasting impact and could possibly modify their genetic potential.The question as to how human contact can have a positive impact on responses to stressors,and productivity is not well understood.Recent work in our laboratory suggested that pleasant human contact may alter ability to tolerate various stressors through enhanced heat shock protein（hsp） 70 expression.The induction of hsp is often associated with increased tolerance to environmental stressors and disease resistance in animals.The attitude and consequent behaviour of stockpeople affect the animals＇ fear of human which eventually influence animals＇ productivity and welfare.Other than attitude and behaviour,technical skills,knowledge,job motivation,commitment and job satisfaction are prerequisites for high job performance.

Enhanced Ion-Selective Diffusion Achieved by Supramolecular Interaction for High Thermovoltage and Thermal Stability

Thermoelectric(TE)generators capable of converting thermal energy into applicable electricity have gained great popularity among emerging energy conversion technologies.Biopolymer-based ionic thermoelectric(i-TE)materials are promising candidates for energy conversion systems because of their wide sources,innocuity,and low manufacturing cost.However,common physically crosslinked biopolymer gels induced by single hydrogen bonding or hydrophobic interaction suffer from low differential thermal voltage and poor thermodynamic stability.Here,we develop a novel i-TE gel with supramolecular structures through multiple noncovalent interactions between ionic liquids(ILs)and gelatin molecular chains.The thermopower and thermoelectric power factor of the ionic gels are as high as 2.83 mV K-1 and 18.33μW m^(-1)K^(-2),respectively.The quasi-solid-state gelatin-[EMIM]DCA i-TE cells achieve ultrahigh 2 h output energy density(E_(2h)=9.9 mJ m^(-2))under an optimal temperature range.Meanwhile,the remarkable stability of the supramolecular structure provides the i-TE hydrogels with a thermal stability of up to 80℃.It breaks the limitation that biopolymer-based i-TE gels can only be applied in the low temperature range and enables biopolymer-based i-TE materials to pursue better performance in a higher temperature range.

Electrostatic Interaction-directed Construction of Hierarchical Nanostructured Carbon Composite with Dual Electrical Conductive Networks for Zinc-ion Hybrid Capacitors with Ultrastability

Metal-organic framework(MOF)-derived carbon composites have been considered as the promising materials for energy storage.However,the construction of MOF-based composites with highly controllable mode via the liquid-liquid synthesis method has a great challenge because of the simultaneous heterogeneous nucleation on substrates and the self-nucleation of individual MOF nanocrystals in the liquid phase.Herein,we report a bidirectional electrostatic generated self-assembly strategy to achieve the precisely controlled coatings of single-layer nanoscale MOFs on a range of substrates,including carbon nanotubes(CNTs),graphene oxide(GO),MXene,layered double hydroxides(LDHs),MOFs,and SiO_(2).The obtained MOF-based nanostructured carbon composite exhibits the hierarchical porosity(V_(meso)/V_(micro)∶2.4),ultrahigh N content of 12.4 at.%and"dual electrical conductive networks."The assembled aqueous zinc-ion hybrid capacitor(ZIC)with the prepared nanocarbon composite as a cathode shows a high specific capacitance of 236 F g^(-1)at 0.5 A g^(-1),great rate performance of 98 F g^(-1)at 100 A g^(-1),and especially,an ultralong cycling stability up to 230000 cycles with the capacitance retention of 90.1%.This work develops a repeatable and general method for the controlled construction of MOF coatings on various functional substrates and further fabricates carbon composites for ZICs with ultrastability.

BINDING AND INTERACTION OF TRANSCRIPTIONAL REGULATOR HUMAN DAXX WITH ADENOVIRUS12 E1B 55 KILODALTON ONCOPROTEIN

Objective: To study the disruption of co- localization of human Daxx(hDaxx) with promyelocytic leukemia protein(PML) at the PML oncogenic domains (PODs) by the interaction of hDaxx with adenovirus(Ad) 12 E1B 55 Kilodalton Oncoprotein (Ad12 E1B 55kD). Methods: The direct binding reaction of hDaxx and Ad12 E1B 55kD was analyzed by coimmunoprecipitation and Western blotting in vivo or in vitro. The interaction of hDaxx with Ad12 E1B 55kD was studied using yeast two-hybrid assay. Results: hDaxx bounded directly to Ad12 E1B 55kD in vivo and in vitro. hDaxx interacted with full length Ad12 E1B 55kD. Conclusion: Transcriptional regulator hDaxx directly binds to and interacts with Ad12 E1B 55kD.

Role of flavonoids in plant interactions with the environment and against human pathogens-A review

Flavonoids are widely-distributed polyphenolic secondary metabolites with diverse biological activities in plants and benefit human health as protective dietary agents.They participate in plants' responses to harsh environmental conditions and effectively regulate the cell differentiation and growth.In plants,the majority of their functions are attributed to their strong antioxidative properties.Similarly,dietary flavonoids protect the human body against free radicals which are associated with the development of cancer and atherosclerosis.Plants rich in polyphenols have been used to cure various diseases because of their antibacterial,antiviral,antifungal and anticancer properties.This review summarizes the up-to-date research trends and development on flavonoids and its derivatives,working mechanisms and potential functions and applications particularly in relation to plant protection and human health.Towards the end,notable concluding remarks with a close-up look at the future research directions have also been presented briefly.

A Facial Expression Emotion Recognition Based Human-robot Interaction System

A facial expression emotion recognition based human-robot interaction(FEER-HRI) system is proposed, for which a four-layer system framework is designed. The FEERHRI system enables the robots not only to recognize human emotions, but also to generate facial expression for adapting to human emotions. A facial emotion recognition method based on2D-Gabor, uniform local binary pattern(LBP) operator, and multiclass extreme learning machine(ELM) classifier is presented,which is applied to real-time facial expression recognition for robots. Facial expressions of robots are represented by simple cartoon symbols and displayed by a LED screen equipped in the robots, which can be easily understood by human. Four scenarios,i.e., guiding, entertainment, home service and scene simulation are performed in the human-robot interaction experiment, in which smooth communication is realized by facial expression recognition of humans and facial expression generation of robots within 2 seconds. As a few prospective applications, the FEERHRI system can be applied in home service, smart home, safe driving, and so on.

Modulatory role of plant-derived metabolites on host-microbiota interactions:personalized therapeutics outlook

A diverse array of microbes in and on the human body constitute the microbiota.These micro-residents continuously interact with the human host through the language of metabolites to dictate the host’s physiology in health and illnesses.Any biotic and abiotic component ensuring a balanced host-microbiota interaction are potential microbiome therapeutic agents to overcome human diseases.Plant metabolites are continually being used to treat various illnesses.These metabolites target the host’s metabolic machinery and host-gut microbiota interactions to overcome human diseases.Despite the paramount therapeutic significance of the factors affecting host-microbiota interactions,a comprehensive overview of the modulatory role of plant-derived metabolites in host-microbiota interactions is lacking.The current review puts an effort into comprehending the role of medicinal plants in gut microbiota modulation to mitigate various human illnesses.It would develop a holistic understanding of hostmicrobiota interactions and the role of effectors in health and diseases.

Human Pose Estimation and Object Interaction for Sports Behaviour

In the new era of technology,daily human activities are becoming more challenging in terms of monitoring complex scenes and backgrounds.To understand the scenes and activities from human life logs,human-object interaction(HOI)is important in terms of visual relationship detection and human pose estimation.Activities understanding and interaction recognition between human and object along with the pose estimation and interaction modeling have been explained.Some existing algorithms and feature extraction procedures are complicated including accurate detection of rare human postures,occluded regions,and unsatisfactory detection of objects,especially small-sized objects.The existing HOI detection techniques are instancecentric(object-based)where interaction is predicted between all the pairs.Such estimation depends on appearance features and spatial information.Therefore,we propose a novel approach to demonstrate that the appearance features alone are not sufficient to predict the HOI.Furthermore,we detect the human body parts by using the Gaussian Matric Model(GMM)followed by object detection using YOLO.We predict the interaction points which directly classify the interaction and pair them with densely predicted HOI vectors by using the interaction algorithm.The interactions are linked with the human and object to predict the actions.The experiments have been performed on two benchmark HOI datasets demonstrating the proposed approach.