Undesirable Interactions Research Articles

Interaction detection in configurable systems – A formal approach featuring roles

Modern software systems are increasingly complex due to their configurability and adaptivity. For modeling and implementing such systems, the concept of roles is particularly well-suited as it allows capturing context-dependent properties and behavior. Similar to other compositional approaches, notably the feature-oriented development approach, the detection of (unintended) interactions between roles is a challenging task. We consider two new aspects of interactions. Hierarchical interactions may occur between systems and active interplays describe the actual situations in a sequence of events where components interact. To reason about such interactions, we introduce a compositional modeling framework based on concepts and notions of roles, comprising role-based automata (RBAs). Based on this formal foundation, we present a modeling language for succinctly describing RBAs and an implementation for translating this language into the input language of the probabilistic model checker PRISM. This enables a formal analysis of functional and non-functional properties including system dynamics, context changes, and interactions. We carry out three experimental studies as a proof of concept of such analyses: First, a peer-to-peer protocol study illustrates how undesired hierarchical interactions can be discovered automatically. Second, a study on a self-adaptive production cell demonstrates how undesired interactions influence quality-of-service measures such as reliability and throughput. Third, we illustrate how to incorporate feature-oriented system design in our role-oriented framework by means of the elevator community benchmark system.

Noise-reduced nicking enzyme-based isothermal amplification via blocking the 3′-end of the amplicon using a novel fluorophore-immobilized binder

Nicking enzyme amplification reaction (NEAR) is a promising isothermal DNA amplification method that has been applied in various sensing platforms as a promising signal amplifier. Although NEAR offers useful features for isothermal amplification, the risk of non-specific amplification imposes constraints on its potential usability. Here, we suggest a novel method to reduce the noise of NEAR, enabled by providing a specific binder to the 3′-end of amplicons as a reaction element, named Stabilizer. Stabilizer was designed to prevent undesirable interactions among the accumulated amplicons, thereby eliminating non-specific amplification caused by mis-annealing. Normal sequence Stabilizer without any modification (STB.N) was not effective in reducing the noise of NEAR. We employed a thermodynamic property of fluorophore-labeling that strengthens its annealing toward a complementary strand. We found that Stabilizer with a fluorophore at the 5′-end (F-STB) significantly reduces the noise level compared to cases of STB.N and Stabilizer-free. The NEAR with enhanced specificity would increase performance and enable applications in need of accuracy.

Microbial-Inspired Surface Patterning for Selective Bacterial Actions for Enhanced Performance in Microbial Fuel Cells.

The performance of any bio-electrochemical system is dependent on the efficiency of electrode-microbial interactions. Surface properties play a focal role in bacterial attachment and biofilm formation on the electrodes. In addition to electrode surface properties, selective bacterial adhesion onto the electrode surface is mandatory to mitigate energy loss due to undesired bacterial interactions on the electrode surface. In the present study, microbial-patterned graphite scaffolds are developed for selective bacterial-electrode interactions. A power density as high as 1105 mW/m2 is achieved with mG-E (a graphite electrode patterned with Escherichia coli), which is about 3 times higher than that of the pristine graphite electrode (370 mW/m2). Initial mechanical pre-treatment of the graphite electrode, followed by bacterial patterning, results in the formation of a unique cobblestone topography with a tuned surface area of 127.12 m2/g. This provides suitable morphology with enhanced active sites for selective bacterial intercalation in graphite layers. This cannot be otherwise achieved by any mechanical or other means. A unique methodology of symbolic regression is adopted to validate a genetic algorithm suitable for predicting a perfect correlation between surface characteristics and electrochemical characteristics with a minimum root-mean-square error of 0.08. The bacterial intercalation onto the graphite electrode causes protuberance of the graphite layers that reduces the surface potential and resistance, leading to high electron transfer. The study presents a unique bacterial-inspired surface patterning on the anode, which is critical for the performance of a microbial fuel cell.

Tunable long-lived exciton lifetime in single-layer two-dimensional LiAlTe2

In two-dimensional (2D) materials, Coulomb interactions induce large binding energies of excitons, which are detrimental to the charge separations and hence crucial to photovoltaic performance. Here, we elucidate that this drawback can be well restrained in 2D materials with an intrinsic polarization field. Based on first-principles calculations combined with nonadiabatic molecular dynamics, we propose an embodied example of a ${\mathrm{LiAlTe}}_{2}$ quadruple layer. Due to the inherent electrical polarization field in 2D ${\mathrm{LiAlTe}}_{2}$, the electron and hole wave functions are separated into opposite atomic layers similar to the case of heterostructures, reducing the undesired Coulomb interactions and contributing to the small binding energy of excitons. Through modeling and recording the excited-state dynamics, we reveal that 2D ${\mathrm{LiAlTe}}_{2}$ harbors an ultralong lifetime of excitons of about 1.69 ns, a recombination time that is similar to that found in type-II van der Waals heterostructures and superior to hitherto known $2\mathrm{D}$ photovoltaic components. Furthermore, the effect of strain on the electron-hole recombination is studied quantitatively. Our findings not only provide a compelling candidate for applications in wearable and flexible thin-film solar cells, but also suggest one of the possible ways to design the thin-film solar cells.

Investigation of Cellulose-Based Separators for Secondary Lithium Metal Batteries

Lithium-ion batteries (LIBs) have been the predominant energy storage technology for a variety of applications such as portable electronic devices and wireless power tools. However, the rising demand for emerging technologies such as long-range electric vehicles and grid-level energy storage and delivery has drastically increased the necessity for low-cost LIBs with enhanced performance and safety.Improvements in the modern LIB technology can be achieved through improvements in different, individual components of the battery. Among the key components of the battery, the separator plays a vital role. To date, polypropylene (PP)/polyethylene (PE) membranes have been used as separators in LIBs due to their desired electrochemical stability. However, these separator materials suffer from low thermal stability, which results in their deformation or decomposition at elevated temperatures upon high charging rates1. A dangerous consequence of this material degradation is an electrical short, leading to an aggressive discharge of the battery and subsequent fire. Moreover, PP/PE separators possess relatively low electrolyte wettability and an expensive and eco-unfriendly fabrication process. Hence, alternative separator materials for future LIB technology are indispensable.Among alternative separator materials, cellulose is a promising candidate2. Cellulose is derived from biomass which is one of the most abundant and renewable resources on Earth. It also is non-toxic and has high mechanical and chemical stability. Additionally, with an initial decomposition temperature of 270°C, cellulose offers a major advantage in thermal stability compared to its polymeric competitors3. The thermal and electrochemical stability, electrolyte wettability, and performance of cellulose-based separators in LIBs have been studied3,4. However, those reports mostly consider the conventional LIB electrode materials– Li transition metal oxide and graphite; and focus on the separator/electrolyte compatibility. Therefore, to be considered for future generations of high-performance Li-based batteries, cellulose-based separators must be investigated in batteries with new electrode chemistries.This work presents new insights on the interaction of cellulose-based separator and metallic Li – the leading candidate for future anodes. Coin cells were prepared using various cathode materials, Li metal anode, and a commercial cellulose-based separator. The cycling performance of the cells was tested at different C rates. Results were compared with the cycling performance of the coin cells with similar electrodes but a commercial PP/PE separator. Comparable discharge profiles were observed in the two groups of cells, but the cellulose separator hampered the charging process. Additional electrochemical analysis suggested an undesired interaction between the cellulose-based separator and metallic Li. To further understand this interaction, various protective coatings on the separator were investigated, the results of which suggest a mechanical degradation in the cellulose separator during cycling and consequently a soft short. These results are expected to provide a new understanding regarding the stability of cellulose-based separators in Li metal-containing batteries, which can help with their implementation in the next generation of Li-based batteries with enhanced performance and safety.

A unified GCNN model for predicting CYP450 inhibitors by using graph convolutional neural networks with attention mechanism

Undesirable drug-drug interactions (DDIs) may lead to serious adverse side effects when more than two drugs are administered to a patient simultaneously. One of the most common DDIs is caused by unexpected inhibition of a specific human cytochrome P450 (CYP450), which plays a dominant role in the metabolism of the co-administered drugs. Therefore, a unified and reliable method for predicting the potential inhibitors of CYP450 family is extremely important in drug development. In this work, graph convolutional neural network (GCN) with attention mechanism and 1-D convolutional neural network (CNN) were used to extract the features of CYP ligands and the binding sites of CYP450 respectively, which were then combined to establish a unified GCN-CNN (GCNN) model for predicting the inhibitors of 5 dominant CYP isoforms, i.e., 1A2, 2C9, 2C19, 2D6, and 3A4. Overall, the established GCNN model showed good performances on the test samples and achieved better performances than the recently proposed iCYP-MFE model by using the same datasets. Based on the heat-map analysis of the resulting molecular graphs, the key structural determinants of the CYP inhibitors were further explored.

Pore formation in MoS2 monolayer under irradiation by swift heavy ions: A molecular dynamics study

Molecular dynamics simulations were performed to study the formation process of nanopores in a freestanding MoS2 monolayer irradiated using swift heavy ions. We considered five types of ions (Ar, Kr, Xe, W, and Bi) with energies ranging from 26 MeV to 4.5 GeV. The impact point was always located in the center of the cell far from the border to reduce undesired high energy interactions over the periodic boundaries. The two-temperature atomistic model with an explicit account of electron thermal conductivity was used. The possibility of forming pores of various shapes with sizes from 1.5 to 48 nm was found. Pore size increases with ion incident energy and decreases with ion mass. Most of the pores have internal amorphization, which can disappear with increasing the irradiation dose. Our results demonstrate that it is feasible to fabricate controlled nanopores in an MoS2 monolayer via swift heavy ion irradiation with Bi ions being the most efficient. Possible practical applications of the obtained results are discussed.

Antifungal Encapsulated into Ligand-Functionalized Nanoparticles with High Specificity for Macrophages.

Infectious diseases caused by intracellular microorganisms such as Histoplasma capsulatum represent a significant challenge worldwide. Drug encapsulation into functionalized nanoparticles (NPs) is a valuable alternative to improving drug solubility and bioavailability, preventing undesirable interactions and drug degradation, and reaching the specific therapeutic target with lower doses. This work reports on Itraconazole (ITZ) encapsulated into core-shell-like polymeric NPs and functionalized with anti-F4/80 antibodies for their targeted and controlled release into macrophages. Uptake assay on co-culture showed significant differences between the uptake of functionalized and bare NPs, higher with functionalized NPs. In vitro assays showed that F4/80-NPs with 0.007 µg/mL of encapsulated ITZ eliminated the H. capsulatum fungus in co-culture with macrophages effectively compared to the bare NPs, without any cytotoxic effect on macrophages after 24 h interaction. Furthermore, encapsulated ITZ modulated the gene expression of anti and pro-inflammatory cytokines (IL-1, INF-Y, IL-6 and IL-10) on macrophages. Additionally, the anti-F4/80 antibody-coating enhanced natural and adequate antifungal response in the cells, exerting a synergistic effect that prevented the growth of the fungus at the intracellular level. Functionalized NPs can potentially improve macrophage-targeted therapy, increasing NPs endocytosis and intracellular drug concentration.

Dual near-infrared II laser modulates the cellular redox state of T cells and augments the efficacy of cancer immunotherapy.

Immunotherapy, including immune checkpoint inhibitors, has revolutionized cancer treatment, but only a minor fraction of patients shows durable responses. A new approach to overcome this limitation is yet to be identified. Recently, we have shown that photobiomodulation (PBM) with near-infrared (NIR) light in the NIR-II window reduces oxidative stress and supports the proliferation of CD8+ T cells, suggesting that PBM with NIR-II light could augment anti-cancer immunity. Here, we report a novel approach to support tumor-infiltrating CD8+ T cells upon PBM with NIR-II laser with high tissue penetration depth. Brief treatments of a murine model of breast cancer with dual 1064 and 1270 nm lasers reduced the expression of the programmed cell death protein 1 (PD-1) in CD8+ T cells in a syngeneic mouse model of breast cancer. The direct effect of the NIR-II laser treatment on T cells was confirmed by the enhanced tumor growth delay by the adoptive transfer of laser-treated CD8+ T cells ex vivo against a model tumor antigen. We further demonstrated that specific NIR-II laser parameters augmented the effect of the immune checkpoint inhibitor on tumor growth. PBM with NIR-II light augments the efficacy of cancer immunotherapy by supporting CD8+ T cells. Unlike the current immunotherapy with risks of undesirable drug-drug interactions and severe adverse events, the laser is safe and low-cost. It can be broadly combined with other therapy without modification to achieve clinical significance. In addition, our study established a path to develop a novel laser-based therapy to treat cancer effectively.

Simulation guided intramolecular orthogonal reporters for dissecting cellular oxidative stress and response

Cellular oxidative stress from effects of reactive oxygen species (ROS) and its induced molecular response play an important role in the pathogenesis of various diseases and important biological processes. Nanostructure-based fluorescent probes can simultaneously map the localization and abundance of ROS and its induced molecules in living cells. However, proximity-induced fluorophore interaction leads to low sensitivity and poor specificity. Here, we engineered intramolecular Orthogonal Reporters (iOR) based on DNA nanostructure scaffolds. Fluorescence reporters in iOR were precisely located with appropriate distance by simulation eliminating the undesired interaction of fluorophores. iOR functionalized with nuclear localization signal peptide is capable of imaging ROS and its related DNA repair enzyme (APE1) in the nucleus and cytoplasm with high sensitivity and specificity. iOR discloses the strong positive relation of ROS and APE1 as well as their synergistic regulation in living cells and tumor-bearing mice. This fact is first presented by direct fluorescence imaging. This work reported a new procedure for developing nanostructure-based molecular probes and would find broad applications in cellular biology and nanotechnology.

Hamiltonian Engineering with Multicolor Drives for Fast Entangling Gates and Quantum Crosstalk Cancellation.

Quantum computers built with superconducting artificial atoms already stretch the limits of their classical counterparts. While the lowest energy states of these artificial atoms serve as the qubit basis, the higher levels are responsible for both a host of attractive gate schemes as well as generating undesired interactions. In particular, when coupling these atoms to generate entanglement, the higher levels cause shifts in the computational levels that lead to unwanted ZZ quantum crosstalk. Here, we present a novel technique to manipulate the energy levels and mitigate this crosstalk with simultaneous off-resonant drives on coupled qubits. This breaks a fundamental deadlock between qubit-qubit coupling and crosstalk. In a fixed-frequency transmon architecture with strong coupling and crosstalk cancellation, additional cross-resonance drives enable a 90ns CNOT with a gate error of (0.19±0.02)%, while a second set of off-resonant drives enables a novel CZ gate. Furthermore, we show a definitive improvement in circuit performance with crosstalk cancellation over seven qubits, demonstrating the scalability of the technique. This Letter paves the way for superconducting hardware with faster gates and greatly improved multiqubit circuit fidelities.

Antifouling surface for biomedical devices: Modification of COC surface by quaternary ammonium moieties via diazonium chemistry

Prefilled biomedical devices (PFD) are growing in the pharmaceutical market due to the ease of delivering a precise dose of protein drugs. As an appealing alternative to the fragile glass, cyclic olefin copolymer (COC) was suggested. However, in the case of COC, the stability of the drug may be negatively impacted by protein aggregation. To potentially improve the surface properties of COC for PFDs, we performed functionalization of COC with quaternary ammonium moieties (QAS) using the advantages of diazonium surface chemistry. The successful functionalization of COC using QAS-diazonium salts (QAS-DS) with different alkyl chain lengths (C4, C8, C9, C10, C12) was confirmed by Raman spectroscopy and XPS measurements. Optical and fluorescence measurements revealed the optimal length of the alkyl chain-COC-C4 for improved antibiofouling performance towards bovine serum albumin (BSA). Moreover, in contrast to glass, polypropylene (PP), and pristine COC, COC-C4 allows storing the insulin for at least 2 weeks without the changes in protein structure according to dynamic light scattering and TEM images. Additionally, diazonium functionalization allows for conserving the high permeability resistance, transparency, and mechanical stiffness. The improved stability of insulin in a COC-C4 container is explained by the formation of an additional hydration layer serving as a barrier to undesired interaction with biomolecules.

Differential Surface Adsorption Phenomena for Conventional and Novel Surfactants Correlates with Changes in Interfacial mAb Stabilization.

Protein adsorption on surfaces can result in loss of drug product stability and efficacy during the production, storage, and administration of protein-based therapeutics. Surface-active agents (excipients) are typically added in protein formulations to prevent undesired interactions of proteins on surfaces and protein particle formation/aggregation in solution. The objective of this work is to understand the molecular-level competitive adsorption mechanism between the monoclonal antibody (mAb) and a commercially used excipient, polysorbate 80 (PS80), and a novel excipient, N-myristoyl phenylalanine-N-polyetheramine diamide (FM1000). The relative rate of adsorption of PS80 and FM1000 was studied by pendant bubble tensiometry. We find that FM1000 saturates the interface faster than PS80. Additionally, the surface-adsorbed amounts from X-ray reflectivity (XRR) measurements show that FM1000 blocks a larger percentage of interfacial area than PS80, indicating that a lower bulk FM1000 surface concentration is sufficient to prevent protein adsorption onto the air/water interface. XRR models reveal that with an increase in mAb concentration (0.5-2.5 mg/mL: IV based formulations), an increased amount of PS80 concentration (below critical micelle concentration, CMC) is required, whereas a fixed value of FM1000 concentration (above its relatively lower CMC) is sufficient to inhibit mAb adsorption, preventing mAb from co-existing with surfactants on the surface layer. With this observation, we show that the CMC of the surfactant is not the critical factor to indicate its ability to inhibit protein adsorption, especially for chemically different surfactants, PS80 and FM1000. Additionally, interface-induced aggregation studies indicate that at minimum surfactant concentration levels in protein formulations, fewer protein particles form in the presence of FM1000. Our results provide a mechanistic link between the adsorption of mAbs at the air/water interface and the aggregation induced by agitation in the presence of surfactants.

(Invited) Stabilizing and Enhancing Lithium-Ion Batteries with Chemically Inert 2D Materials

Efficient energy storage systems represent a critical technology across many sectors including consumer electronics, electrified transportation, and a smart grid accommodating intermittent renewable energy sources. Arguably, the most important advance in energy storage over the past three decades is the lithium-ion battery, which was recently recognized with the Nobel Prize in Chemistry. However, despite its many successes, issues related to safety, energy density, charging time, and operating temperature range have hindered the realization of the full potential of lithium-ion battery technology, particularly in large-scale applications such as grid-level storage and full electrification of transportation networks. Nanostructured materials were once thought to present compelling opportunities for next-generation lithium-ion batteries, but inherent problems related to high surface area to volume ratios at the nanometer-scale (e.g., undesirable surface chemical interactions between electrodes and electrolytes) have impeded their adoption for commercial applications. This talk will explore how the chemical inertness of select two-dimensional (2D) materials are driving a resurgence in nanostructured lithium-ion battery materials [1]. For example, conformal graphene coatings on lithium-ion battery cathode powders mitigate surface degradation and minimize the formation of the solid electrolyte interphase, thus improving cycling stability [2]. In addition, the high electrical conductivity of graphene reduces cell impedance, resulting in enhanced kinetics that enable high-rate capability and low-temperature performance down to –20 °C [3]. On the other hand, ionogel electrolytes based on ionic liquids and hexagonal boron nitride (hBN) nanoplatelets provide safe, high-rate operation at high temperatures up to 175 °C, which represents the highest operating temperature to date for solid-state lithium-ion batteries [4,5]. The strong interfacial interactions between hBN and ionic liquids further enable novel electrolyte architectures based on layered heterostructure ionogels that result in unprecedently high energy densities and rate performance for solid-state batteries [6].[1] H. Bergeron, et al., Chemical Reviews, 121, 2713 (2021).[2] K.-Y. Park, et al., Advanced Energy Materials, 10, 2001216 (2020).[3] K.-Y. Park, et al., Advanced Materials, DOI: 10.1002/adma.202106402 (2021).[4] W. J. Hyun, et al., ACS Nano, 13, 9664 (2019).[5] W. J. Hyun, et al., Advanced Energy Materials, 10, 2002135 (2020).[6] W. J. Hyun, et al., Advanced Materials, 33, 2007864 (2021).

STUDY OF SOIL STRUCTURE INTERACTION AND SEISMICRESPONSE OF BASE ISOLATED STEEL FRAME WITH BUCKLING RESTRAINED BRACEDAMPING SYSTEMS

n this study, The project relies on the, process in which the response of the soil influences the motion of the structure and the motion of the structure influences the response of the soil is termed as Soil Structure Interaction. In this case neither the structural displacements nor the ground displacements are independent from each other. The phrase ‘soil-structure interaction’ may be defined as influence of the behaviour of soil immediately beneath and around the foundation on the response of soil-structure subjected to either static or dynamic loads. A buckling-restrained brace (BRB) is a structural brace in a building, designed to allow the building to withstand cyclical lateral loadings, typically earthquake-induced loading. It consists of a slender steel core, a concrete casing designed to continuously support the core and prevent buckling under axial compression, and an interface region that prevents undesired interactions between the two. It consists of four models of clay, sand and silt, each one has models as without bracing, with X-bracing, with inverted V-bracing and Y-bracing. It is concluded that X-bracing has less displacement, storey drift and high base shear compared to others. Also, X-bracing with SSI has less displacement, storey drift and high base shear compared to without SSI

Polypharmacy and Potential Drug–Drug Interactions in Patients with Rheumatoid Arthritis

Background: Rheumatoid arthritis (RA) is a systemic autoimmune disease with protean manifestations. It is characterized by symmetric polyarticular inflammation, which can lead to progressive joint damage. As a result, RA is associated with substantial functional disability, morbidity, and accelerated mortality, which pose an enormous and growing societal burden. Polypharmacy is a major public health concern, which is growing worldwide. Polypharmacy is associated with adverse outcomes including mortality, falls, adverse drug reactions, increased length of stay in hospital and readmission to hospital soon after discharge. Objectives: The aim of this study was to quantify polypharmacy in a group of patients with RA, its relationship with patients’ characteristics and to assess the risk of potential undesirable interactions between medications used for managing RA and those used for chronic and non-chronic diseases. Materials and Methods: A cross-sectional study was conducted at Baghdad Teaching Hospital, Rheumatology Unit during the period from December 2019 to December 2020. A total of 188 adult patients, previously diagnosed with RA according to the 2010 American College of Rheumatology/ European League against Rheumatism rheumatoid arthritis classification criteria, were included in the study. Data were collected using a pre-constructed data collection sheet. Questionnaires included demographic and clinical data of the patients. In this study, polypharmacy was defined as the association of five or more medications, regardless of the duration. Drug interactions were identified by use of the Medscape’s drug interaction checker® database. Results: Among 188 RA patients in this study, polypharmacy was found in 71.8% of the patients and there were 331 potential drug–drug interactions (1.77 ± 2.52 DDIs/patient). Most of the potential drug–drug interactions were related to the use of methotrexate, with nonsteroidal anti-inflammatory drugs being the major representative of these drug–drug interactions with methotrexate. Conclusion: High prevalence of polypharmacy was found in RA patients. Positive correlation between polypharmacy and patient’s age, disease activity and the presence of other comorbid conditions. Polypharmacy was associated with increased incidence of potential drug–drug interactions in RA patients. Methotrexate was involved in most drug–drug interactions.

Mass Spectrometry Approaches Empowering Neuropeptide Discovery and Therapeutics.

The discovery of insulin in the early 1900s ushered in the era of research related to peptides acting as hormones and neuromodulators, among other regulatory roles. These essential gene products are found in all organisms, from the most primitive to the most evolved, and carry important biologic information that coordinates complex physiology and behavior; their misregulation has been implicated in a variety of diseases. The evolutionary origins of at least 30 neuropeptide signaling systems have been traced to the common ancestor of protostomes and deuterostomes. With the use of relevant animal models and modern technologies, we can gain mechanistic insight into orthologous and paralogous endogenous peptides and translate that knowledge into medically relevant insights and new treatments. Groundbreaking advances in medicine and basic science influence how signaling peptides are defined today. The precise mechanistic pathways for over 100 endogenous peptides in mammals are now known and have laid the foundation for multiple drug development pipelines. Peptide biologics have become valuable drugs due to their unique specificity and biologic activity, lack of toxic metabolites, and minimal undesirable interactions. This review outlines modern technologies that enable neuropeptide discovery and characterization, and highlights lessons from nature made possible by neuropeptide research in relevant animal models that is being adopted by the pharmaceutical industry. We conclude with a brief overview of approaches/strategies for effective development of peptides as drugs. SIGNIFICANCE STATEMENT: Neuropeptides, an important class of cell-cell signaling molecules, are involved in maintaining a range of physiological functions. Since the discovery of insulin's activity, over 100 bioactive peptides and peptide analogs have been used as therapeutics. Because these are complex molecules not easily predicted from a genome and their activity can change with subtle chemical modifications, mass spectrometry (MS) has significantly empowered peptide discovery and characterization. This review highlights contributions of MS-based research towards the development of therapeutic peptides.

Highly efficient flexible organic photovoltaic modules for sustainable energy harvesting under low-light condition via suppressing voltage-drop by metal-mediated cross-linkable polymer interfacial layer

This study aims to expand the practical applications of large-area flexible organic photovoltaics (OPV), such that they retain their high stability and efficiency even under various weather conditions and external stresses. By developing polyethyleneimine derivative-based cathode interfacial layer (CIL) and non-fullerene acceptor (NFA) material in OPVs, the efficiency and stability decrease rapidly due to an undesirable interaction when these two materials are concomitantly applied. In this study, we designed a novel low-cost metal-mediated cross-linked non-conjugated polymer interfacial layer (c-PEIE) and improved the device performance and stability of flexible OPVs from the cell-to-module scale. c-PEIE CIL based flexible OPV cell achieves one of the highest power conversion efficiencies (PCE) of 16.45% and remarkable photostability, retaining 77.58% of its initial PCE for 110 h under continuous light illumination, while the conventional PEIE based cells realize a PCE of 12.58% and poor device stability. Accordingly, a 50 cm2, large-area, flexible OPV module was also fabricated with an excellent PCE of 13.12% which is ∼ 80% as efficient as small-area flexible cells. Notably, c-PEIE based OPV devices maintain high output power on cloudy days, which is a particular point of interest to efficiently harvest sunlight energy constantly. The tunable energy barrier and significant low-leakage current of CIL play a critical role in reducing open-circuit voltage and fill factor losses under low-light environments. Such energy sources can provide power efficiently all day long in low-light or cloudy environments to the Internet of Things wireless networks integrated with battery-independent photovoltaics.

Janus nanoribbon-in-ribbon embedded structure microbelts and array with luminescent-conductive-magnetic polyfunction

By innovatively combining Janus structure with core–shell structure, a brand-new flexible one-dimensional Janus nanoribbon-in-ribbon embedded structure microbelt is designed and assembled. As a case study, {[CoFe2O4/Polymethyl methacrylate (PMMA)]//[Polyaniline (PANI)/PMMA]}@[Tb(acac)3bpy/PMMA] magnetism-electric conduction-luminescence multifunctional Janus nanoribbon-in-ribbon embedded structure microbelt (denoted as [(M//E)@L] microbelt) is constructed via electrospinning. Each [(M//E)@L] microbelt is composed of the core layer of [CoFe2O4/PMMA]//[PANI/PMMA] Janus nanoribbon with magnetic-conductive bifunctionality and the shell layer of Tb(acac)3bpy/PMMA luminescent nanobelt, and further [(M//E)@L] microbelts are directionally aligned to form array. The Janus nanoribbon in the core layer is conductive along the nanoribbon length direction, but insulating along with nanoribbon width direction due to the presence of non-conductive CoFe2O4/PMMA, viz. the two vertical directions have different conductions, and thus Janus nanoribbon has microscopic conductive anisotropy. Based on this characteristic, new concept of microscopic conductive anisotropy or microscopic anisotropic conduction is first proposed. The each [(M//E)@L] microbelt with special three functional partitions restricts the luminescent, conductive and magnetic materials respectively in their own regions, leading to availably reducing the undesirable interactions among these functional materials to achieve excellent polyfunctions. The formation mechanisms of unique Janus nanoribbon-in-ribbon embedded structure microbelt and array are proposed, and new techniques for constructing microbelt and array are established.

Real-Time Social Robot’s Responses to Undesired Interactions Between Children and their Surroundings

Aggression in children is frequent during the early years of childhood. Among children with psychiatric disorders in general, and autism in particular, challenging behaviours and aggression rates are higher. These can take on different forms, such as hitting, kicking, and throwing objects. Social robots that are able to detect undesirable interactions within its surroundings can be used to target such behaviours. In this study, we evaluate the performance of five machine learning techniques in characterizing five possible undesired interactions between a child and a social robot. We examine the effects of adding different combinations of raw data and extracted features acquired from two sensors on the performance and speed of prediction. Additionally, we evaluate the performance of the best developed model with children. Machine learning algorithms experiments showed that XGBoost achieved the best performance across all metrics (e.g., accuracy of 90%) and provided fast predictions (i.e., 0.004 s) for the test samples. Experiments with features showed that acceleration data were the most contributing factor on the prediction compared to gyroscope data and that combined data of raw and extracted features provided a better overall performance. Testing the best model with data acquired from children performing interactions with toys produced a promising performance for the shake and throw behaviours. The findings of this work can be used by social robot developers to address undesirable interactions in their robotic designs.