Effective Interaction Research Articles

Disclosing Topographical and Chemical Patterns in Confined Films of High-Molecular-Weight Block Copolymers under Controlled Solvothermal Annealing

The microphase separation of high-molecular-weight block copolymers into nanostructured films is strongly dependent on the surface fields. Both, the chain mobility and the effective interaction parameters can lead to deviations from the bulk morphologies in the structures adjacent to the substrate. Resolving frustrated morphologies with domain period L0 above 100 nm is an experimental challenge. Here, solvothermal annealing was used to assess the contribution of elevated temperatures of the vapor Tv and of the substrate Ts on the evolution of the microphase-separated structures in thin films symmetric of polystyrene-b-poly(2vinylpyridine) block copolymer (PS-PVP) with L0 about 120 nm. Pronounced topographic mesh-like and stripe patterns develop on a time scale of min and are attributed to the perforated lamella (PL) and up-standing lamella phases. By setting Tv/Ts combinations it is possible to tune the sizes of the resulting PL patterns by almost 10%. Resolving chemical periodicity using selective metallization of the structures revealed multiplication of the topographic stripes, i.e., complex segregation of the component within the topographic pattern, presumably as a result of morphological phase transition from initial non-equilibrium spherical morphology. Reported results reveal approaches to tune the topographical and chemical periodicity of microphase separation of high-molecular-weight block copolymers under strong confinement, which is essential for exploiting these structures as functional templates.

Uncovering post-adoption usage of AI-based voice assistants: a technology affordance lens using a mixed-methods approach

ABSTRACT Despite the growing proliferation of AI-based voice assistants in our daily lives, how different functions of AI-based voice assistants affect users’ post-adoption usage behaviours remains an under-investigated research question. This study explores the nature and causation of post-adoption usage behaviours (effective utilisation after initial adoption or diffusion) within the context of AI-based voice assistants. Using a sequential mixed-methods research design, we first identify the post-adoption usage behaviours of AI-based voice assistants as a multidimensional concept comprised of routine use and extended use, then develop a contextualised model by revealing technology-specific antecedents, cognitive beliefs, and boundary conditions. By integrating results from the quantitative study and qualitative study, we find that three technology affordances (i.e., anthropomorphism affordance, interactivity affordance, and personalisation affordance) are salient antecedents of two cognitive beliefs, which further affect users’ routine use and extended use of AI-based voice assistants. Additionally, we uncover use frequency as a boundary condition and obtain a complementary view of post-adoption usage of AI-based voice assistants. The empirical research findings can extend the post-adoption IS usage literature and provide practical implications for crafting user-centred functionalities to facilitate effective human-AI interactions.

An Injectable Hydrogel Composing Anti-Inflammatory and Osteogenic Therapy toward Bone Erosions Microenvironment Remodeling in Rheumatoid Arthritis.

Healing bone erosions in rheumatoid arthritis (RA) remains greatly challenging via biomaterial strategies. Given the unsuccessful innate bone erosion healing due to an inflammatory disorder, over-activated osteoclasts, and impaired osteoblasts differentiation, RA pathogenesis-guided engineering of an innovative hydrogel platform is needed for remodeling osteoimmune and osteogenic microenvironment of bone erosion healing. Herein, in situ adaptable and injectable interpenetrating polymer network (IPN) hydrogel is developed through an ingenious combination of a bio-orthogonal reaction between hyaluronic acid (HA) and collagen, along with effective electrostatic interactions leveraging bisphosphonate (BP)-functionalized HA macromers (HABP) and nanorod shaped zinc (Zn)-doped biphasic calcium phosphate (ZnBCP). IPN hydrogel exhibits exceptional adaptability to the local shape complexity at bone erosions, and by integrating ZnBCP and HABP, a multi-stage releasing platform is engineered, facilitating controlled cargo delivery for remodeling more anti-inflammatory M2 cells and reducing over-activated osteoclastic activities, thereby reconstructing the bone regeneration microenvironment. Sustainedly co-delivering multiple ions (calcium and phosphate) can display excellent osteogenic properties and be conducive to the bone formation process, by effects of osteogenesis-associated cell differentiation. Overall, the introduced bioactive IPN hydrogel therapy remodels the osteoimmune environment by synergistic pro-inflammation-resolving, osteogenesis, and anti-osteoclastic activities, displaying excellent bone reconstruction in the collagen-induced arthritis rabbit model.

Boosting oxygen reduction in acidic media through integration of Pt-Co alloy effect and strong interaction with carbon defects

Boosting oxygen reduction in acidic media through integration of Pt-Co alloy effect and strong interaction with carbon defects

Effective interactions of the open bosonic string via field theory

We describe a method to extract an effective Lagrangian description for open bosonic strings, at zero transcendentality. The method relies on a particular formulation of its scattering amplitudes derived from color-kinematics duality. More precisely, starting from a (DF)2 + YM quantum field theory, we integrate out all the massive degrees of freedom to generate an expansion in the inverse string tension α′. We explicitly compute the Lagrangian terms through O\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{O} $$\\end{document}(α′4), and target the sector of operators proportional to F4 to all orders in α′.

Motorized chain models of the ideal chromosome

An array of motor proteins consumes chemical energy in setting up the architectures of chromosomes. Here, we explore how the structure of ideal polymer chains is influenced by two classes of motors. The first class which we call "swimming motors" acts to propel the chromatin fiber through three-dimensional space. They represent a caricature of motors such as RNA polymerases. Previously, they have often been described by adding a persistent flow onto Brownian diffusion of the chain. The second class of motors, which we call "grappling motors" caricatures the loop extrusion processes in which segments of chromatin fibers some distance apart are brought together. We analyze these models using a self-consistent variational phonon approximation to a many-body Master equation incorporating motor activities. We show that whether the swimming motors lead to contraction or expansion depends on the susceptibility of the motors, that is, how their activity depends on the forces they must exert. Grappling motors in contrast to swimming motors lead to long-ranged correlations that resemble those first suggested for fractal globules and that are consistent with the effective interactions inferred by energy landscape analyses of Hi-C data on the interphase chromosome.

Effect of off-axis electron beam on the performance of a gyroklystron amplifier

A crucial part of a gyroklystron is an electron beam. For the efficient operation of the gyroklystron, effective interaction between the radio frequency wave and the electron beam is necessary. Although the manufacturing and assembly of the gyroklystron are complicated, during the assembly process of various components of the gyroklystron, there is some possibility that the components may be misaligned from their actual positions. The operation of a gyroklystron is very sensitive if its components are misaligned. Electron beam misalignment is one type of such misalignment. This paper studies the effect of an off-axis electron beam on gyroklystron performance. Due to misalignment, the electron beam radius will vary in its position as the electron beam gyrates. First, the nonlinear single-mode analysis describing the beam–wave interaction process within the gyroklystron amplifier is discussed. As reported in the literature, an experimental, two-cavity 35 GHz fundamental harmonic gyroklystron amplifier has been used to conduct the present study. The results obtained from the analytically developed approach are benchmarked by the results of the experimental device. Subsequently, the analysis developed has been extended to investigate the impact of the misaligned electron beam on the gyroklystron performance characteristics. The study shows that efficiency, output power and gain decrease with misalignment, whereas bandwidth does not change due to such misalignments. These findings demonstrate the critical role that the misaligned electron beam plays in the operation of a gyroklystron amplifier.

Interaction between antidepressant drug trazodone with double-stranded DNA: Multi-spectroscopic and computational analysis

Trazodone (TZD) is an antidepressant drug used to treat major depressive and sleeping disorders. Elevated doses of trazodone are associated with central nervous system depression, which manifests as nausea, drowsiness, confusion, vertigo, exhaustion, etc. To develop a clinically viable active pharmaceutical compound with minimal adverse effects, it is imperative to possess a comprehensive knowledge of the drug's action mechanism on DNA. Hence, we investigate the mode of interaction between trazodone and DNA utilizing various spectroscopic and computational techniques. Studies using UV–vis titration showed that the DNA and trazodone have an effective interaction. The magnitude of the Stern-Volmer constant (KSV) has been calculated to be 5.84 × 106 M−1 by the Lehrer equation from a steady-state fluorescence study. UV–vis absorption, DNA melting, dye displacement, and circular dichroism studies suggested that trazodone binds with DNA in minor grooves. Molecular docking and molecular dynamic simulation demonstrated that the thalidomide-DNA system was stable, and the mode of binding was minor groove. Furthermore, ionic strength investigation demonstrates that DNA and trazodone do not have a substantial electrostatic binding interaction.

Humidity modifies species-specific and age-dependent heat stress effects in an insect host-parasitoid interaction.

Climate change is projected to increase the frequency and intensity of extreme heat events, and may increase humidity levels, leading to coupled thermal and hydric stress. However, how humidity modulates the impacts of heat stress on species and their interactions is currently unknown. Using an insect host-parasitoid interaction: the Indian meal moth, Plodia interpunctella, and its endoparasitoid wasp, Venturia canescens, we investigated how humidity interacted with heat stress duration, applied at different host developmental stages, to affect life history traits. Hosts parasitized as 4th instar larvae and unparasitized hosts were maintained in high- (60.8% RH) or low-humidity (32.5% RH) at constant 28°C. They were then exposed to a 38°C thermal stress with a duration of 0 (no heat stress), 6 or 72 h in either the 4th or 5th host instar. Neither humidity nor heat stress duration affected emergence of unparasitized hosts, but increasing heat stress duration during the 4th instar decreased parasitoid emergence irrespective of humidity. When applied during the 5th instar, increasing heat duration decreased parasitoid emergence under low humidity, but no effect of heat stress was found under high humidity. Moreover, experiencing longer heat stress in the 4th instar increased host larval development time and decreased body size under high humidity, but this effect differed under low humidity; increasing heat duration in the 5th instar decreased parasitoid body sizes only under low humidity. Larval stage and heat stress duration directly affected parasitized host survival time, with a concomitant indirect reduction of parasitoid sizes. We show that humidity modifies key life history responses of hosts and parasitoids to heat stress in species-specific ways, highlighting the potential importance of humidity in regulating host-parasitoid interactions and their population dynamics. Finally, we emphasize that interactions between environmental stressors need to be considered in climate change research.

How Regulatory Media Information Disclosure Affects Auditor Selection — Empirical Evidence Based on the Interaction Platform between Investors and Listed Companies

This study uses a econometric model to assess how online interactions between investors and listed companies influence auditor selection. It observes auditor choice as a metric to gauge management's response to market reactions from information disclosed on investor-company platforms. Findings reveal that more effective online interactions lead to the selection of higher quality auditors, especially in companies with greater marketization and higher institutional investor shareholding ratios.

Structural effects, corrosion inhibition mechanisms and timeliness of three tetrazole derivatives on copper in a 3.5wt.% NaCl solution

The structural effects, corrosion inhibition mechanisms and timeliness of 5-methyltetrazole (MT), 5-aminotetrazole (AT) and 5-mercapto-1-methyltetrazole (MMT) on copper in a 3.5 wt.% NaCl solution were studied by electrochemical experiments, surface characterizations and theoretical calculations. At the initial soaking stage, MT exhibited higher corrosion inhibition efficiency (99.65 %), which might stem from the electron donating effect and hydrophobic interaction of -CH3. While MMT exhibited lower corrosion inhibition efficiency (92.64 %), which might stem from the electron withdrawing effect and hydrophilicity of -SH. As the soaking time prolonged, the corrosion inhibition efficiencies of AT and MMT increased (99.49 % and 99.51 %). This might be because the N and S atoms of -NH2 and -SH could also provide lone pair electrons to coordinate with copper, especially S atom. As the soaking time was further prolonged, the formation of corrosion products weakened the interaction between N and S with copper, reducing the corrosion inhibition performance of AT and MMT. MT, AT and MMT molecules on Cu (111) surface can mainly undergo perpendicular adsorption, simultaneously accompanied by parallel adsorption.

DeFuseDTI: Interpretable drug target interaction prediction model with dual-branch encoder and multiview fusion

Predicting the interaction between drugs and targets is a crucial step in drug development, and computer-based deep learning approaches have the potential to significantly reduce costs. Existing models using a single encoder often suffer from insufficient cross-modal feature extraction, with most models tending to overly focus on extracting locally aggregated information, thereby diluting the detailed features of each target residue and drug atom. Additionally, the lack of effective interaction fusion between drug and target lead to prediction results lacking reliable interpretability, posing a more urgent issue. To address these challenges, we propose a dual-branch encoder model, DeFuseDTI, which includes base encoder and detail encoder to extract locally aggregated features and detailed features of each target residue and drug atom. The detail encoder (utilizing Invertible Neural Networks for targets and graph transformers for drugs) can capture furtherly the features of each atom and residue, providing rich and precise features for model interpretability. For better achieve interactive learning of drug and target features, the Multiview Fusion Attention learning module was introduced to integrate multiview features and generate a unified representations for decoding prediction results. Based on the module's unique attention mechanism, drug-target importance matrices can be obtained, which offer interpretable analysis at the molecular level. Experimental results and analyses demonstrate that DeFuseDTI outperforms several state-of-the-art models on four public datasets. Its significant interpretability holds promise for providing accurate and scientifically meaningful guidance for biochemical experiments at the molecular level.

Optimized Electrodeposition of Ni2O3 on Carbon Paper for Enhanced Electrocatalytic Oxidation of Ethanol.

The urgent need for sustainable and efficient energy conversion technologies has propelled research into novel electrocatalysts for fuel cell applications. This study investigates a carbon paper (CP)-supported Ni2O3 catalyst for the electrocatalytic oxidation of ethanol. We utilized electrodeposition to uniformly deposit/dop Ni2O3 onto the CP, creating an effective electrocatalyst. Our approach allows the tailoring of the doping degree by adjusting the electrodeposition potential. The optimal doping degree, achieved at a medium deposition potential, results in an electrode with high intrinsic activity and a substantial electrochemically active surface area (ECSA), thereby enhancing its electrocatalytic activity. This catalyst efficiently facilitates the oxidation of ethanol to formic acid while maintaining good stability. The enhanced performance is attributed to the effective interface and interaction between Ni2O3 and CP. This work not only provides insights into the design of efficient Ni-based catalysts for ethanol oxidation but also paves the way for developing advanced materials for renewable energy conversion.

Electron–ion collision and polarization of X-ray fluorescence radiation under hot quantum plasma conditions

In the current article, the spectral properties and electron collision (total and magnetic) excitation cross sections of ions taking placed in quantum plasmas are investigated. These cross sections are further used to study the polarization and angular distribution characteristics of the de-excitation radiation X-ray spectra, which play an important role in basic theoretical research, the diagnosis of the plasma environment, and the design of optical devices. To do so, a distorted wave method within the relativistic Dirac–Coulomb atomic structure scheme is suggested. The effective interaction potential between electrons and particles in hot quantum plasmas in the method is determined using a quantum approach that incorporates the influence of effective plasma screening effects caused by collective plasma oscillations. This potential replaces the traditional Coulomb interaction potential and is used in solving the modified Dirac equation to obtain the bound and continuum electron wave functions. Higher-order relativistic effects, such as the Breit interaction and the dominant quantum electrodynamics corrections, are added to enhance the accuracy of the method. Detailed calculations for the relativistic atomic structure and collision excitation dynamics process are carried out, taking the highly stripped H-like O7+ ion of astrophysical importance as an illustrative example. Detailed investigations are also conducted on the variation of energies, collision cross sections, and fluorescence polarizations as functions of the plasma parameters. Our results suggest that the joint effects of shielding and plasma coupling lead the energies, cross sections and fluorescence polarizations decrease (compared with the isolated case). The angular distribution of the X-ray fluorescence emission shows large change, suggesting their sensitivity to these effects. This study not only offers a valuable approach to investigating the plasma shielding and plasmon coupling effects in quantum plasmas but also holds significant relevance for applications in controlled nuclear fusion, astrophysical plasmas and so on.

CYBERCRIME: CURRENT STATUS AND COUNTERMEASURES

The current stage of development of society is characterized by the widespread introduction of modern telecommunication technologies into all spheres of people’s lives. Unfortunately, information technologies are increasingly being used by attackers for criminal purposes. The reason for this is the distinctive features of virtual space and technologies used to transmit and use information. The article provides a brief description of the state of cybercrime at the current stage of development, and also highlights the specific features of crimes committed using information technology, which ensure an increase in the total number, as well as a high level of latency. The authors pay special attention to such characteristics of cybercrime as transborder nature, the anonymity of the criminal and the high speed of dissemination of information among a large number of Internet users, facilitating the use of high technologies by attackers hoping to hide traces of crimes and remain undetected. In addition, a brief description of victims of cybercrime is given. The authors have identified the main trends in the development of new ways and methods of committing them, and proposed measures to prevent the increase in the number of crimes in cyberspace by informing citizens, increasing the level of information and financial literacy, and international cooperation for effective interaction in order to ensure cybersecurity.

Inovasi Media Pembelajaran Menggunakan AR (Augmented Reality) pada Materi Sistem Pencernaan

The learning process is a communication that involves teachers, students and subject matter. Learning media is needed to clarify the material and facilitate effective interaction between teachers and students. Along with the development of technology, Augmented Reality (AR) is one of the potential learning media. AR is able to improve concept understanding with interesting and interactive 3D visualizations, such as in the human digestive system material in the Merdeka Phase F class XI curriculum. However, AR also has drawbacks such as the lack of immediate feedback and distraction for students. To overcome this, innovation is needed, for example by integrating audio and video in AR media, thus providing a more thorough and effective learning experience. This innovation can support active and collaborative inquiry-based learning, enrich student understanding, as well as facilitate dynamic formative assessment. With collaboration between educators, technology developers and policy makers, the challenges of AR implementation can be overcome. The integration of this technology in education has the potential to improve the quality of learning and the development of 21st century skills such as creativity and problem solving. Key words: media innovation, augmented reality, biology learning

Exploring an athletic talent development environment in China: A case study of a sport-friendly high school

This case study utilized the holistic ecological approach (HEA) to explore a successful athletic talent development environment (ATDE) in China. As a case, we selected a basketball team in one Shanghai sport-friendly high school with outstanding individual and team achievements and aimed at (a) describing the ATDE, and (b) identifying environmental success factors (ESF). Using participant observations, document analysis, informal talks, and formal interviews with key stakeholders, including coaches, teachers, athletes, and administrators from sports and education departments, we derived the ATDE and ESF empirical models. The findings showed that (a) the ATDE demonstrated effective interactions between macro- and micro-levels, and (b) the experienced head coach, dedicated assistant coach, and support from athletes’ parents contributed to overcoming barriers of preconditions (e.g., limited financial and human resources) within the environment. Further, a coherent and robust cultural paradigm led by the head coach helped the environment maintain its success for a long period. Although some features are similar to successful ATDEs in other countries, unique characteristics (e.g., not prioritizing athletes’ autonomy) specific to this ATDE within the Chinese cultural context have been identified. Our findings supplement current studies on ATDEs using the HEA and reflect the environment within Chinese context, offering insights for researchers and practitioners.

Inferring effective electrostatic interaction of charge-stabilized colloids from scattering using deep learning

An innovative strategy is presented that incorporates deep auto-encoder networks into a least-squares fitting framework to address the potential inversion problem in small-angle scattering. To evaluate the performance of the proposed approach, a detailed case study focusing on charged colloidal suspensions was carried out. The results clearly indicate that a deep learning solution offers a reliable and quantitative method for studying molecular interactions. The approach surpasses existing deterministic approaches with respect to both numerical accuracy and computational efficiency. Overall, this work demonstrates the potential of deep learning techniques in tackling complex problems in soft-matter structures and beyond.

Experiences of restrictive interventions in psychiatric health care from the perspectives of patients and health care professionals: Meta-synthesis of qualitative evidence.

Following their experience, patients with physical restraints often experienced traumatic sensations. The experiences of healthcare professionals' (HCPs') are primarily concerned with moral distress or conflicts between loyalty to the treatment and oppression of the patient's freedom when implementing RIs. Improving the competency of HCPs can help establish therapeutic relationships rooted in compassionate care and facilitate appropriate assessments to determine whether and how often RIs are necessary. Furthermore, fostering an environment that guarantees patient safety and dignity, assuring a sufficient staffing ratio, and providing opportunities to share RI experiences can help improve the quality of care and build safe environments for RIs. Effective interaction between HCPs and patients, thorough patient assessment, and compassionate patient care may improve competency of HCPs intervene RIs procedures. Creating a safe therapeutic environment, including improvements to structural environments, increasing the staff-to-patient ratio, establishing organizational policies that guarantee staff debriefing, provide emotional support, provide appropriate training programs to HCPs to their coping skills during RIs also reduce the use of RIs and improve the quality of mental health care. INTRODUCTION: Restrictive interventions (RIs) are used in psychiatric inpatient units for ensuring safety. However, few studies have comprehensively reviewed physical restraint and seclusion experiences from the perspectives of both patients and healthcare professionals' (HCPs'). This study aims to gain an in-depth understanding of the RI experiences of mental health inpatients and HCPs. A meta-synthesis was undertaken of qualitative studies exploring the RI experiences. Five electronic databases were searched and additional manual searches were performed for studies published within the last decade. Twelve articles were included, and a thematic analysis was conducted. The Critical Appraisal Skills Program (CASP) checklist was used to assess data quality. Two main subthemes were identified: 'Competency of HCPs' (three subthemes: interaction between patients and HCPs, assessment methods, and care) and 'systems' (three subthemes: environment, protocols with training, and debriefing), including both positive and negative experiences. The Competency of HCPs and the ward environment are critical factors related to patients' unmet needs. Effective interactions between HCPs and patients, thorough patient assessments, and compassionate patient care are important elements of RI implementation. An environment that guarantees safety and care with dignity, sufficient staffing ratios, and opportunities to share RI experiences may improve quality of care and create safe environments for RIs.

Collaborative Analysis of Learners’ Emotional States Based on Cross-Modal Higher-Order Reasoning

Emotion is a significant factor influencing education and teaching, closely intertwined with learners’ cognitive processing. Conducting analysis of learners’ emotions based on cross-modal data is beneficial for achieving personalized guidance in intelligent educational environments. Currently, due to factors such as data scarcity and environmental noise, data imbalances have led to incomplete or missing emotional information. Therefore, this study proposes a collaborative analysis model based on attention mechanisms. The model extracts features from various types of data using different tools and employs multi-head attention mechanisms for parallel processing of feature vectors. Subsequently, through a cross-modal attention collaborative interaction module, effective interaction among visual, auditory, and textual information is facilitated, significantly enhancing comprehensive understanding and the analytical capabilities of cross-modal data. Finally, empirical evidence demonstrates that the model can effectively improve the accuracy and robustness of emotion recognition in cross-modal data.