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Abstract Carbaporphyrin dimers, investigated for their distinctive electronic structures and exceptional properties, have predominantly consisted of systems containing identical subunits. This study addresses the associated knowledge gap by focusing on asymmetric carbaporphyrin dimers with Janus-like characteristics. The synthesis of a Janus-type carbaporphyrin pseudo-dimer 5 is presented. It displays antiaromatic characteristics on the fused side and nonaromatic behavior on the unfused side. A newly synthesized tetraphenylene (TPE) linked bis-dibenzihomoporphyrin 8 and a previously reported dibenzo[g,p]chrysene (DBC) linked bis-dicarbacorrole 9 were prepared as controls. Comprehensive analyses, including 1H NMR spectral studies, single crystal X-ray diffraction analyses, and DFT calculations, validate the mixed character of 5. A further feature of the Janus pseudo-dimer 5 is that it may be transformed into a heterometallic complex, with one side coordinating a Cu(III) center and the other stabilizing a BODIPY complex. This disparate regiochemical reactivity underscores the potential of carbaporphyrin dimers as versatile frameworks, with electronic features and site-specific coordination chemistry controlled through asymmetry. These findings position carbaporphyrin dimers as promising candidates for advances in electronic structure studies, coordination chemistry, materials science, and beyond.

Remotely sensed products are often used in watershed modeling as additional constraints to improve model predictions and reduce model uncertainty. Remotely sensed products also enabled the spatial evaluation of model simulations due to their spatial and temporal coverage. However, their usability is not extensively explored in various regions. This study evaluates the effectiveness of incorporating remotely sensed evapotranspiration (RS-ET) and leaf area index (RS-LAI) products to enhance watershed modeling predictions. The objectives include reducing parameter uncertainty at the watershed scale and refining the model's capability to predict the spatial distribution of ET and LAI at sub-watershed scale. Using the Soil and Water Assessment Tool (SWAT) model, a systematic calibration procedure was applied. Initially, solely streamflow data was employed as a constraint, gradually incorporating RS-ET and RS-LAI thereafter. The results showed that while 14 parameter sets exhibit satisfactory performance for streamflow and RS-ET, this number diminishes to six with the inclusion of RS-LAI as an additional constraint. Furthermore, among these six sets, only three effectively captured the spatial patterns of ET and LAI at the sub-watershed level. Our findings showed that leveraging multiple remotely sensed products has the potential to diminish parameter uncertainty and increase the credibility of intra-watershed process simulations. These results contributed to broadening the applicability of remotely sensed products in watershed modeling, enhancing their usefulness in this field.

There is a growing need for systems that can be used to effectively detect and classify intrusions in extensive network data exchanges. To this end, we propose Hi-MLIC, a hierarchical multilayer lightweight intrusion classification model that has been designed to address various intrusion types. This study highlights the challenges involved in classifying intrusions due to data imbalance across different types of intrusion data along with the complex nature of consolidating multiple benchmark datasets into cohesive datasets for real-time detection. To address these issues, we consolidated packet capture data from two widely used benchmark datasets, CIC-IDS2017 and UNSW-NB15, into two newer and more comprehensive datasets, CM-CIC-IDS2017 and CM-UNSW-NB15, respectively. This consolidation enables the identification and classification of a broader range of intrusion types. Our hierarchical approach achieves improved classification accuracy by effectively addressing the class imbalance that is inherent in non-hierarchical models. Layer-1 separates network traffic into benign and malicious categories. Layer-2 further classifies malicious traffic into four groups, while Layer-3 identifies 23 specific intrusion types. We reduced the model complexity and processing time by performing misclassification analysis and eliminating unnecessary features. Our model ultimately achieved a recall metric of up to 98.8%, thus demonstrating its effectiveness and efficiency in intrusion detection and classification. Altogether, the proposed Hi-MLIC represents a significant advancement in addressing the challenges of real-time network intrusion detection.

The importance of a high-quality dataset availability in 3D human action analysis research cannot be overstated. This paper introduces DGU-HAO (Human Action analysis dataset with daily life Objects). This novel 3D human action multi-modality dataset encompasses four distinct data modalities accompanied by annotation data, including motion capture, RGB video, image, and 3D object modeling data. It features 63 action classes involving interactions with 60 common furniture and electronic devices. Each action class comprises approximately 1,000 motion capture data representing 3D skeleton data and corresponding RGB video and 3D object modeling data, resulting in 67,505 motion capture data samples. It offers comprehensive 3D structural information of the human, RGB images and videos, and point cloud data for 60 objects, collected through the participation of 126 subjects to ensure inclusivity and account for diverse human body types. To validate our dataset, we leveraged MMNet, a 3D human action recognition model, achieving Top-1 accuracy of 91.51% and 92.29% using the skeleton joint and bone methods, respectively. Beyond human action recognition, our versatile dataset is valuable for various 3D human action analysis research endeavors.

Abstract We propose a Fabry–Perot cavity (FPC) antenna to suppress a sidelobe level (SLL) while maintaining a reasonably high gain. Generally, conventional FPC antennas (FPCAs) produce a high SLL because waves in their FPC leak considerably through lateral openings, which is a primary reason for lowering antenna gains. We propose two design approaches to solve this problem: the reflection magnitude tapering of a partially reflective surface (PRS) and considering different incident modes for the PRS design. First, the proposed tapering can remarkably reduce an SLL by providing the PRS with more radiation opportunities. Second, the different incident modes of transverse electric (TE) and transverse magnetic (TM) can increase an antenna gain by considering a more realistic illumination environment of the PRS. We have proven that our antenna provides 19.8 dBi realized gain with high sidelobe suppression (SLS) of more than 23 dB. Consequently, the proposed FPCA can suppress sidelobes significantly while maintaining a high gain. Good agreement between simulations and experiments demonstrates the usefulness of our proposal.

Environmental factors, such as climate change and land use changes, affect water quality drastically. To consider these, various predictive models, both process-based and data-driven, have been used. However, each model has distinct limitations. In this study, a hybrid model combining the soil and water assessment tool and the reverse time attention mechanism (SWAT–RETAIN) was proposed for predicting daily streamflow and total phosphorus (TP) load of a watershed. SWAT–RETAIN was applied to Hwangryong River, South Korea. The hybrid model uses the SWAT output as input data for the RETAIN. Spatial, meteorological, and hydrological data were collected to develop the SWAT to generate high temporal resolution data. RETAIN facilitated effective simultaneous prediction. The SWAT–RETAIN exhibited high accuracy in predicting streamflow (Nash–Sutcliffe efficiency (NSE): 0.45, root mean square error (RMSE): 27.74, percent bias (PBIAS): 22.63 for test sets), and TP load (NSE: 0.50, RMSE: 423.93, PBIAS: 22.09 for test sets). This result was evident in the performance evaluation using flow duration and load duration curves. The SWAT–RETAIN provides enhanced temporal resolution and performance, enabling the simultaneous prediction of multiple variables. It can be applied to predict various water quality variables in larger watersheds. HIGHLIGHTS Process-based and data-driven models combined for improved prediction accuracy.; Output of SWAT was used as input data for RETAIN.; SWAT–RETAIN yielded superior predictive power over standalone SWAT.; Trends in observed values were accurately captured.; Applicable to time-series prediction of other water quality variables.;

The color conversion efficiency of phosphor films can be significantly improved by producing them in the shape of photonic crystals (PhCs). When light with photonic band‐edge wavelengths is incident on a PhCs phosphor film, the excitation photons are resonantly absorbed, enhancing the emission intensity. This study develops three‐dimensional PhC phosphor films based on self‐assembled inverse opal structures. PhC phosphors are constructed using a silk fibroin polymer and red organic fluorescent dyes (λpeak ≈ 610 nm) doped into it. The photonic structures are designed using electromagnetic wave simulations and photonic band structure analyses. The fabricated PhC phosphor films are integrated with blue micro‐light‐emitting diode (micro‐LED) chips (λpeak ≈ 452 nm), resulting in a color conversion efficiency increase of more than 1.5 times that of bulk phosphor films. Additionally, experiments are performed using various micro‐LED chips with a size of less than 100 μm. Overall, the results of this study demonstrate the potential of PhC phosphor films in future micro‐LED‐based devices and applications, including displays and communication systems.

Background: Droplet digital polymerase chain reaction (ddPCR) is an exact method of measurement. Objectives: We conducted this study to identify the prognostic factors for successful treatment-free remission in patients with chronic-phase chronic myeloid leukemia who discontinued tyrosine kinase inhibitors (TKIs). We also aimed to validate ddPCR for predicting molecular relapse. Design: This is a prospective, multicenter study. Methods: We enrolled patients treated with TKIs for at least 3 years with a confirmed sustained deep molecular response (DMR) for at least 1 year. TKI was re-administered in patients who experienced the loss of major molecular response (MMR). Results: A total of 66 patients from five institutions in South Korea were enrolled. During a median follow-up period of 16.5 months, 29/66 (43.9%) patients experienced molecular relapse; the probability of molecular relapse-free survival (RFS) at 6 or 12 months after TKI discontinuation was 65.6% or 57.8%, respectively, with most molecular relapses occurring within the first 7 months. All patients who lost MMR were re-treated with TKI, and all re-achieved MMR at a median of 2.8 months. E14a2 transcript type ( p = 0.005) and longer DMR duration (⩾48 months) prior to TKI discontinuation ( p = 0.002) were associated with prolonged molecular RFS and with sustained DMR. Patients with both e13a2 transcript type and detectable BCR::ABL1 (⩾MR 5.0 ) by ddPCR at the time of TKI discontinuation showed shorter duration of molecular RFS ( p = 0.015). Conclusion: Our data suggest that transcript type and BCR::ABL1 transcript levels on ddPCR should be taken into consideration when deciding whether to discontinue TKI therapy.

Abstract Background Capsular contracture is a critical complication of silicone implantation caused by fibrotic tissue formation from excessive foreign body responses. Various approaches have been applied, but targeting the mechanisms of capsule formation has not been completely solved. Myofibroblast differentiation through the transforming growth factor beta (TGF-β)/p-SMADs signaling is one of the key factors for capsular contracture development. In addition, biofilm formation on implants may result chronic inflammation promoting capsular fibrosis formation with subsequent contraction. To date, there have been no approaches targeting multi-facted mechanisms of capsular contracture development. Methods In this study, we developed a multi-targeting nitric oxide (NO) releasing bionanomatrix coating to reduce capsular contracture formation by targeting myofibroblast differentiation, inflammatory responses, and infections. First, we characterized the bionanomatrix coating on silicon implants by conducting rheology test, scanning electron microcsopy analysis, nanoindentation analysis, and NO release kinetics evaluation. In addition, differentiated monocyte adhesion and S. epidermidis biofilm formation on bionanomatrix coated silicone implants were evaluated in vitro. Bionanomatrix coated silicone and uncoated silicone groups were subcutaneously implanted into a mouse model for evaluation of capsular contracture development for a month. Fibrosis formation, capsule thickness, TGF-β/SMAD 2/3 signaling cascade, NO production, and inflammatory cytokine production were evaluated using histology, immunofluorescent imaging analysis, and gene and protein expression assays. Results The bionanomatrix coating maintained a uniform and smooth surface on the silicone even after mechanical stress conditions. In addition, the bionanomatrix coating showed sustained NO release for at least one month and reduction of differentiated monocyte adhesion and S. epidermidis biofilm formation on the silicone implants in vitro. In in vivo implantation studies, the bionanomatrix coated groups demonstrated significant reduction of capsule thickness surrounding the implants. This result was due to a decrease of myofibroblast differentiation and fibrous extracellular matrix production through inhibition of the TGF-β/p-SMADs signaling. Also, the bionanomatrix coated groups reduced gene expression of M1 macrophage markers and promoted M2 macrophage markers which indicated the bionanomatrix could reduce inflammation but promote healing process. Conclusions In conclusion, the bionanomatrix coating significantly reduced capsular contracture formation and promoted healing process on silicone implants by reducing myfibroblast differentiation, fibrotic tissue formation, and inflammation. Graphical Abstract A multi-targeting nitric oxide releasing bionanomatrix coating for silicone implant can reduce capsular contracture and improve healing process. The bionanomatrix coating reduces capsule thickness, α-smooth muscle actin and collagen synthesis, and myofibroblast differentiation through inhibition of TGF-β/SMADs signaling cascades in the subcutaneous mouse models for a month.

Abstract Background To understand the molecular mechanisms involved in regulation of DNA methyltransferases (DNMTs) by metformin in non-small cell lung cancer (NSCLC) cells. Methods Expression levels of DNMTs in response to metformin were analyzed in NSCLC cells. MicroRNAs regulating expression of DNMTs at the post-transcriptional level were searched using miRNA-target databases (miRDB and miRTarBase), TCGA RNASeqV2 lung cancer data, and miRNA-seq. Results Metformin dose-dependently downregulated expression of DNMT1 and DNMT3a at the post-transcriptional level and expression of DNMT3b at the transcriptional level in A549 lung cancer cells. Activity of DNMTs was reduced by about 2.6-fold in A549 cells treated with 10 mM metformin for 72 h. miR-148/-152 family members (miR-148a, miR-148b, and miR-152) targeting the 3′UTR of DNMTs were associated with post-transcriptional regulation of DNMTs by metformin. Metformin upregulated expression of miR-148a, miR-148b, and miR-152 in A549 and H1650 cells. Transfection with an miR-148b plasmid or a mimic suppressed expression of DNMT1 and DNMT3b in A549 cells. Transfection with the miR-148a mimic in A549 and H1650 cells decreased the luciferase activity of DNMT1 3′UTR. A combination of metformin and cisplatin synergistically increased expression levels of miR-148/-152 family members but decreased expression of DNMTs in A549 cells. Low expression of miR-148b was associated with poor overall survival (HR = 2.56, 95% CI 1.09—6.47; P = 0.04) but not with recurrence-free survival. Conclusions The present study suggests that metformin inhibits expression of DNMTs by upregulating miR-148/-152 family members in NSCLC cells.

Symmetry breaking charge separations have been found to be important for charge transfer in bacteriochlorophyll pairs in photosynthetic reaction centers, but engineering symmetry breaking charge separations in artificial dimers of related chromophores is challenging. Here, the authors report the design and synthesis of aromatic-bridged as well as meso-meso-linked BF2-smaragdyrin dimers that exhibit symmetry-breaking charge transfer properties.

Objectives This study aims to assess the applicability of the SWAT-C water quality model recently developed to predict in-stream Total Organic Carbon (TOC) in a watershed within South Korea. Methods The SWAT-C model was tested in the Hwangryong River Watershed. SWAT-C is an advanced version of Soil and Water Assessment Tool (SWAT) to simulate carbon cycling at the watershed scale. The model was simulated for 11 years (2010-2020) consisting of 2-year warm-up (2010-2011), 6-year calibration (2012-2017), and 3-year validation (2018-2020) periods. SWAT-C was calibrated and validated against monthly streamflow and TOC loads. The model performance was evaluated using NSE (Nash-Sutcliffe efficiency), KGE (Kling-Gupta efficiency), and PBIAS (percent bias) Simulated Dissolve Organic Carbon (DOC) and Particulate Organic Carbon (POC) loads were also presented to see the major caron type loaded to the downstream. Results and Discussion The calibration results showed that SWAT-C could depict streamflow and TOC loads with acceptance model performances (NSE > 0.5, KGE > 0.5 and PBIAS =< 25%). Especially, the seasonal variations of TOC loads were well simulated by SWAT-C. The TOC load was predicted to increase in the summer season with high precipitation and slightly lower in the other seasons. This seasonal pattern is likely caused by frequent heavy rainfall events in summer. Conclusion This study demonstrated that SWAT-C model is applicable in South Korea with sufficient prediction accuracy. Thus, SWAT-C would serve as an efficient tool to monitor TOC loads in South Korea.

Understanding structure-property relationship of dye arrays is of great importance for designing organic photonic and photovoltaic materials. Here, authors present a slip-stacked perylene bisimide array as a model system to investigate singlet fission mechanisms by depending upon interchromophoric interaction.

Herein, we present a new method for the calculation of the specific absorption rate (SAR) of rats (named time-weighted SAR) to practically consider the effect of the ever-changing movements of rats on their SARs. First, nine rats in separate cages were recorded for approximately 22 h, and the footage every 1 min was collected to obtain 1,307 still shots per rat. Next, five representative postures, which were classified according to the similarity of the still shots, were selected. Subsequently, the percentage of each posture was calculated by computing the number of still shots classified into the corresponding representative postures. Lastly, we demonstrated that although each rat exhibited relatively different and diverse movements during the observation period, the application of this percentage to the SARs of each posture resulted in very similar SAR levels among the rats. This indicates that the time-weighted SAR can be a suitable parameter for accounting for various behavior patterns of rats, as it can measure the total amount of real RF exposure more precisely and practically.

Humans can recognize or infer unseen classes of objects using descriptions explaining the characteristics (semantic information) of the classes. However, conventional deep learning models trained in a supervised manner cannot classify classes that were unseen during training. Hence, many studies have been conducted into generalized zero-shot learning (GZSL), which aims to produce system which can recognize both seen and unseen classes, by transferring learned knowledge from seen to unseen classes. Since seen and unseen classes share a common semantic space, extracting appropriate semantic information from images is essential for GZSL. In addition to semantic-related information (attributes), images also contain semantic-unrelated information (contents), which can degrade the classification performance of the model. Therefore, we propose a content-attribute disentanglement architecture which separates the content and attribute information of images. The proposed method is comprised of three major components: 1) a feature generation module for synthesizing unseen visual features; 2) a content-attribute disentanglement module for discriminating content and attribute codes from images; and 3) an attribute comparator module for measuring the compatibility between the attribute codes and the class prototypes which act as the ground truth. With extensive experiments, we show that our method achieves state-of-the-art and competitive results on four benchmark datasets in GZSL. Our method also outperforms the existing zero-shot learning methods in all of the datasets. Moreover, our method has the best accuracy as well in a zero-shot retrieval task. Our code is available at https://github.com/anyoojin1996/CA-GZSL.

Composite development indices show an exponential movement of major economic indicators to identify and predict the overall trend of the national economy. However, the existing method of writing composite development indices is based on simple statistical methods using macroscopic data. Therefore, it presents limitations when grasping regional economic trends late. It is because the time of announcement of composite development indices is concentrated at the end of each month, quarter, and year. This study used the floating population estimated from smartphone data that can be collected in real-time to analyze how floating population patterns affect regional economic situations to compensate for these limitations. The primary purpose was to present a prompt development prediction methodology that reflects this meaningful relationship. A correlation and cross-correlation analysis was performed to exhibit a clear relationship between composite development indices and floating population value. In addition, a time series model and a multiple regression model analyses were applied to predict regional development indices. The results obtained facilitated the prompt selection of regional composite indices after choosing a model that exhibits high prediction accuracy and efficiency of the application. The selected regional development composite indices are expected to be used as a faster and more reliable prediction criterion than the existing development composite indices used to predict a specific city’s economic situation.

The proposed design approach improves the circularly polarized Fabry-Perot cavity antenna (CP-FPCA) by increasing gain and sidelobe suppression (SLS) while reducing the axial ratio (AR) and cross-polarization levels. Conventional CP-FPC antennas have a high AR due to the lack of independent control over circular polarization conditions. The solution proposes a double-layered circularly polarized partially reflecting surface (CP-PRS) that independently controls the circular polarization conditions at the design frequency f0 (10 GHz) for equal magnitudes and at a ±90° phase difference between orthogonal components of the transmitted waves. The PRS and artificial magnetic conductor (AMC) unit cells are employed to satisfy Trentini’s beamforming condition, leading to increased gain and SLS and lowered AR and cross-polarization levels. Consequently, the proposed CP-FPCA provides a 15.4 dBi high gain with 25.3% aperture efficiency and more than 23.5 dB high SLS in each plane. Moreover, it achieves an AR lowered by 0.12 dB and a cross-polarization level below −42 dB. A strong correlation between the simulations and experiments proves the practicality of our proposal.

Abstract A family of tunable halochromic switches is developed using a naphthalimide‐fused dipyrrin as the core π‐conjugated motif. Electronic properties of these dipyrrins are tuned by substitution of their alpha and meso positions with aryl groups of variable donor–acceptor strength. The first protonation results in a conformational change that enhances electronic coupling between the dipyrrin chromophore and the meso substituent, leading to halochromic effects that occasionally exceed 200 nm and switch the absorption between the near‐infrared (NIR)‐I and NIR‐II ranges. A NIR‐II photothermal effect, switchable by acid–base chemistry is demonstrated for selected dipyrrins. Further protonation is possible for derivatives bearing additional amino groups, leading to up to four halochromic switching step. The most electron‐rich dipyrrins are also susceptible to chemical oxidation, yielding NIR‐absorbing radical cations and closed‐shell dications.

Summary: To approach the theoretical efficiency of perovskite solar cells (PSCs), the defects in perovskites should be managed. Among different types of defects, halide vacancies easily form on the surface of perovskite grains (PGs), hindering perovskite stability and the charge-transport process by trapping charge carriers. In this work, oxidized black phosphorus quantum dots (O-BPQDs) are incorporated into a perovskite to resolve these issues. Oxygen atoms of the O-BPQDs interact with uncoordinated Pb (halide vacancies), forming grain interconnections. These interactions reduce halide vacancies and suppress the overall recombination kinetics. Along with defect reduction, the O-BPQDs offer an efficient charge-transport channel across individual PGs. We achieve a best power-conversion efficiency (PCE) of 22.34% for SnO2-based PSCs and of 23.1% for TiO2-based PSCs. These PSCs exhibit moisture stability in a relative humidity (RH) 40% environment comparable to 3D/2D perovskites. Our strategy provides practical applicability and versatility for PSCs to approach the theoretical PCE value.

Surface passivation is a critical aspect of preventing surface oxidation and improving the emission properties of nanocrystal quantum dots (QDs). Recent studies have demonstrated the critical role of surface ligands in determining the performance of QD-based light-emitting diodes (QD-LEDs). Herein, the underlying mechanism by which the capping ligands of InP/ZnSe/ZnS QDs influence the brightness and lifetime of the QD-LEDs is investigated. The electrochemical results demonstrate that highly luminescent InP/ZnSe/ZnS QDs exhibit modulated charge injection depending on the length of the surface ligand chains: short alkyl chains on the ligands are favorable for charge transport to the QDs. In addition, the correlation between the spectroscopic and XRD analyses suggests that the length of the ligand chain tunes the ligand–ligand coupling strength, thereby controlling the inter-QD energy transfer dynamics. The present findings shed new light on the crucial role of surface ligands for InP/ZnSe/ZnS QD-LED applications.

Although research on schema has been widely investigated for the past decades, little research has addressed the development of a systematic instructional design theory using schema principles and processes. This study proposes a systematic schema-based instructional design model, including general and schema analysis, schema-based design, and development processes and techniques for evaluating a learner’s acquired schema. By synthesizing empirical studies, this study comprehensively reviews literature on schema and foundational principles for learning. The goal of the study is to enrich the knowledge base of schema-based instructional design for different learning environments. Thus, the study is concluded by a discussion on how to utilize a schema-based instructional design for self-paced learning environments with additional implications and further recommendations.

This study examined the effects of an integrated approach that combines segmentation and self-explanation designs on learner achievement for meaningful video-based learning. This was a pretest-posttest research design with a sample size of 121 participants randomly assigned to one of four different types of video instructions (continuous, segmentation, self-explanation, or the combination of segmentation and self-explanation). Participants engaged in video instruction that used either a continuous video or segmented video clips and incorporated either self-explanation prompts or no self-explanation prompts. The results showed that participants in the combination and segmentation conditions outperformed those in the continuous condition in evaluation ability, and participants in the combination condition outperformed those in the continuous condition in the overall performance after controlling for prior knowledge. The current study indicates that the combined design can effectively facilitate student learning by engaging them in meaningful video-based learning.

Background: While the effectiveness of tutoring-style videos has been reported in previous studies conducted in laboratories, how these types of videos facilitate students' learning experiences and achievement has not been much explored in prior studies, which prevents discussion on how to design such tutoring-style videos. Objectives: In this study, we addressed the limitations reported in studies conducted in authentic classes and attempted to explore students' learning patterns and experiences with tutoring-style videos involving interactions between the instructor and agents. In addition, we attempted to reveal what instructional strategies can be used in tutoring-style videos to enhance students' engagement and achievement. Methods: The study took place in an undergraduate introductory biology class offered at a university located in the Midwest of the United States. The same instructor taught two sections of this course which lasted for 15 weeks during a Spring semester. The two sections were randomly assigned to an experimental group in which participants watched tutoring-style videos and a control group with participants watching traditional videos. The experiment was administered in a module lasting two and a half weeks focused on microbiology. Surveys and tests were conducted to determine whether the tutoring-style videos had a positive impact on student engagement and achievement. In addition, a video content analysis was carried out to elicit insights on how to design effective tutoring-style videos. Results: For students' emotional engagement and perceived usefulness, no significant difference was found between the two groups, even though the descriptive statistics indicated slightly higher scores from the experimental group than the control group on both subscales. In terms of achievement, the participants reported significantly more learned concepts from watching rich-interactions in the tutoring-style videos than the participants in the control group; and they also reported a significantly smaller number of learned concepts from watching one-interactions in the videos than the control group participants. We also found that instruction in the tutoring-style videos used effective strategies for facilitating students' participation and cognitive processing. Conclusions: Our findings indicate that tutoring-style videos can be effective learning materials by allowing students to engage in interactions between instructors and agents in the videos. The more instructional strategies used to facilitate the interactions between the instructor and the agents, the higher engagement can be expected from viewers. Our study would inform the design and development of effective tutoring-style videos.

Many legacy information systems are currently being clouded. This is due to the advantage of being able to respond flexibly to the changes in user needs and system environment while reducing the initial investment cost of IT infrastructure such as servers and storage. The infrastructure of the information system migrated to the cloud is being integrated through the API connections, while being subdivided by using MSA (Micro Service Architecture) internally. DBMS (Database Management System) is also becoming larger after cloud migration. Scale calculation in most layers of the application architecture can be measured and calculated from auto-scaling perspective, but the method of hardware scale calculation for DBMS has not been established as standardized methodology. If there is an error in hardware scale calculation of DBMS, problems such as poor performance of the information system or excessive auto-scaling may occur. In addition, evaluating hardware size is more crucial because it also affects the financial cost of the migration. CPU is the factor that has the greatest influence on hardware scale calculation of DBMS. Therefore, this paper aims to calculate the conversion factor for CPU scale calculation that will facilitate the cloud migration between heterogeneous DBMS. In order to do that, we utilize the concept and definition of hardware capacity planning and scale calculation in the on-premise information system. The methods to calculate the conversion factor using TPC-H tests are proposed and verified. In the future, further research and testing should be conducted on the size of the segmented CPU and more heterogeneous DBMS to demonstrate the effectiveness of the proposed test model. [ABSTRACT FROM AUTHOR]

Neurotropic alphaherpesviruses, including herpes simplex virus type 1 (HSV-1), recruit microtubule motor proteins to invade cells. The incoming viral particle traffics to nuclei in a two-step process. First, the particle uses the dynein-dynactin motor to sustain transport to the centrosome. In neurons, this step is responsible for long-distance retrograde axonal transport and is an important component of the neuroinvasive property shared by these viruses. Second, a kinesin-dependent mechanism redirects the particle from the centrosome to the nucleus. We have reported that the kinesin motor used during the second step of invasion is assimilated into nascent virions during the previous round of infection. Here, we report that the HSV-1 pUL37 tegument protein suppresses the assimilated kinesin-1 motor during retrograde axonal transport. Region 2 (R2) of pUL37 was required for suppression and functioned independently of the autoinhibitory mechanism native to kinesin-1. Furthermore, the motor domain and proximal coiled coil of kinesin-1 were sufficient for HSV-1 assimilation, pUL37 suppression, and nuclear trafficking. pUL37 localized to the centrosome, the site of assimilated kinesin-1 activation during infection, when expressed in cells in the absence of other viral proteins; however, pUL37 did not suppress kinesin-1 in this context. These results indicate that the pUL37 tegument protein spatially and temporally regulates kinesin-1 via the amino-terminal motor region in the context of the incoming viral particle. [ABSTRACT FROM AUTHOR]