Search

Purpose: To retrospectively determine the cumulative survival rate (CSR) and marginal bone level change (ΔMBL) around novel hybrid design tissue-level (TL) dental implants that support multiple-screw-retained restorations. Materials and Methods: Implant CSRs were analyzed at the implant and patient level using Kaplan-Meier estimates. ΔMBL was measured by comparing the periapical loading and follow-up visit radiographs using an improved standardized digital methodology based on image gray levels. ΔMBL outcomes were subject to linear mixed regression to identify potential risk factors. Results: A total of 301 TL implants in 69 patients with an average age of 62.6 ± 11.7 years (range: 36 to 87 years) at the time of implant placement were considered for the analysis. All 301 implants were successfully restored and loaded. The 54-month CSRs at the implant and patient levels were 98.9% (95% CI: 96.7 to 99.6) and 95.3% (95% CI: 86.1 to 98.5), respectively. ΔMBL after a mean follow-up of 22 ± 10.7 months after loading was 0.00 ± 0.57 mm. None of the implant sites showed marginal bone loss exceeding 1.5 mm. Multivariate regression analysis revealed a significant association between ΔMBL and the loading protocol (P = .027) but not between ΔMBL and age or transgingival height. Conclusions: The high CSRs and stable peri-implant marginal bone levels support the use of recent TL implants, which have a hybrid design inherited from the bone-level implant-abutment connection, as a suitable treatment option for restoring partially or fully edentulous patients with a good mid-term prognosis. These results should be complemented by further prospective studies in a real-world multicenter private practice setup that represents the daily realities of implant treatment. [ABSTRACT FROM AUTHOR]

This study presents a hybrid (Bayesian‐frequentist) approach to sample size re‐estimation (SSRE) for cluster randomised trials with continuous outcome data, allowing for uncertainty in the intra‐cluster correlation (ICC). In the hybrid framework, pre‐trial knowledge about the ICC is captured by placing a Truncated Normal prior on it, which is then updated at an interim analysis using the study data, and used in expected power control. On average, both the hybrid and frequentist approaches mitigate against the implications of misspecifying the ICC at the trial's design stage. In addition, both frameworks lead to SSRE designs with approximate control of the type I error‐rate at the desired level. It is clearly demonstrated how the hybrid approach is able to reduce the high variability in the re‐estimated sample size observed within the frequentist framework, based on the informativeness of the prior. However, misspecification of a highly informative prior can cause significant power loss. In conclusion, a hybrid approach could offer advantages to cluster randomised trials using SSRE. Specifically, when there is available data or expert opinion to help guide the choice of prior for the ICC, the hybrid approach can reduce the variance of the re‐estimated required sample size compared to a frequentist approach. As SSRE is unlikely to be employed when there is substantial amounts of such data available (ie, when a constructed prior is highly informative), the greatest utility of a hybrid approach to SSRE likely lies when there is low‐quality evidence available to guide the choice of prior. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Design Methods Results Conclusion Implications Impact Patient or Public Contribution To implement strategies to improve the care of patients with acute pain in the emergency department (ED).Pre–post implementation study using a Type 2 hybrid effectiveness–implementation design.Implementation strategies were introduced and monitored through the Ottawa Model of Research Uses' assessment, monitoring and evaluation cycles, supported by focused and sustained facilitation.Improvements in time‐to‐analgesia within 30 min (21%–27%), administration of nurse‐initiated analgesia (NIA) (17%–27%) and measurement of pain (65%–75%) were achieved post‐implementation. NIA was the strongest predictor of receiving analgesia within 30 min. Adoption of pain interventions into practice was not immediate yet responded to sustained facilitation of implementation strategies.Collaboration with local clinicians to introduce simple interventions that did not disrupt workflow or substantially add to workload were effective in improving analgesia administration rates, and the proportion of patients receiving analgesia within 30 min. The assessment, monitoring and evaluation cycles enabled agile and responsive facilitation of implementation activities within the dynamic ED environment. Improvements took time to embed into practice, trending upward over the course of the implementation period, supporting the sustained facilitation approach throughout the study.Sustained adoption of evidence‐based pain interventions into the care of people presenting to the ED with acute pain can be achieved through sustained facilitation of implementation. NIA should be at the centre of acute pain management in the ED.This study addressed the lingering gap between evidence and practice for patients with acute pain in the ED. Implementation of locally relevant/informed implementation strategies supported by focused and sustained facilitation improved the care of patients with acute pain in the ED. This research will have an impact on people presenting to EDs with acute pain, and on clinicians treating people with acute pain in the ED. Relevant equator guidelines were followed and the StaRI reporting method used.No Patient or Public Contribution in this study. [ABSTRACT FROM AUTHOR]

The implementation of school-based obesity-prevention programs is understudied. Kids SIP smart ER is a 6-month, school-based, behavioral intervention for Appalachian middle school students and includes a teacher implementation strategy. Kids SIP smart ER effectively reduced students' sugar-sweetened beverages (SSB) when Researcher-Led. However, Teacher-Led effectiveness and fidelity are unknown. To explore the relative SSB effects when Kids SIP smart ER was Researcher-Led versus Teacher-Led and to examine teacher fidelity. This study of secondary outcomes used a quasi-experimental analytic approach of a Hybrid Type 1 effectiveness–implementation and cluster randomized controlled tria (RCT) of Kids SIP smart ER. Student SSB behaviors and teacher self-rated fidelity were assessed, respectively, with the validated Beverage Intake Questionnaire (BEVQ-15) and lesson-specific checklists. Analyses included descriptive statistics and modified two-part models with time-fixed effects and school-year cohort cluster controls. The analytic sample included students from six control schools (n = 220), six Researcher-Led intervention schools (n = 306), and five Teacher-Led intervention schools (n = 218), as well as eight teachers. Teacher-Led intervention students decreased SSB by −14.3 ounces/day (95% confidence interval = −15.4, −13.2; P <.001). Relative to control and to Researcher-Led intervention, the Teacher-Led treatment effect among students was −11.6 ounces SSB/day (P <.001, effect size = 0.75) and −4.3 (P =.004, effect size = 0.25), respectively. Teachers returned fidelity checklists for 90% of planned lessons. Fidelity averaged 94% (SD = 4.0%) among returned forms and 85% (SD = 18.9%) when missing forms were counted as zeros. Teachers can implement Kids SIP smart ER with high fidelity and produce statistically and clinically meaningful improvements in students' SSB behaviors. Findings have implications for the sustained implementation of Kids SIP smart ER and other school-based obesity-prevention programs. Clinical Trial information : NCT03740113. [ABSTRACT FROM AUTHOR]

High-strength steels (HSSs) have been gaining increasing attention in recent years because of their potential application for lightweight structures. Hybrid structural steel I-sections, featured by dissimilar strength grades for constitutive plates, provide a more economical solution to suit bending loading scenario. This study conducted experiments on nine I-sections with Q690 flange plates under four-point loads, incorporating three different web strength grades including Q690, Q460, and Q355. Furthermore, the local buckling behavior of representative I-sections with various section geometries was analyzed using a validated numerical method to understand the role of web strength grade. Test and numerical analysis results revealed that the section with web steel in the strain hardening stage exhibited different levels of ductility among specimens with different strength webs. It was also observed that earlier yielding or inelastic buckling of the lower strength web plate in hybrid I-sections affects the local buckling behavior of I-girders, in terms of moment resistance and rotation capacity. In addition, the initial local imperfection mode used in numerical analysis was found to affect the rotation capacity of I-girders, but the effect of web strength grade remains consistent among I-sections with the same local buckling deformation mode. This study provides further insights into the local buckling behavior of hybrid I-sections subjected to uniform bending, laying the foundation for further development of design methods. [ABSTRACT FROM AUTHOR]

In this article, interrelated models appropriate for conceptualizing a mixed research design within a hybrid design are presented. Initially, the discussion centers on outlining the core principles defining community-based participatory research and characteristics defining mixed research. The design model presents selective examples of mixed research elements to be considered when the researcher is strategizing the design. The integration model details the language of integration and the role of legitimation as it relates to integration. The integrity model presents selective quality criteria designed to elevate credibility of the conclusions. The contribution of this article lies in its focus on mixed research design within the hybrid design, and the presentation of interrelated models, namely, design, integration, and integrity models that address this focus. [ABSTRACT FROM AUTHOR]

Aim Methods Results Conclusions Cognitive impairments are a core feature of first‐episode psychosis (FEP) and one of the strongest predictors of long‐term psychosocial functioning. Cognition should be assessed and treated as part of routine clinical care for FEP. Cognitive screening offers the opportunity to rapidly identify and triage those in most need of cognitive support. However, there are currently no validated screening measures for young people with FEP. CogScreen is a hybrid effectiveness‐implementation study which aims to evaluate the classification accuracy (relative to a neuropsychological assessment as a reference standard), test–retest reliability and acceptability of two cognitive screening tools in young people with FEP.Participants will be 350 young people (aged 12–25) attending primary and specialist FEP treatment centres in three large metropolitan cities (Adelaide, Sydney, and Melbourne) in Australia. All participants will complete a cross‐sectional assessment over two sessions including two cognitive screening tools (Screen for Cognitive Impairment in Psychiatry and Montreal Cognitive Assessment), a comprehensive neuropsychological assessment battery, psychiatric and neurodevelopmental assessments, and other supplementary clinical measures. To determine the test–retest reliability of the cognitive screening tools, a subset of 120 participants will repeat the screening measures two weeks later.The protocol, rationale, and hypotheses for CogScreen are presented.CogScreen will provide empirical evidence for the validity and reliability of two cognitive screening tools when compared to a comprehensive neuropsychological assessment. The screening measures may later be incorporated into clinical practice to assist with rapid identification and treatment of cognitive deficits commonly experienced by young people with FEP. [ABSTRACT FROM AUTHOR]

In this paper, a novel high-speed and energy-efficient 4–2 compressor cell is proposed using carbon nanotube field-effect transistors. The proposed compressor is realized efficiently based on NAND–NOR gates and multiplexers. To estimate the performance of the presented design, simulations are carried out using Synopsis HSPICE under different conditions. The results demonstrate the improvement of the proposed design compared to the best reference designs in terms of delay and energy consumption, by 20–26%, respectively. Also, the susceptibility of the proposed design against the process, voltage, temperature (PVT), and noise variations is examined. It is robust against PVT variations and high amplitude of noises compared with its counterpart. Further, embedding the proposed compressor in an 8 × 8-bit binary multiplier demonstrates that it has better speed and energy consumption with regard to its counterparts. [ABSTRACT FROM AUTHOR]

Text messaging interventions are increasingly used to help people manage depression and anxiety. However, little is known about the effectiveness and implementation of these interventions among U.S. Latinxs, who often face barriers to using mental health tools. The StayWell at Home (StayWell) intervention, a 60-day text messaging program based on cognitive behavioral therapy (CBT), was developed to help adults cope with depressive and anxiety symptoms during the COVID-19 pandemic. StayWell users (n = 398) received daily mood inquiries and automated skills-based text messages delivering CBT-informed coping strategies from an investigator-generated message bank. We conduct a Hybrid Type 1 mixed-methods study to compare the effectiveness and implementation of StayWell for Latinx and Non-Latinx White (NLW) adults using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. Effectiveness was measured using the PHQ-8 depression and GAD-7 anxiety scales, assessed before starting and after completing StayWell. Guided by RE-AIM, we conducted a thematic text analysis of responses to an open-ended question about user experiences to help contextualize quantitative findings. Approximately 65.8% (n = 262) of StayWell users completed pre-and-post surveys. On average, depressive (-1.48, p = 0.001) and anxiety (-1.38, p = 0.001) symptoms decreased from pre-to-post StayWell. Compared to NLW users (n = 192), Latinx users (n = 70) reported an additional -1.45 point (p

Background: Traditional dose selection for oncology registration trials typically employs a one- or two-step single maximum tolerated dose (MTD) approach. However, this approach may not be appropriate for molecularly targeted therapy, which tends to have toxicity profiles that are markedly different than cytotoxic agents. The US Food and Drug Administration launched Project Optimus to reform dose optimization in oncology drug development and has recently released a related guidance for industry. Methods: We propose a “three steps toward dose optimization” procedure, in response to these initiatives, and discuss the details in dose-optimization designs and analyses. The first step is dose escalation to identify the MTD or maximum administered dose with an efficient hybrid design, which can offer good overdose control and increases the likelihood of the recommended MTD being close to the true MTD. The second step is the selection of appropriate recommended doses for expansion (RDEs), based on all available data, including emerging safety, pharmacokinetics, pharmacodynamics, and other biomarker information. The third step is dose optimization, which uses data from a randomized fractional factorial design with multiple RDEs explored in multiple tumor cohorts during the expansion phase to ensure a feasible dose is selected for registration trials, and that the tumor type most sensitive to the investigative treatment is identified. Conclusion: We believe using this three-step approach can increase the likelihood of selecting an optimal dose for a registration trial that demonstrates a balanced safety profile while retaining much of the efficacy observed at the MTD.

Though previously unacknowledged, a SMART (Sequential Multiple Assignment Randomized Trial) design uses both regression discontinuity (RD) and randomized controlled trial (RCT) designs. This combination structure creates a conceptual symbiosis between the two designs that enables both RCT- and previously unrecognized, RD-based inferential claims. In Phase 1, based on a quantitative cut-point, a SMART design yields successful or unsuccessful participants after the initial RCT. In Phase 2, interventions are randomly assigned to successful and unsuccessful, Phase 1 subgroups, thereby yielding both RCT and RD results. Like RCT-based inferences, many but not all newly recognized, RD-based SMART inferences are potentially unbiased. In particular, comparisons between RCT and RD outcomes are potentially problematic. Principles from the within-study comparison literature are used to inform SMART-based research, thereby introducing otherwise ignored inferential and procedural possibilities. Awareness of RD designs embedded within SMARTs encourages previously unrecognized inferential claims, though potential internal validity threats and limitations must be carefully weighed. Finally, new, SMART-like sequences of quasi-experiments and experiments can be tested and embedded logic applied. [ABSTRACT FROM AUTHOR]

Background and Objectives Adult day services (ADS) provide quality-of-life benefits to people with dementia, but few provide systematic caregiver support. We report outcomes of a multisite, national trial testing a staff-delivered caregiver program, ADS Plus. Research Design and Methods Cluster-randomized trial involving 34 ADS: 18 sites provided ADS (controls) and 16 provided ADS and ADS Plus (intervention). Trained staff met with caregivers to provide dementia education, support/validation, referrals/linkages, and strategies for care challenges and self-care over 12 months. Main outcomes included depressive symptoms (Center for Epidemiological Studies Depression Scale [CES-D]) and well-being at 6 and 12 months, and client attendance over 12 months. Results Of 203 caregivers (Intervention = 102; Control = 101), 5.9% at 3 months, 12.8% at 6 months, and 22.7% at 12 months were lost to follow-up. Caregivers were predominantly female (80.3%), with 76.4% identifying as White/Caucasian, 14.8% Black/African American, and 12.3% Hispanic/Latino. Most (88.2%) had ≥college education and were 65.0 years old (SD  = 13.46). For those with 6-month data, 40.4% control and 40.2% ADS Plus caregivers had depressed symptoms (≥16 CES-D) at baseline. By 6 months, 43.6% control versus 34.2% ADS Plus caregivers had ≥16 scores (odds ratio = 0.38, p  = .072). By 12 months, after covariate adjustments, ADS Plus caregivers reported reduced total depression scores versus controls (p  = .013) and lower depressed affect scores (p  = .015). Of 18 sites providing 12-month client attendance data, 9 intervention sites reported 126.05 days attended versus 78.49 days for 9 control sites (p  = .079). Discussion and Implications Compared with ADS alone, by 12 months, ADS Plus improved caregiver mood and increased ADS utilization by 60.6%. Results support ADS staff delivering evidence-based caregiver support to enhance ADS benefits. Clinical Trial Registration NCT02927821 [ABSTRACT FROM AUTHOR]

Ternary logic has an advantage over conventional binary logic since it uses less power and promises to take up less space on chips and in interconnects. When ternary logic is used to design multiplier circuits, they exhibit good efficiency. A device known as a carbon nanotube field-effect transistor (CNTFET) offers more benefits than a MOSFET, including low off-current characteristics like low power and good performance. In this paper, a new 1-trit multiplier design is suggested along with a comparison of four 1-trit multiplier ideas based on CNTFETs. Power, latency, PDP, and the number of transistors is compared. Power, speed, and PDP are all improved by the suggested 1-trit multiplier. There are fewer transistors required. The Cadence Virtuoso Tool simulates each of these circuits using CNTFET 32 nm technology. [ABSTRACT FROM AUTHOR]

In recent years deep learning (DL) models have obtained great success in hyperspectral image classification (HSIC) with commendable performance and especially convolutional neural networks (CNNs) have attracted huge attention due to the exceptional performance demonstrated in this area. However, most of the CNN-based models have to suffer with low classification performance due to non-availability of abundant training samples. Recently, hybrid-CNN models, utilizing both spectral and spatial features unitedly, have exhibited remarkable classification accuracy. Yet, the hybrid-CNN models have been adopted in very limited research works due to a very high computational complexity. Furthermore, huge dimensional HSIs contain highly correlated but irrelevant bands. The selection of most relevant spectral bands affects the performance and computational complexity of HSIC models very profoundly. To address these issues, the authors have proposed a binary grey wolf optimization-based hybrid CNN (BGWOHCNN) framework for HSIC, in this paper. In the hybrid framework, a 3-D CNN has been employed to exploit spatial and spectral features jointly along with a 2-D CNN utilizing the spatial features and reducing the computational complexity of the overall design. In addition, binary grey wolf optimization (BGWO) technique has been adapted to select the most relevant spectral bands for HSIC. As per the best of authors' knowledge and belief, the BGWO technique has been investigated for the first time with hybrid CNN for HSIC in the current work. Further, the experiments are conducted to investigate the performance and superiority of the proposed framework over three very popular datasets viz. Salinas, Indian Pines and Pavia University. The obtained results are compared with the six state-of-art DL models, in terms of average accuracy, overall accuracy and Cohen's kappa coefficient, to show that the proposed framework provides very promising results to HSIC tasks. [ABSTRACT FROM AUTHOR]

As the roles of historical trials and real‐world evidence in drug development have substantially increased, several approaches have been proposed to leverage external data and improve the design of clinical trials. While most of these approaches focus on methodology development for borrowing information during the analysis stage, there is a risk of inadequate or absent enrollment of concurrent control due to misspecification of heterogeneity from external data, which can result in unreliable estimates of treatment effect. In this study, we introduce a Bayesian hybrid design with flexible sample size adaptation (BEATS) that allows for adaptive borrowing of external data based on the level of heterogeneity to augment the control arm during both the design and interim analysis stages. Moreover, BEATS extends the Bayesian semiparametric meta‐analytic predictive prior (BaSe‐MAP) to incorporate time‐to‐event endpoints, enabling optimal borrowing performance. Initially, BEATS calibrates the expected sample size and initial randomization ratio based on heterogeneity among the external data. During the interim analysis, flexible sample size adaptation is performed to address conflicts between the concurrent and historical control, while also conducting futility analysis. At the final analysis, estimation is provided by incorporating the calibrated amount of external data. Therefore, our proposed design allows for an approximation of an ideal randomized controlled trial with an equal randomization ratio while controlling the size of the concurrent control to benefit patients and accelerate drug development. BEATS also offers optimal power and robust estimation through flexible sample size adaptation when conflicts arise between the concurrent control and external data. [ABSTRACT FROM AUTHOR]

Lattices were lightweight load-bearing and energy absorption structures, while the traditional designs with a periodic arrangement of single-type cells restricted the design domains. In this work, novel two-phase hybrid strategies based on different types and numbers of thin-plate cubic cells were proposed, and quasi-static compression experiments and finite element numerical simulations were performed to investigate their energy absorption characteristics and deformation mechanisms. The effects of the relative density and load direction on the compression responses were also explored. The results showed that SC-BCC lattices exhibited higher specific energy absorption than conventional lattices and other practical metamaterials, and changing the number and arrangement of cells of the hybrid structures achieved better mechanical properties in a specific loading direction. The specific energy absorption capacity of the hybrid plate-lattice can be up to 4.30 J/g in the present work, which is higher than the SEA capacity of conventional aluminum lattice and TPU truss lattice structure. These findings provided a novel structural design strategy for fabricating the plate-lattice architectures in conjunction with additive manufacturing. [ABSTRACT FROM AUTHOR]

Continuously increasing applications of robot technologies in unstructured environments put higher requirements on the robotic grippers' performance, such as interaction capability, output force range, and controllability. However, currently, it is hard for either rigid or soft grippers to meet these requirements, as single soft or rigid structures alone are difficult to effectively overcome/alleviate their inherent defects, e.g., low compliance of rigid structures and low output force of soft structures. To deal with these difficulties, soft-rigid coupling grippers, or hybrid grippers are proposed. Technically, the soft-rigid coupling is a promising design that combines soft and rigid structures, in order to exploit their respective advantages, such as the strength of rigid structures and compliance of soft structures, in the same set of the gripper system. For the first time, herein, this paper systematically discusses the collaboration strategies of the existing hybrid robotic grippers, by classifying them as Rigid-active-soft-passive, Rigid-passive-soft-active, and Rigid-active-soft-active. At the same time, we introduce the integrated fabrication methods of hybrid grippers, through which the soft and rigid structures with great stiffness and property differences can be coupled together to construct a stable system. Also, possible performance improvements on soft-rigid coupling design for gripper systems are discussed. [ABSTRACT FROM AUTHOR]

Abstract Background Measurement-Based Care (MBC) is the routine administration of measures, clinicians’ review of the feedback and discussion of the feedback with their clients, and collaborative evaluation of the treatment plan. Although MBC is a promising way to improve outcomes in clinical practice, the implementation of MBC faces many barriers, and its uptake by clinicians is low. The purpose of this study was to investigate whether implementation strategies that were developed with clinicians and aimed at clinicians had an effect on (a) clinicians’ uptake of MBC and (b) clients’ outcomes of MBC. Methods We used an effectiveness-implementation hybrid design based on Grol and Wensing’s implementation framework to assess the impact of clinician-focused implementation strategies on both clinicians’ uptake of MBC and outcomes obtained with MBC for clients in general mental health care. We hereby focused on the first and second parts of MBC, i.e., the administration of measures and use of feedback. Primary outcome measures were questionnaire completion rate and discussion of the feedback with clients. Secondary outcomes were treatment outcome, treatment length, and satisfaction with treatment. Results There was a significant effect of the MBC implementation strategies on questionnaire completion rate (one part of clinicians’ uptake), but no significant effect on the amount of discussion of the feedback (the other part of clinicians’ uptake). Neither was there a significant effect on clients’ outcomes (treatment outcome, treatment length, and satisfaction with treatment). Due to various study limitations, the results should be viewed as exploratory. Conclusions Establishing and sustaining MBC in real-world general mental health care is complex. This study helps to disentangle the effects of MBC implementation strategies on differential clinician uptake, but the effects of MBC implementation strategies on client outcomes need further examination.

Abstract In the present study, a new type of hybrid spillway termed labyrinth-shaft spillway was introduced to improve the discharge capacity and efficiency of the spillway. An advanced computational fluid dynamics (CFD) technique was used to analyze the performance of the labyrinth-shaft spillway. The hydraulic performance of the new model was investigated for different labyrinth geometries with a verified computational model. The analysis results demonstrated that the discharge capacity of the labyrinth-shaft spillway was better when compared to that of the conventional shaft spillways with the same weir heads. The discharge coefficient that reflects the efficiency of the labyrinth-shaft spillway was also much better when compared to the conventional spillway, while the opposite was observed with relatively small nappe heads. Similarly, the comparison with the findings of previous studies on labyrinth weirs in the literature demonstrated that labyrinth-shaft spillways performed better when compared to the conventional labyrinth weirs in-channel flow conditions, especially with high nappe heads. A new formula was also developed in the present study with regression analysis conducted on the collected data to calculate the discharge coefficients of the labyrinth-shaft spillway for H/P > 0.2.

BackgroundApproximately 20% of adults in the United States experience chronic pain. Integrative Medical Group Visit (IMGV) offers an innovative approach to chronic pain management through training in mindfulness, nutrition, and other mind-body techniques combined with peer support. To date, there are no studies on IMGV implementation, despite its promise as a feasible non-pharmacological intervention for chronic pain management. In this study, we assessed the feasibility of implementing IMGV and assessing its effectiveness for chronic pain.MethodsImplementation Mapping was used to develop and evaluate implementation strategies for IMGV. Strategies included disseminating educational materials, conducting ongoing training, and conducting educational meetings. IMGV was delivered by three healthcare providers: an allopathic physician, registered yoga teacher, and naturopathic physician. The effectiveness of IMGV on patient health outcomes was assessed through qualitative interviews and a Patient-Reported Outcomes Scale (PROMIS-29). Provider perspectives of acceptability, appropriateness, and feasibility were assessed through periodic reflections (group interviews reflecting on the process of implementation) and field notes. Paired t-tests were used to assess changes between scores at baseline and post intervention. Qualitative data were coded by three experienced qualitative researchers using thematic content analysis.ResultsOf the initial 16 patients enrolled in research, 12 completed at least two sessions of the IMGV. Other than fatigue, there was no statistically significant difference between the pre- and post-scores. Patients reported high satisfaction with IMGV, noting the development of new skills for self-care and the supportive community of peers. Themes from patient interviews and periodic reflections included the feasibility of virtual delivery, patient perspectives on acceptability, provider perspectives of feasibility and acceptability, ease of recruitment, complexity of referral and scheduling process, balancing medical check-in with group engagement, and nursing staff availability.ConclusionsIMGV was feasible, acceptable, and effective from the perspectives of patients and providers. Although statistically significant differences were not observed for most PROMIS measures, qualitative results suggested that participants experienced increased social support and increased pain coping skills. Providers found implementation strategies effective, except for engaging nurses, due to staff being overwhelmed from the pandemic. Lessons learned from this pilot study can inform future research on implementation of IMGV.

Switched reluctance machines (SRMs) are potential candidates for use in the propulsion systems of electric vehicles. However, they suffer from low power density and high torque ripple. In this paper, a segmented rotor double-sided axial flux SRM (DSAFSRM) is chosen for detailed analysis. A hybrid design algorithm is proposed to take the effects of iron non-linearity into account. The proposed design procedure benefits from simplicity and high accuracy at the same time. A two-step optimization procedure is presented which minimizes the torque ripple of the DSAFSRM without jeopardizing its efficiency. The torque ripple is reduced from 120% to 35% after optimization. In the two-step optimization procedure, both geometrical and switching related parameters are investigated. Moreover, a double-sided radial flux SRM is designed and compared with the proposed DSAFSRM in terms of torque ripple, average torque, efficiency and power density. The results indicate superior performance of the optimized DSAFSRM, especially in terms of average torque, which is 26% higher than the torque produced by the double-sided radial flux SRM. [ABSTRACT FROM AUTHOR]

The design of rock support in hard rock tunnelling is often assisted by the use of empirical engineering rock mass classification systems. This has involved support design in a wide variety of geological- and rock mechanical-conditions, including poor ground conditions like fault zones and weak rocks. For most of the encountered situations, the empirical support designs have performed well. However, the empirical classification systems pose several limitations to describe ground behavior and derive optimal rock support design in poor ground conditions as discussed in several publications during the last decades. In the present study, an analysis of 118 case records, mostly from monitored Norwegian tunnel sites, has been undertaken to investigate the performance of the current empirical design practice with the Q-system when exposed to poor ground conditions. The results have revealed significant improvement possibilities which relate to a wide variety of ground conditions. Among others, weak rocks, anisotropic rock, and rock mass conditions in the transition from self-bearing rock masses to rock masses requiring load-bearing support in the tunnel, and typically with rock mass quality Q < 1. As a result, a set of improvements and design recommendations have been developed and an integrated or hybrid design methodology specific for poor ground conditions proposed. The hybrid approach combines the main components and advantages of different design methodologies and provides guidance for design optimization where the empirical approach presents limitations. Highlights: The empirical approach of tunnel rock support design has limitations to capture ground behavior, a relevant parameter for support design in poor ground conditions. The study of a database with more than one hundred case records has revealed important improvement possibilities in the current design practice using the empirical approach. The involvement and integration of different design approaches and tools through a hybrid design methodology can allow for design optimization in poor ground conditions. [ABSTRACT FROM AUTHOR]

In sports data analysis and visualization, understanding collective tactical behavior has become an integral part. Interactive and automatic data analysis is instrumental in making use of growing amounts of compound information. In professional team sports, gathering and analyzing sportsperson monitoring data are common practice, intending to evaluate fatigue and succeeding adaptation responses, analyze performance potential, and reduce injury and illness risk. Data visualization technology born in the era of big data analytics provides a good foundation for further developing fitness tools based on artificial intelligence (AI). Hence, this study proposed a video-based effective visualization framework (VEVF) based on artificial intelligence and big data analytics. This study uses the machine learning method to categorize the sports video by extracting both the videos' temporal and spatial features. Our system is based on convolutional neural networks united with temporal pooling layers. The experimental outcomes demonstrate that the recommended VEVF model enhances the accuracy ratio of 98.7%, recall ratio of 94.5%, F1-score ratio of 97.9%, the precision ratio of 96.7%, the error rate of 29.1%, the performance ratio of 95.2%, an efficiency ratio of 96.1% compared to other existing models. [ABSTRACT FROM AUTHOR]

Abstract Background Due to identifiability problems, statistical inference about treatment-by-period interactions has not been discussed for stepped wedge designs in the literature thus far. Unidirectional switch designs (USDs) generalize the stepped wedge designs and allow for estimation and testing of treatment-by-period interaction in its many flexible design forms. Methods Under different forms of the USDs, we simulated binary data at both aggregated and individual levels and studied the performances of the generalized linear mixed model (GLMM) and the marginal model with generalized estimation equations (GEE) for estimating and testing treatment-by-period interactions. Results The parallel group design had the highest power for detecting the treatment-by-period interactions. While there was no substantial difference between aggregated-level and individual-level analysis, the GLMM had better point estimates than the marginal model with GEE. Furthermore, the optimal USD for estimating the average treatment effect was not efficient for treatment-by-period interaction and the marginal model with GEE required a substantial number of clusters to yield unbiased estimates of the interaction parameters when the correlation structure is autoregressive of order 1 (AR1). On the other hand, marginal model with GEE had better coverages than GLMM under the AR1 correlation structure. Conclusion From the designs and methods evaluated, in general, parallel group design with a GLMM is, preferred for estimation and testing of treatment-by-period interaction in a clustered randomized controlled trial for a binary outcome.

Abstract Background Shared implementation challenges at scale in early childhood home visiting have led researchers to explore precision home visiting as a promising service delivery mechanism to better address families’ unique needs and build greater program efficiencies. This randomized controlled pilot study aimed to assess the acceptability of a precision approach to one home visiting model, Family Spirit® and explore potential differences between Precision Family Spirit (PFS) and Standard Family Spirit (Standard FS) on participant-home visitor relationship and maternal outcomes. Methods Participants (N = 60) were at least 14 years old, pregnant or within 2 months postpartum, and enrolled in Family Spirit. Four sites in Michigan were randomized 1:1 to deliver PFS (up to 17 core lessons plus up to 13 additional lessons as needed) or Standard FS (home visiting services as usual). Primary (program acceptability, participant satisfaction, home visitor-participant relationship quality, retention, adherence) and secondary (knowledge, quality of life, difficulty with parenting problems, substance use, depression, stress) outcomes at 6 months postpartum are presented. PFS participants also self-reported on quality of life, difficulty with parenting problems, stress, substance use, and concerns with sexual and reproductive health and self and child’s nutrition status at each home visit. This informed which lessons they should receive. Results Mothers in both groups reported positive program acceptability, satisfaction, and home visitor-participant relationships at 6 months postpartum. However, open-ended feedback from Standard FS participants indicates that some lesson content may not be applicable to all participants. At 6 months, retention was 82.3% for PFS and 66.7% for Standard FS, and adherence was 30.1% for PFS and 20.6% for Standard FS. Conclusions Preliminary findings indicate that precision home visiting may be acceptable and feasible. A definitive trial is needed to build on this pilot data, assess outcomes for mothers and children participating in a precision approach to home visiting as compared to standard home visiting, and ready this approach for scale. Trial registration ClinicalTrials.gov NCT03975530 (first posted on 05/06/2019).

The present study evaluates the structural and environmental performance of recycled fibers as a low‐cost and eco‐friendly reinforcement of segmental tunnel lining. In this research, the defect effects in the support area are investigated using three types of scaled panel samples. In addition to the fiber‐only reinforced concrete, the performance of a new hybrid design is evaluated. The axial displacements, crack widths, crack lengths, and crack depths were monitored by displacement gauges and image processing. The experimental and numerical results show that the presence of defects, in addition to increasing at least five times the opening of the spalling crack, induces the appearance of new secondary cracks. Based on the results, it was observed that recycled fibers have a good ability to reduce the opening and growth of cracks. The hybrid reinforced design showed a significant performance compared to conventional reinforced segments, even in the most critical support conditions. According to several environmental parameters, the highest environmental compatibility in continuous support conditions is related to the fiber‐only reinforced concrete design; however, with presence of defects in the support area, the new hybrid reinforced design has shown the highest environmental compatibility in most environmental parameters. It was finally concluded that the fiber‐only reinforced concrete with recycled steel fibers and the new proposed hybrid reinforced concrete designs had high efficiencies in all cases in terms of structural, environmental, and economical performances. In addition to significantly reducing the crack openings in the hybrid reinforced design, the used rebars were reduced by about 40%. [ABSTRACT FROM AUTHOR]

In the present study, a new type of hybrid spillway termed labyrinth-shaft spillway was introduced to improve the discharge capacity and efficiency of the spillway. An advanced computational fluid dynamics (CFD) technique was used to analyze the performance of the labyrinth-shaft spillway. The hydraulic performance of the new model was investigated for different labyrinth geometries with a verified computational model. The analysis results demonstrated that the discharge capacity of the labyrinth-shaft spillway was better when compared to that of the conventional shaft spillways with the same weir heads. The discharge coefficient that reflects the efficiency of the labyrinth-shaft spillway was also much better when compared to the conventional spillway, while the opposite was observed with relatively small nappe heads. Similarly, the comparison with the findings of previous studies on labyrinth weirs in the literature demonstrated that labyrinth-shaft spillways performed better when compared to the conventional labyrinth weirs in-channel flow conditions, especially with high nappe heads. A new formula was also developed in the present study with regression analysis conducted on the collected data to calculate the discharge coefficients of the labyrinth-shaft spillway for H/P > 0.2. [ABSTRACT FROM AUTHOR]

The traditional single-treatment strategy for cancer is frequently unsuccessful due to the complexity of cellular signaling. However, suppression of multiple targets is vital to defeat tumor cells. In this research, new compounds for the treatment of cancer were developed successfully as novel hybrid anticancer agents. Based on a molecular hybridization strategy, we designed hybrid agents that target multiple protein kinases to fight cancer cells. The proposed hybrid agents combined purine and isatin moieties in their structures with 4-aminobenzohydrazide and hydrazine as different linkers. Having those two moieties in one molecule enabled the capability to inhibit multiple kinases, such as human epidermal receptor (EGFR), human epidermal growth factor receptor 2 (HER2), vascular endothelial growth factor receptor 2 (VEGFR2) and cyclin-dependent kinase 2 (CDK2). Anticancer activity was evaluated by performing cytotoxicity assays, kinase inhibition assays, cell cycle analysis, and BAX, Bcl-2, Caspase 3 and Caspase 9 protein level determination assays. The results showed that the designed hybrids tackled the cancer by inhibiting both cell proliferation and metastasis. A molecular docking study was performed to predict possible binding interactions in the active site of the investigated protein kinase enzymes. [ABSTRACT FROM AUTHOR]

Background/Aims: To evaluate how uncertainty in the intra-cluster correlation impacts whether a parallel-group or stepped-wedge cluster-randomized trial design is more efficient in terms of the required sample size, in the case of cross-sectional stepped-wedge cluster-randomized trials and continuous outcome data. Methods: We motivate our work by reviewing how the intra-cluster correlation and standard deviation were justified in 54 health technology assessment reports on cluster-randomized trials. To enable uncertainty at the design stage to be incorporated into the design specification, we then describe how sample size calculation can be performed for cluster- randomized trials in the 'hybrid' framework, which places priors on design parameters and controls the expected power in place of the conventional frequentist power. Comparison of the parallel-group and stepped-wedge cluster-randomized trial designs is conducted by placing Beta and truncated Normal priors on the intra-cluster correlation, and a Gamma prior on the standard deviation. Results: Many Health Technology Assessment reports did not adhere to the Consolidated Standards of Reporting Trials guideline of indicating the uncertainty around the assumed intra-cluster correlation, while others did not justify the assumed intra-cluster correlation or standard deviation. Even for a prior intra-cluster correlation distribution with a small mode, moderate prior densities on high intra-cluster correlation values can lead to a stepped-wedge cluster-randomized trial being more efficient because of the degree to which a stepped-wedge cluster-randomized trial is more efficient for high intra-cluster correlations. With careful specification of the priors, the designs in the hybrid framework can become more robust to, for example, an unexpectedly large value of the outcome variance. Conclusion: When there is difficulty obtaining a reliable value for the intra-cluster correlation to assume at the design stage, the proposed methodology offers an appealing approach to sample size calculation. Often, uncertainty in the intra-cluster correlation will mean a stepped-wedge cluster-randomized trial is more efficient than a parallel-group cluster-randomized trial design. [ABSTRACT FROM AUTHOR]

BACKGROUND: Dissemination of evidence-based practices that can reduce morbidity and mortality is important to combat the growing opioid overdose crisis in the USA. Research and expert consensus support reducing high-dose opioid therapy, avoiding risky opioid-benzodiazepine combination therapy, and promoting multi-modal, collaborative models of pain care. Collaborative care interventions that support primary care providers have been effective in medication tapering. We developed a patient-centered Primary Care-Integrated Pain Support (PIPS) collaborative care clinical program based on effective components of previous collaborative care interventions. Implementation facilitation, a multi-faceted and dynamic strategy involving the provision of interactive problem-solving and support during implementation of a new program, is used to support key organizational staff throughout PIPS implementation. The primary aim of this study is to evaluate the effectiveness of the implementation facilitation strategy for implementing and sustaining PIPS in the Veterans Health Administration (VHA). The secondary aim is to examine the effect of the program on key patient-level clinical outcomes-transitioning to safer regimens and enhancing access to complementary and integrative health treatments. The tertiary aim is to determine the categorical costs and ultimate budget impact of PIPS implementation. METHODS: This multi-site study employs an interrupted time series, hybrid type III design to evaluate the effectiveness of implementation facilitation for a collaborative care clinical program-PIPS-in primary care clinics in three geographically diverse VHA health care systems (sites). Participants include pharmacists and allied staff involved in the delivery of clinical pain management services as well as patients. Eligible patients are prescribed either an outpatient opioid prescription greater than or equal to 90 mg morphine equivalent daily dose or a combination opioid-benzodiazepine regimen. They must also have an upcoming appointment in primary care. The Consolidated Framework for Implementation Research will guide the mixed methods work across the formative evaluation phases and informs the selection of activities included in implementation facilitation. The RE-AIM framework will be used to assess Reach, Effectiveness, Adoption, Implementation, and Maintenance of PIPS. DISCUSSION: This implementation study will provide important insight into the effectiveness of implementation facilitation to enhance uptake of a collaborative care program in primary care, which targets unsafe opioid prescribing practices.

Background: Due to identifiability problems, statistical inference about treatment-by-period interactions has not been discussed for stepped wedge designs in the literature thus far. Unidirectional switch designs (USDs) generalize the stepped wedge designs and allow for estimation and testing of treatment-by-period interaction in its many flexible design forms.Methods: Under different forms of the USDs, we simulated binary data at both aggregated and individual levels and studied the performances of the generalized linear mixed model (GLMM) and the marginal model with generalized estimation equations (GEE) for estimating and testing treatment-by-period interactions.Results: The parallel group design had the highest power for detecting the treatment-by-period interactions. While there was no substantial difference between aggregated-level and individual-level analysis, the GLMM had better point estimates than the marginal model with GEE. Furthermore, the optimal USD for estimating the average treatment effect was not efficient for treatment-by-period interaction and the marginal model with GEE required a substantial number of clusters to yield unbiased estimates of the interaction parameters when the correlation structure is autoregressive of order 1 (AR1). On the other hand, marginal model with GEE had better coverages than GLMM under the AR1 correlation structure.Conclusion: From the designs and methods evaluated, in general, parallel group design with a GLMM is, preferred for estimation and testing of treatment-by-period interaction in a clustered randomized controlled trial for a binary outcome. [ABSTRACT FROM AUTHOR]

Identifying the maximum tolerated dose (MTD) and recommending a Phase II dose for an investigational treatment is crucial in cancer drug development. A suboptimal dose often leads to a failed late‐stage trial, while an overly toxic dose causes harm to patients. There is a very rich literature on trial designs for dose‐finding oncology clinical trials. We propose a novel hybrid design that maximizes the merits and minimizes the limitations of the existing designs. Building on two existing dose‐finding designs: a model‐assisted design (the modified toxicity probability interval) and a dose‐toxicity model‐based design, a hybrid design of the modified toxicity probability interval design and a dose‐toxicity model such as the logistic regression model is proposed, incorporating optimal properties from these existing approaches. The performance of the hybrid design was tested in a real trial example and through simulation scenarios. The hybrid design controlled the overdosing toxicity well and led to a recommended dose closer to the true MTD due to its ability to calibrate for an intermediate dose. The robust performance of the proposed hybrid design is illustrated through the real trial dataset and simulations. The simulation results demonstrated that the proposed hybrid design can achieve excellent and robust operating characteristics compared to other existing designs and can be an effective model for determining the MTD and recommended Phase II dose in oncology dose‐finding trials. For practical feasibility, an R‐shiny tool was developed and is freely available to guide clinicians in every step of the dose finding process. [ABSTRACT FROM AUTHOR]

Bu makalede, X-Bant ’ta hibrit Mikroşerit-YTED (Yalıtkan Taban Entegreli Dalga Kılavuzu) bant geçiren filtrenin optimizasyon çalışması yapılmıştır. Yüksek geçiren bir YTED filtre ile alçak geçiren bir mikroşerit filtrenin seri entegrasyonuyla elde edilen hibrit bant geçiren filtrenin geometrisindeki asimetrik bölümler düzeltilmiştir. Optimizasyon çalışmasında, CST (Computer Simulation Technology) Studio Suite simülasyon programındaki 5 farklı optimizasyon algoritma tekniği hibrit M-YTED bant geçiren filtreye uygulanmıştır. Filtreye uygulanan bu tekniklerin sonuçları karşılaştırılmalı olarak verilmiştir. Metotlar karşılaştırıldığında, geçiş bandındaki S11 değerleri toplamının en düşük değerde olması nedeniyle Parçacık Sürü Optimizasyon Algoritması seçilmiştir. Filtrenin w4 parametresinin değeri 6,165 mm olarak elde edilmiştir. Filtrenin kalite faktörü, optimizasyon çalışmasıyla Guvenli ve diğ., (2021)’nin çalışmasına göre 3,21 kat artırılmıştır. Hibrit Mikroşerit-YTED bant geçiren filtrenin geçiş bandı [ω1-ω2] 7,60 GHz ile 8,40 GHz frekans aralığında, filtrenin merkez frekansı (ω0) 7,90 GHz, filtrenin bant genişliği de 0,80 GHz (%10,01) olacak şekilde tasarlanmıştır. M-YTED bant geçiren filtrenin simülasyon sonuçlarına göre, merkez frekansı 8,15 GHz ve bant genişliği 0,92 GHz'dir (%11,29). Analitik ve simülasyon sonuçları karşılaştırıldığında, analitik sonuçlara göre simülasyon merkez frekansındaki frekans değişimi %1,98 ve bant genişliği değişimi %15’dir. Analitik ve simülasyon sonuçlarının birbiriyle uyumlu olduğu görülmektedir.

• Proposing novel lightweight self-similar hierarchical structures with square lattice. • Obtaining subwavelength and superwide bandgaps by introducing hierarchy. • Proposing design principles for bandgap widening without increasing system weight. • Demonstrating vibration isolation by analyzing transmission spectrum. • Enlarging working frequencies by hybrid design. Vibration isolation has always been a flourishing subject with practical interest because it helps in reducing structure vibration that has serious effects on moving vehicles and equipment operation, and it exists everywhere and incessantly in daily life. With the advantage of predictable and designable frequency bandgaps, elastic metamaterial has attracted a lot of research attention in the past decade and beyond. Inspired by the design of Chinese traditional window and kirigami pattern, this paper introduces a self-similar hierarchical elastic metamaterial that can offer superwide subwavelength bandgaps without increasing system weight. The comparison of band structures obtained by finite element simulation manifests significant effects of hierarchy design on lowering bandgap frequency and widening bandgap width. Through comprehensive analyses, the principles for maximizing bandgap width without increasing system weight are highlighted. The vibration response of supercells that consist of 2 × 3 unitcells is constructed for both the first- and second-order hierarchical structures are investigated. After analyzing the different working frequencies of supercells with distinct hierarchical ratios, the first-order and second-order hybrid hierarchical supercells containing unitcells with complementary bandgaps are designed. An excellent increase in effective and perfect attenuation width is demonstrated. The work presented herein provides a new and effective method for generating subwavelength and superwide bandgaps in lightweight structures. This advancement holds great promise for improving the application potential of elastic metamaterials. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: Shared implementation challenges at scale in early childhood home visiting have led researchers to explore precision home visiting as a promising service delivery mechanism to better address families' unique needs and build greater program efficiencies. This randomized controlled pilot study aimed to assess the acceptability of a precision approach to one home visiting model, Family Spirit® and explore potential differences between Precision Family Spirit (PFS) and Standard Family Spirit (Standard FS) on participant-home visitor relationship and maternal outcomes.Methods: Participants (N = 60) were at least 14 years old, pregnant or within 2 months postpartum, and enrolled in Family Spirit. Four sites in Michigan were randomized 1:1 to deliver PFS (up to 17 core lessons plus up to 13 additional lessons as needed) or Standard FS (home visiting services as usual). Primary (program acceptability, participant satisfaction, home visitor-participant relationship quality, retention, adherence) and secondary (knowledge, quality of life, difficulty with parenting problems, substance use, depression, stress) outcomes at 6 months postpartum are presented. PFS participants also self-reported on quality of life, difficulty with parenting problems, stress, substance use, and concerns with sexual and reproductive health and self and child's nutrition status at each home visit. This informed which lessons they should receive.Results: Mothers in both groups reported positive program acceptability, satisfaction, and home visitor-participant relationships at 6 months postpartum. However, open-ended feedback from Standard FS participants indicates that some lesson content may not be applicable to all participants. At 6 months, retention was 82.3% for PFS and 66.7% for Standard FS, and adherence was 30.1% for PFS and 20.6% for Standard FS.Conclusions: Preliminary findings indicate that precision home visiting may be acceptable and feasible. A definitive trial is needed to build on this pilot data, assess outcomes for mothers and children participating in a precision approach to home visiting as compared to standard home visiting, and ready this approach for scale.Trial Registration: ClinicalTrials.gov NCT03975530 (first posted on 05/06/2019). [ABSTRACT FROM AUTHOR]

The low-velocity impact properties and the optimal hybrid ratio range for improving the property of hybrid composites are studied, and the application of hybrid composites in automobile engine hoods is discussed in this paper. The low-velocity impact properties of the hybrid composite material are simulated under different stacking sequences and hybrid ratios by finite element simulation, and the accuracy of the finite element model (FEM) is verified through experiments. Increasing the proportion of carbon fiber (CF) in the hybrid layer and placing the basalt fiber (BF) on the compression side can improve the energy absorption capacity under low-velocity impact loads. CF/BF hybrid composite hoods are optimized based on the steel hood and the low-velocity impact performance of the hybrid composite. The BCCC layer absorbs the most energy under low-velocity impact loads. Compared with CFRP, the energy absorbed under 10 J and 20 J impact energy is increased by 26.1% and 14.2%, respectively. Through the low-velocity impact properties of hybrid composites, we found that placing BF on the side of the load and keep the ratio below 50%, while increasing the proportion of CF in the hybrid laminate can significantly improve the property of the hybrid laminate. The results show that the stiffness and modal properties of the hybrid composite can meet the design index requirements, and the pedestrian protection capability of the hood will also increase with the increase in the proportion of BF. [ABSTRACT FROM AUTHOR]

In recent years, the lattice structure produced by additive manufacturing is a type of metal foam that has been increasingly investigated for its unique mechanical properties. However, the conventional Computer-Aided Design (CAD) is inefficient, the triply periodic minimal surfaces are rarely mixed, and the smooth transitions at the boundaries are not considered. In this study, a hybrid optimization design method based on implicit surfaces is proposed, which combines multiple implicit surfaces to achieve the continuous change in the curvature at the structure junctions and reduce the stress concentration. The hybrid lattice structures designed by this method were additively manufactured using 316L alloy via a selective laser melting. The results of the finite element analysis and mechanical compression test show that the hybrid lattice structures generated by this method exhibit a higher yield strength and energy absorption. These works can be used for other implicit surfaces, improve and enrich the types of implicit surfaces, and provide more good choices for practical applications. [ABSTRACT FROM AUTHOR]

Abstract In sports data analysis and visualization, understanding collective tactical behavior has become an integral part. Interactive and automatic data analysis is instrumental in making use of growing amounts of compound information. In professional team sports, gathering and analyzing sportsperson monitoring data are common practice, intending to evaluate fatigue and succeeding adaptation responses, analyze performance potential, and reduce injury and illness risk. Data visualization technology born in the era of big data analytics provides a good foundation for further developing fitness tools based on artificial intelligence (AI). Hence, this study proposed a video-based effective visualization framework (VEVF) based on artificial intelligence and big data analytics. This study uses the machine learning method to categorize the sports video by extracting both the videos' temporal and spatial features. Our system is based on convolutional neural networks united with temporal pooling layers. The experimental outcomes demonstrate that the recommended VEVF model enhances the accuracy ratio of 98.7%, recall ratio of 94.5%, F1-score ratio of 97.9%, the precision ratio of 96.7%, the error rate of 29.1%, the performance ratio of 95.2%, an efficiency ratio of 96.1% compared to other existing models.

Hybrid design is an effective approach to construct functional mechanical metamaterials. In this study, a periodic hybrid method for the TPMS (triply periodic minimal surface) structures is proposed, maintaining the original surface connectivity and structural strength. It is implemented by the combination of implicit function Ψ(x,y,z) and transition function ηx,y,z of the TPMS governing equation. Furthermore, three classical TPMS, i.e., P (Schwarz Primitive), IWP (Schoen I-WP) and FRD (Schoen F-RD), are represented to study the elastic properties of hybridizations using FE (Finite Element) computational method and experiments. Through the RVE-based (Representative Volume Element) homogenization method, it is demonstrated how hybridization of TPMS expands the designable range of elastic modulus. In addition, the elastic properties of the hybridizations, such as axial modulus, diagonal modulus and anisotropy, etc., can be quantificationally tailored by turning the formal parameters of TPMS. This study can be considered as a foundational contribution for the advancement of hybrid TPMS metamaterials.

A new base catalyst was derived from submerged fermented Theobroma cacao pod husk (TCPH) in this work, the developed catalyst was tested for the production of fatty acid ethyl ester (FAEE) using the blends of beef tallow (BTO) - waste use oil (WUO) in the ratios of 10:90 (BTO10), 20:80 (BTO20), 30:70 (BTO30)….., 90:10 (BTO90), respectively. To determine the optimum FAEE yield with variable effects (reaction time, catalyst amount, reaction temperature, and EtOH/OMR), a hybrid design from response surface was adopted with coefficient of determination (R2) and Adjusted coefficient of determination (R2-adj.). Furthermore, the catalytic efficiency was tested by catalyst recycle, refining, and reusability test.Data revealed the oil blend ratio of BTO60:WUO40 was adequate to produced low viscous FAEE. Catalysts' analysis and characterization revealed the catalyst produced high CaO-base of 87.65 (%wt.), which accounted for the high yield of FAEE. Mathematical optimization via hybrid design showed that the catalyst amount with high F-value = 3063.24 and P-value = 0.0115, played the most significant role in the conversion of blended oil to FAEE among the variable factors considered. Furthermore, based on Box-Cox transformation, the lambda indicated a normal data in normal function of Y3 for polynomial model accuracy. Optimum validated FAEE yields of 99.64 (%wt.) with high coefficient of determination (R2) was established. The qualities of the FAEE were within the standard specification for biodiesel, and the produced catalysts can serve as feedstocks for industrial application.