Safety and efficacy of low-power pure-cut hot snare polypectomy for small nonpedunculated colorectal polyps compared with conventional resection methods: A propensity score matching analysis.

Objectives: Cold snare polypectomy (CSP) is widely performed for small colorectal polyps. However, small colorectal polyps sometimes include high-grade adenomas or carcinomas that require endoscopic resection with electrocautery. This study aimed to evaluate the efficacy and safety of a novel resection technique, hot snare polypectomy with low-power pure-cut current (LPPC-HSP) for small colorectal polyps, compared with CSP and conventional endoscopic mucosal resection (EMR). Methods: Records of patients who underwent CSP, EMR, or LPPC-HSP for nonpedunculated colorectal polyps less than 10 mm between April 2021 and March 2022 were retrospectively evaluated. We analyzed and compared the treatment outcomes of CSP and EMR with those of LPPC-HSP using propensity score matching. Results: After propensity score matching of 396 pairs, an analysis of CSP and LPPC-HSP indicated that LPPC-HSP had a significantly higher R0 resection rate (84% vs. 68%; p < 0.01). Delayed bleeding was observed in only two cases treated with CSP before matching. Perforation was not observed with either treatment. After propensity score matching of 176 pairs, an analysis of EMR and LPPC-HSP indicated that their en bloc and R0 resection rates were not significantly different (99.4% vs. 100%, p = 1.00; 79% vs. 81%, p = 0.79). Delayed bleeding and perforation were not observed with either treatment. Conclusions: The safety of LPPC-HSP was comparable to that of CSP. The treatment outcomes of LPPC-HSP were comparable to those of conventional EMR for small polyps. These results suggest that this technique is a safe and effective treatment for nonpedunculated polyps less than 10 mm.

Domination and power domination in a one-pentagonal carbon nanocone structure.

Domination is an important factor in determining the robustness of a graph structure. A thorough examination of the graph's topological structure is necessary for analyzing and examining it for various aspects. Understanding the stability of a chemical compound is a significant criterion in chemistry, which necessitates conducting numerous experimental tests. The domination number and power domination number are pivotal in defining a wide range of physical properties, which include physiochemical properties, thermodynamic properties, chemical activities, and biological activities. The one-pentagonal carbon nanocone (1-PCNC) is a member of the carbon nanocone family and has a structure similar to that of honeycomb networks, which are renowned for their robustness. In this paper, we find the domination number and power domination number of 1-PCNC by considering it as an (m-1)-layered infinite graph.

An Energy Efficient and Temperature Stable Digital FLL-based Wakeup Timer with Time-Domain Temperature Compensation.

This brief presents an on-chip digital intensive frequency-locked loop (DFLL)-based wakeup timer with a time-domain temperature compensation featuring a embedded temperature sensor. The proposed compensation exploits the deterministic temperature characteristics of two complementary resistors to stabilize the timer's operating frequency across the temperature by modulating the activation time window of the two resistors. As a result, it achieves a fine trimming step (± 1 ppm), allowing a small frequency error after trimming (<± 20 ppm). By reusing the DFLL structure, instead of employing a dedicated sensor, the temperature sensing operates in the background with negligible power (2 %) and hardware overhead (< 1 %). The chip is fabricated in 40 nm CMOS, resulting in 0.9 pJ/cycle energy efficiency while achieving 8 ppm/ºC from -40ºC to 80ºC.

Performance evaluation of facility locations using integrated DEA-based techniques.

Facility location, particularly in the context of international investments by global enterprises, stands out as a paramount concern within the purview of top management's strategic decision-making process. The selection of a suitable location plays a pivotal role in determining the ultimate achievement of organizational objectives. The process of selecting an appropriate location requires the comprehensive analysis of a substantial volume of data, encompassing diverse tangible and intangible evaluation criteria that may exhibit inherent conflicts. This paper addresses the challenge of determining the best location for a manufacturing facility by employing alternative performance measures within the framework of the data envelopment analysis (DEA) model. In a performance evaluation process, not only positive but also negative aspects should be determined. This paper, therefore, proposes a double-frontier DEA-AR model, which is an integrated approach that incorporates the efficient frontier, anti-efficient frontier, and assurance region weight restrictions, with the aim of increasing the discrimination ability of the DEA method. An efficient frontier evaluates the information of each location from a positive viewpoint, while the worst side is evaluated by an anti-efficient frontier. The technique of weight restrictions, which allows incorporating expert opinion into the assessment, is also applied with both frontiers to restrict the regions of weights to some specific area. The prescribed approach is illustrated by a numerical example of selecting the best location among ten different countries under consideration of 22 selection criteria obtained from PEST analysis. The results show that the proposed alternative performance measures significantly improve discrimination capability, enabling the ranking of candidates based on their suitability for the optimal location.

Consideration of the conversion factor from air dose rates to individual external dose per hour after the Fukushima accident - Individual external dose measurements of a TEPCO employee in Fukushima prefecture over a 9 year Period.

The accident at Fukushima Daiichi Nuclear Power Plant (FDNPP) in 2011 resulted in the dispersion of radioactive materials throughout the surrounding area and an increase in the air dose rate was even confirmed in Fukushima City, which is located approximately 60 km northeast of FDNPP. A Tokyo Electric Power Company (TEPCO) Holdings employee, who has lived and worked in Fukushima City since the FDNPP accident, measured individual external doses, GPS data, and his activities in Fukushima Prefecture over a 9 year period beginning in 2014. This data provides valuable information about the area. The data show the following results.  Comparison of the air dose rate at the home location to the individual external dose per hour at the home shows that the average conversion factor has increased over the 9 years and exceeded 0.3 since 2019, indicating an overall relatively good correlation.  Individual external doses measured in the office on the fourth floor of a concrete structure in Fukushima City have not changed significantly from 2014 to 2022, when air dose rates showed a decrease.  Outdoor individual external doses, such as those measured when commuting on foot, have a relatively strong correlation with air dose rates from airborne monitoring with the conversion factor of about 0.6. The conversion factor do not differ significantly from 2014 to 2022. In this study, the individual external dose data is applicable to the TEPCO measurer and is not necessarily representative of all residents of Fukushima City. However individual external dose data for 9 consecutive years will be useful for estimating individual external doses from air dose rates, and estimating annual additional exposure doses, if even some of them are applicable to similar life patterns and lifestyles.

[Bayesian network prediction study on the impact of occupational health psychological factors on insomnia among thermal power generation workers].

Objective: To explore the risk factors of insomnia among employees in the thermal power generation industry and the network relationships between their interactions, and to provide scientific basis for personalized interventions for high-risk groups with insomnia. Methods: In November 2022, 860 employees of a typical thermal power generation enterprise were selected as the research subjects by cluster sampling. On-site occupational health field surveys and questionnaire surveys were used to collect basic information, occupational characteristics, anxiety, depression, stress, occupational stress, and insomnia. The interaction between insomnia and occupational health psychological factors was evaluated by using structural equation model analysis and Bayesian network construction. Results: The detection rates of anxiety, depression and stress were 34.0% (292/860), 32.1% (276/860) and 18.0% (155/860), respectively. The total score of occupational stress was (445.3±49.9) points, and 160 workers (18.6%) were suspected of insomnia, and 578 workers (67.2%) had insomnia. Structural equation model analysis showed that occupational stress had a significant effect on the occurrence of insomnia in thermal power generation workers (standardized load coefficient was 0.644), and occupational health psychology had a low effect on insomnia (standardized load coefficient was 0.065). However, the Bayesian network model further analysis found that anxiety and stress were the two parent nodes of insomnia, with direct causal relationships, the arc strength was-8.607 and -15.665, respectively. The model prediction results showed that the probability of insomnia occurring was predicted to be 0 in the cases of no stress and anxiety, low stress without anxiety, and no stress with low anxiety. When high stress with low anxiety and low stress with high anxiety occurred, the predicted probability of insomnia occurring were 0.38 and 0.47, respectively. When both high stress and high anxiety occurred simultaneously, the predicted probability of insomnia occurring was 0.51. Conclusion: Bayesian network risk assessment can intuitively reveal and predict the insomnia risk of thermal power generation workers and the network interaction relationship between the risks. Anxiety and stress are the direct causal risks of insomnia, and stress is the main risk of individual insomnia of thermal power generation workers. The occurrence of insomnia can be reduced based on scientific intervention of stress conditions.

Who's in control? Situating expertise, (mis)trust, and power among the Latine/Hispanic community in COVID-19's liminal moments.

BACKGROUND: Research has established the disproportionate impact of COVID-19 on Black, Indigenous, and People of color (BIPOC) communities, and the barriers to vaccine trust and access among these populations. Focusing on perceptions of safety, access, and trustworthiness, studies often attach barriers to community-members, and discuss vaccines as if developed from an objective perspective, or "view from nowhere" (Haraway). OBJECTIVE: We sought to follow Haraway's concept of "situated knowledges," whereby no one truth exists, and information is understood within its context, to understand the exertions of expertise surrounding vaccines. We focused on perceptions of power among a BIPOC community during a relatively unexamined moment, wherein the status of the pandemic and steps to prevent it were particularly uncertain. METHODS: We report the findings of ten focus groups conducted among members of Rhode Island's Latine/Hispanic communities between December 2021 and May 2022. We called this time COVID-19's liminal moment because vaccines were distributed, mandates were lifted, vaccine efficacy was doubted, and new strains spread. We translated, transcribed, and analyzed focus groups using thematic analysis. RESULTS: Community-member (n = 65) perceptions of control aligned with three key themes: (1) no power is capable of controlling COVID-19, (2) we are the objects of scientific and political powers, and (3) we, as individuals and communities, can control COVID-19 through our decisions and actions. CONCLUSIONS: By centering the perspectives of a minoritized community, we situated the scientific knowledge produced about COVID-19 within the realities of imperfect interventions, uncontrollable situations, and medical power-exertions. We argue that medical knowledge should not be assumed implicitly trustworthy, or even capable, but instead seen as one of many products of human labor within human systems. Trust and trustworthiness must be mutually negotiated between experts, contexts, and communities through communication, empowerment, and justice.

Beta-Band power modulation in the human amygdala differentiates between go/no-go responses in an arm reaching task.

Introduction Traditionally known for its involvement in emotional processing, the amygdala's involvement in motor control remains relatively unexplored, with sparse investigation into the neural mechanisms governing amygdaloid motor movement and inhibition. Objective This study aimed to characterize the amygdaloid beta-band (13-30 Hz) power between "Go" and "No-go" trials of an arm reaching task. Methods Ten participants with drug-resistant epilepsy implanted with stereoelectroencephalographic (SEEG) electrodes in the amygdala were enrolled in this study. SEEG data was recorded throughout discrete phases of a Direct Reach Go/No-go task, during which participants reached a touchscreen monitor or withheld movement based on a colored cue. Multitaper power analysis along with Wilcoxon signed-rank and Yates-corrected Z tests were used to assess significant modulations of beta power between the Response and Fixation (baseline) phases in the "Go" and "No-go" conditions. Results In the "Go" condition, nine out of the ten participants showed a significant decrease in relative beta-band power during the Response phase (p ≤ 0.0499). In the "No-go" condition, eight out of the ten participants presented a statistically significant increase in relative beta-band power during the Response phase (p ≤ 0.0494). Four out of the eight participants with electrodes in the contralateral hemisphere and seven out of the eight participants with electrodes in the ipsilateral hemisphere presented significant modulation in beta-band power in both the "Go" and "No-go" conditions. At the group level, no significant differences were found between the contralateral and ipsilateral sides or between genders. Conclusion This study reports beta-band power modulation in the human amygdala during voluntary movement in the setting of motor execution and inhibition. This finding supplements prior research in various brain regions associating beta-band power with motor control. The distinct beta-power modulation observed between these response conditions suggests involvement of amygdaloid oscillations in differentiating between motor inhibition and execution.

Sample Size Determination and Study Design Impact on Dose-Scale Pharmacodynamic Bioequivalence: a Case Study Using Orlistat.

Dose-scale pharmacodynamic bioequivalence is recommended for evaluating the consistency of generic and innovator formulations of certain locally acting drugs, such as orlistat. This study aimed to investigate the standard methodology for sample size determination and the impact of study design on dose-scale pharmacodynamic bioequivalence using orlistat as the model drug. A population pharmacodynamic model of orlistat was developed using NONMEM 7.5.1 and utilized for subsequent simulations. Three different study designs were evaluated across various predefined relative bioavailability ratios of test/reference (T/R) formulations. These designs included Study Design 1 (2×1 crossover with T1 60 mg, R1 60 mg, and R2 120 mg), Study Design 2 (2×1 crossover with T2 120 mg, R1 60 mg, and R2 120 mg), and Study Design 3 (2×2 crossover with T1 60 mg, T2 120 mg, R1 60 mg, and R2 120 mg). Sample sizes were determined using a stochastic simulation and estimation approach. Under the same T/R ratio and power, Study Design 3 required the minimum sample size for bioequivalence, followed by Study Design 1, while Study Design 2 performed the worst. For Study Designs 1 and 3, a larger sample size was needed on the T/R ratio < 1.0 side for the same power compared to that on the T/R ratio > 1.0 side. The opposite asymmetry was observed for Study Design 2. We demonstrated that Study Design 3 is most effective for reducing the sample size for orlistat bioequivalence studies, and the impact of T/R ratio on sample size shows asymmetry.

Tuned exchange imaging: Can the filter exchange imaging pulse sequence be adapted for applications with thin slices and restricted diffusion?

Filter exchange imaging (FEXI) is a double diffusion-encoding (DDE) sequence that is specifically sensitive to exchange between sites with different apparent diffusivities. FEXI uses a diffusion-encoding filtering block followed by a detection block at varying mixing times to map the exchange rate. Long mixing times enhance the sensitivity to exchange, but they pose challenges for imaging applications that require a stimulated echo sequence with crusher gradients. Thin imaging slices require strong crushers, which can introduce significant diffusion weighting and bias exchange rate estimates. Here, we treat the crushers as an additional encoding block and consider FEXI as a triple diffusion-encoding sequence. This allows the bias to be corrected in the case of multi-Gaussian diffusion, but not easily in the presence of restricted diffusion. Our approach addresses challenges in the presence of restricted diffusion and relies on the ability to independently gauge sensitivities to exchange and restricted diffusion for arbitrary gradient waveforms. It follows two principles: (i) the effects of crushers are included in the forward model using signal cumulant expansion; and (ii) timing parameters of diffusion gradients in filter and detection blocks are adjusted to maintain the same level of restriction encoding regardless of the mixing time. This results in the tuned exchange imaging (TEXI) protocol. The accuracy of exchange mapping with TEXI was assessed through Monte Carlo simulations in spheres of identical sizes and gamma-distributed sizes, and in parallel hexagonally packed cylinders. The simulations demonstrate that TEXI provides consistent exchange rates regardless of slice thickness and restriction size, even with strong crushers. However, the accuracy depends on b-values, mixing times, and restriction geometry. The constraints and limitations of TEXI are discussed, including suggestions for protocol adaptations. Further studies are needed to optimize the precision of TEXI and assess the approach experimentally in realistic, heterogeneous substrates.

The application effect of the optimized scheduling model of virtual power plant participation in the new electric power system.

To build a comprehensive framework for virtual power plant (VPP) development aligned with market dynamics and to devise effective strategies to foster its growth, this study undertakes several key steps. Firstly, it constructs a VPP development framework based on market conditions, to drive the evolution of new power systems and facilitating energy transformation. Secondly, through a blend of theoretical analysis and model construction, the fundamental principles of VPP are systematically elucidated, and a decision model for the VPP development framework, focusing on price demand response, is formulated. Lastly, an optimal scheduling model for the new power system is developed, with its efficacy validated across three distinct scenarios. The findings underscore the critical importance of integrating energy storage technologies, particularly pumped storage hydropower systems, for achieving balance and optimization within new power systems. Model verification reveals that the incorporation of energy storage power stations significantly enhances system stability and efficiency, particularly in addressing the volatility associated with renewable energy sources. Additionally, the analysis indicates that while the adoption of energy storage technologies may marginally increase overall power generation costs, the total power generation cost declines with the integration of battery storage and pumped storage hydropower stations. This suggests that leveraging energy storage technologies not only enhances system operational reliability but also contributes to reducing the overall cost of power production to a certain extent. In summary, this study presents an economic and environmentally sustainable scheduling model for new power systems within the context of market trading environments. By offering both theoretical insights and practical guidance, it aims to support sustainable development and energy transformation initiatives. Ultimately, the study is poised to foster the adoption of clean energy, facilitate the establishment of smart grids, and bolster the sustainable utilization of energy resources, thereby advancing environmental conservation efforts.

Adventitious Error and Its Implications for Testing Relations Between Variables and for Composite Measurement Outcomes.

Wu and Browne (Psychometrika 80(3):571-600, 2015. https://doi.org/10.1007/s11336-015-9451-3 ; henceforth W &B) introduced the notion of adventitious error to explicitly take into account approximate goodness of fit of covariance structure models (CSMs). Adventitious error supposes that observed covariance matrices are not directly sampled from a theoretical population covariance matrix but from an operational population covariance matrix. This operational matrix is randomly distorted from the theoretical matrix due to differences in study implementations. W &B showed how adventitious error is linked to the root mean square error of approximation (RMSEA) and how the standard errors (SEs) of parameter estimates are augmented. Our contribution is to consider adventitious error as a general phenomenon and to illustrate its consequences. Using simulations, we illustrate that its impact on SEs can be generalized to pairwise relations between variables beyond the CSM context. Using derivations, we conjecture that heterogeneity of effect sizes across studies and overestimation of statistical power can both be interpreted as stemming from adventitious error. We also show that adventitious error, if it occurs, has an impact on the uncertainty of composite measurement outcomes such as factor scores and summed scores. The results of a simulation study show that the impact on measurement uncertainty is rather small although larger for factor scores than for summed scores. Adventitious error is an assumption about the data generating mechanism; the notion offers a statistical framework for understanding a broad range of phenomena, including approximate fit, varying research findings, heterogeneity of effects, and overestimates of power.

A vulnerability detection method for IoT protocol based on parallel fuzzy algorithm.

The Internet of Things communication protocol is prone to security vulnerabilities when facing increasing types and scales of network attacks, which can affect the communication security of the Internet of Things. It is crucial to effectively detect these vulnerabilities in order to improve the security of IoT communication protocols and promptly fix them. Therefore, this study proposes a distributed IoT communication protocol vulnerability detection method based on an improved parallelized fuzzy testing algorithm. Firstly, based on design principles and by comparing different communication protocols, a communication architecture for the distribution network's Internet of Things was constructed, and the communication protocols were formalized and decomposed. Next, preprocess the vulnerability detection samples, and then use genetic algorithm to improve the parallelized fuzzy testing algorithm to perform vulnerability detection. Through this improved algorithm, the missed detection rate and false detection rate can be effectively reduced, thereby improving the security of IoT communication protocols. The experimental results show that the highest missed detection rate of this method is only 4.0 %, and the false detection rate is low, with high detection efficiency. This indicates that the method has good performance and reliability in detecting vulnerabilities in IoT communication protocols.

In-situ electrochemical impedance analysis of a commercial SOFC stack fueled by real wood gas.

The combination of solid oxide fuel cells (SOFCs) and wood gasification has the potential to significantly increase renewable electricity production and decrease emissions. Depending on the quality of the wood gas, degradation processes have a significant impact on the reliability and lifetime of the SOFC. Using electrochemical impedance spectroscopy (EIS) and subsequent distribution of relaxation times (DRT) analysis, the impact on the degradation of coupling wood gasification with a commercial SOFC stack is determined in this study. The thermal behavior of the SOFC stack under various operating conditions, as well as various synthetic wood gas mixtures classified by their hydrogen-to-carbon (H/C) ratio, was assessed. The decrease in the H/C ratio from 8 to 1, observed during syngas and real wood gas operation, leads to a rightward shift in the Nyquist plots, suggesting an increase in the SOFC stack's impedance. Correlations between variations in the H/C ratio and their effects on anodic electrooxidation, ionic conduction, gas transport, and diffusion were identified using DRT analysis to interpret the EIS results. By incorporating an upstream desulfurization system and ensuring an H/C ratio greater than 2, the coupling of biomass gasification with the SOFC stack was stable to degradation issues.

The association between unilateral and bilateral performance-related measures in elite female soccer players: a multifaceted investigation.

Purpose: The present study aimed to investigate a) the associations between bilateral performance utilizing countermovement jump (CMJ), squat jump (SJ), speed and unilateral CMJ, isokinetic peak torque in knee extension and flexion with angular velocities of 60°/s and 180°/s and tensiomyography (TMG) parameters; b) whether the asymmetries derived from unilateral tests are associated with bilateral CMJ, SJ and speed in elite female soccer players. Methods: Thirty-five elite female soccer players (average age: 20 ± 5 years) completed CMJ, SJ, speed, isokinetic muscle strength and TMG tests. Results: Compared to the non-dominant leg, the dominant leg demonstrated greater peak torque output in both knee flexion (7.4%) and knee extension (5.6%) isokinetic tasks, as well as m. vastus medialis contraction time (7.6%), and soccer-specific agility test (4.1%). Conversely, the hamstring to quadriceps peak torque ratio at 180°/s (8.5%) was significantly greater in the non-dominant leg. The associations between CMJ, SJ and speed performance were positive and ranged from weak (r = 0.350) to high (r = 0.710). For speed and TMG-derived variables, correlations were negative and ranged from weak (r = -0.345, p = 0.042, for vastus medialis contraction time) to moderate (r = -0.530, p = 0.001, for biceps femoris contraction time). Furthermore, both bilateral CMJ and SJ negatively correlated with TMG-derived variables, ranging from weak (r = -0.350, p = 0.039, for vastus lateralis contraction time) to moderate (r = -0.537, p = 0.003, for rectus femoris contraction time). Conclusion: The overall significant, albeit inconsistent, correlations between the diverse performance scores obtained highlight the necessity for a multifaceted and thorough diagnostic strategy in female soccer players.

Reliability, interrelationships, and minimal detectable changes of strength and power metrics among well-trained rugby sevens players.

Despite the importance of strength and power in rugby skills and match outcomes, there exists a noticeable gap in the measurement consistency and estimation of a true change of typical assessments designed to assess these qualities. To address this gap, we investigated the between-session reliability, interrelationships, and minimal detectable changes (MDC) of commonly used strength and power measures in team sports. Sixteen national-level rugby 7 s players were tested on two occasions, one week apart. Both the best and average (of 2-3 trials) peak force, peak power, height, distance, and/or strength indices during countermovement jump (CMJ), drop jump (DJ), isometric mid-thigh pull (IMTP), plyometric push-up (PPU), and standing long jump (SLJ) were obtained. Furthermore, one-repetition maximum (1RM) strength for bench press and back squat, reactive strength index, and dynamic strength index were also determined. Reliability was assessed using intraclass correlation coefficients (ICC) and coefficients of variation (CV), and used for MDC calculations, and interrelationships between variables were determined using correlation coefficients. Reliability was excellent for bench press, back squat, and SLJ (ICCs > 0.91); high to excellent for IMTP peak force, all CMJ, and DJ (except best DJ height and contact time), and PPU peak force parameters (ICCs > 0.78), with < 10% CVs (except PPU peak power). MDCs were generally smaller for average than best values. Large to very large relationships (r = 0.60 to 0.85) were observed between bench press, back squat, and IMTP with selected parameters of CMJ and PPU (p < 0.05), but not in DJ and SLJ. In conclusion, selected measures of strength and power displayed high to excellent reproducibility, with average values (rather than best) offering more stable assessments, and "smaller" MDCs. Based upon the relationships, it can be inferred that maximising strength would likely contribute to enhanced explosive performance.

National Greenhouse Gas Emission Reduction Potential from Adopting Anaerobic Digestion on Large-Scale Dairy Farms in the United States.

Waste-to-energy systems can provide a functional demonstration of the economic and environmental benefits of circularity, innovation, and reimagining existing systems. This study offers a robust quantification of the greenhouse gas (GHG) emission reduction potential of the adoption of anaerobic digestion (AD) technology on applicable large-scale dairy farms in the contiguous United States. GHG reduction estimates were developed through a robust life cycle modeling framework paired with sensitivity and uncertainty analyses. Twenty dairy configurations were modeled to capture important differences in housing and manure management practices, applicable AD technologies, regional climates, storage cleanout schedules, and methods of land application. Monte Carlo results for the 90% confidence interval illustrate the potential for AD adoption to reduce GHG emissions from the large-scale dairy industry by 2.45-3.52 MMT of CO2-eq per year considering biogas use only in renewable natural gas programs and as much as 4.53-6.46 MMT of CO2-eq per year with combined heat and power as an additional biogas use case. At the farm level, AD technology may reduce GHG emissions from manure management systems by 58.1-79.8% depending on the region. Discussion focuses on regional differences in GHG emissions from manure management strategies and the challenges and opportunities surrounding AD adoption.

Simultaneous Inference of Multiple Binary Endpoints in Biomedical Research: Small Sample Properties of Multiple Marginal Models and a Resampling Approach.

In biomedical research, the simultaneous inference of multiple binary endpoints may be of interest. In such cases, an appropriate multiplicity adjustment is required that controls the family-wise error rate, which represents the probability of making incorrect test decisions. In this paper, we investigate two approaches that perform single-step p $p$ -value adjustments that also take into account the possible correlation between endpoints. A rather novel and flexible approach known as multiple marginal models is considered, which is based on stacking of the parameter estimates of the marginal models and deriving their joint asymptotic distribution. We also investigate a nonparametric vector-based resampling approach, and we compare both approaches with the Bonferroni method by examining the family-wise error rate and power for different parameter settings, including low proportions and small sample sizes. The results show that the resampling-based approach consistently outperforms the other methods in terms of power, while still controlling the family-wise error rate. The multiple marginal models approach, on the other hand, shows a more conservative behavior. However, it offers more versatility in application, allowing for more complex models or straightforward computation of simultaneous confidence intervals. The practical application of the methods is demonstrated using a toxicological dataset from the National Toxicology Program.

Exploring the efficacy of laser-assisted in-office tooth bleaching: A study on varied irradiation times and power settings utilizing a diode laser (445 nm).

The aim of this study was to evaluate the effectiveness of a laser-assisted in-office tooth bleaching treatment, employing a diode laser (445 nm) using different power and time settings. Two hundred human incisors were collected for evaluating tooth color change (ΔΕ00) and whiteness index in dentistry (ΔWID) following laser-assisted tooth bleaching treatment. The specimens were distributed into 25 groups (n = 8) according to laser output power (0.5-2 W) and duration of irradiation (10-60 s) that was applied. ΔΕ00 and ΔWID were evaluated using a spectrophotometer at three points of time (24 h, 1 week and 1 month after treatments). Three-way ANOVA revealed that power, duration of laser irradiation, and time of measurement after bleaching treatments significantly affected both ΔΕ00 and ΔWID(p < 0.05). Furthermore, laser irradiation increased ΔΕ00 and ΔWID at all applied powers compared to the control group (p < 0.05), but this increase was dependent on the duration of irradiation. Laser irradiation significantly increased ΔΕ00 when the duration of operation was 50-60 s at 0.5-1 W, while at 1.5-2 W was significantly increased when the duration was 30-60 s. ΔWID was significant higher in the laser groups compared to the control group at all powers, except for 0.5 W where it was significant higher when the duration was 50-60 s. The outcomes of the study can help in selecting the suitable power settings and duration of laser exposure to achieve the optimal whitening results while ensuring the safety of the tooth pulp.

High-Performance PM6:Y6-Based Ternary Solar Cells with Enhanced Open Circuit Voltage and Balanced Mobilities via Doping a Wide-Band-Gap Amorphous Acceptor.

Great progress has been made in organic solar cells (OSCs) in recent years, especially after the report of the highly efficient small-molecule electron acceptor Y6. However, the relatively low open circuit voltage (VOC) and unbalanced charge mobilities remain two issues that need to be resolved for further improvement in the performance of OSCs. Herein, a wide-band-gap amorphous acceptor IO-4Cl, which possessed a shallower lowest unoccupied molecular orbital (LUMO) energy level than Y6, was introduced into the PM6:Y6 binary system to construct a ternary device. The mechanism study revealed that the introduced IO-4Cl was alloyed with Y6 to prevent the overaggregation of Y6 and offer dual channels for effective hole transportation, resulting in balanced hole and electron mobilities. Taking these advantages, an enhanced VOC of 0.894 V and an improved fill factor of 75.58% were achieved in the optimized PM6:Y6:IO-4Cl-based ternary device, yielding a promising power conversion efficiency (PCE) of 17.49%, which surpassed the 16.72% efficiency of the PM6:Y6 binary device. This work provides an alternative solution to balance the charge mobilities of PM6:Y6-based devices by incorporating an amorphous high-performance LUMO A-D-A small molecule as the third compound.