Multiple Adjustments Research Articles

Agricultural Machinery Path Tracking with Varying Curvatures Based on an Improved Pure-Pursuit Method

The current research on path tracking primarily focuses on improving control algorithms, such as adaptive and predictive models, to enhance tracking accuracy and stability. To address the issue of low tracking accuracy caused by variable-curvature paths in automatic navigation within agricultural environments, this study proposes a fuzzy control-based path-tracking method. Firstly, a pure-pursuit model and a kinematic model were established based on a Four-Wheel Independent Steering and Four-Wheel Independent Driving (4WIS-4WID) structure. Secondly, a fuzzy controller with three inputs and one output was designed, using the lateral deviation, de; heading deviation, θe; and bending degree, c, of the look-ahead path as the input variables. Through multiple simulations and adjustments, 75 control rules were developed. The look-ahead distance, Ld, was obtained through fuzzification, fuzzy inference, and defuzzification processes. Next, a speed-control function was constructed based on the agricultural machinery’s pose deviations and the bending degree of the look-ahead path to achieve variable speed control. Finally, field tests were conducted to verify the effectiveness of the proposed path-tracking method. The tracking experiment results for the two types of paths indicate that under the variable-speed dynamic look-ahead distance strategy, the average lateral deviations for the variable-curvature paths were 1.8 cm and 3.3 cm while the maximum lateral deviations were 10.1 cm and 10.5 cm, respectively. Compared to the constant-speed fixed look-ahead pure-pursuit model, the average lateral deviation was reduced by 56.1% and the maximum lateral deviation by 50.4% on the U-shaped path. On the S-shaped path, the average lateral deviation was reduced by 56.0% and the maximum lateral deviation by 58.9%. The proposed method effectively improves the path-tracking accuracy of agricultural machinery on variable-curvature paths, meeting the production requirements for curved operations in agricultural environments.

Subcutaneous Furosemide Therapy for Chronic Management of Refractory Congestive Heart Failure in Dogs and Cats

Reduced efficacy of oral diuretics in the treatment of congestive heart failure (CHF) can be secondary to reduced enteral drug absorption. The aim of this study was to determine the efficacy of subcutaneous (SC) furosemide administration to control the signs of refractory CHF in dogs and cats and to assess the feasibility of this route of administration. The clinical records of 13 dogs and 17 cats with a history of refractory CHF treated with subcutaneous (SC) furosemide were reviewed retrospectively. Administration of SC furosemide was offered as an alternative therapy when animals experienced an unsatisfactory clinical response to oral diuretics despite multiple dose adjustments and when, for this reason, pet owners were considering euthanasia. The satisfactory control of the animal’s breathing rate and effort and overall pet owner’s satisfaction were observed in all cases. Following administration of SC furosemide, the median survival time was 106 (95% CI: 22–154) days in dogs and 89 (95% CI: 35 to 749) days in cats. This study showed that furosemide administered subcutaneously appears to be an efficacious and feasible therapeutic option for providing control of the signs of cardiac congestion in both dogs and cats with a previous unsatisfactory response to oral diuresis.

Operation Optimization Model of Regional Power Grid Considering Congestion Management and Security Check in Complex Market Operation Environment

Security checks are essential for ensuring the safe operation of the regional power grid (RPG) and the smooth functioning of the electricity spot market (ESM). Currently, China’s RPG operating environment encompasses a complex mix of centralized ESM, decentralized ESM, and planned power generation. This complexity has led to increasingly severe RPG congestion issues. To address this, this paper introduces a security check mechanism design and operational optimization approach tailored for RPGs in complex markets, with a focus on congestion management. Firstly, the paper elaborates on the practical foundations, unique constraints, and requirements for security checks and congestion management during the RPG’s operational mode transitions. Secondly, it outlines the principles underlying the security check mechanism and presents a framework for RPG security checks and congestion management. Through a comparative analysis of three different programs, including their advantages, disadvantages, and applicable scenarios, the paper provides an optimal program recommendation. Building on this, the paper develops an operational optimization method that incorporates congestion management for each of the three security check and congestion management programs. Lastly, an IEEE-39 node test system is simulated to validate the effectiveness of the proposed programs. The mechanism and simulation analysis results show that Program 3, based on market mechanisms, has theoretical and practical advantages over Program 1 (based on multiple adjustments) and Program 2 (based on dispatch plans) for congestion management. Under the same line congestion situation, Program 1 requires two adjustments to relieve the line congestion, while Program 2 and Program 3 can solve the problem with just one optimization adjustment, and the congestion management effect of Program 3 is more obvious and superior.

A novel longitudinal rank-sum test for multiple primary endpoints in clinical trials: Applications to neurodegenerative disorders

Neurodegenerative disorders such as Alzheimer’s disease (AD) present a significant global health challenge, characterized by cognitive decline, functional impairment, and other debilitating effects. Current AD clinical trials often assess multiple longitudinal primary endpoints to comprehensively evaluate treatment efficacy. Traditional methods, however, may fail to capture global treatment effects, require larger sample sizes due to multiplicity adjustments, and may not fully utilize the available longitudinal data. To address these limitations, we introduce the Longitudinal Rank Sum Test (LRST), a novel nonparametric rank-based omnibus test statistic. The LRST enables a comprehensive assessment of treatment efficacy across multiple endpoints and time points without the need for multiplicity adjustments, effectively controlling Type I error while enhancing statistical power. It offers flexibility for various data distributions encountered in AD research and maximizes the utilization of longitudinal data. Simulations across realistic clinical trial scenarios, including those with conflicting treatment effects, and real-data applications demonstrate the LRST’s performance, underscoring its potential as a valuable tool in AD clinical trials.

COVID-19 pandemic and housing demand mortgage: Partial adjustment model approach

One of the efforts to encourage the fulfillment of housing needs is the provision of housing both from the government and the private sector by considering the community's purchasing power. The background of this research is that the fulfillment of housing needs by both the government and the private sector has yet to be maximized while the demand for housing is relatively high. This research is still necessary because the demand for housing is still high. Increased housing demand will push house prices due to limited housing land. The problems faced focus on the relatively high demand for mortgages because even in the conditions of the COVID-19 pandemic, people still make houses their top priority. This study aims to analyze the effect of people's income, loan interest rates, the amount of housing finance, and dummy before and during the COVID-19 pandemic on housing demand mortgage. The data analysis technique in this study used multiple regression Partial Adjustment Model (PAM). The results showed that the variables of income as proxy for GDP and loan interest rates significantly affected housing demand mortgage. In contrast, the amount of housing finance and the COVID-19 dummy had no significant impact. The research implication that researchers can provide to the government is to provide policy recommendations regarding the Housing Finance Liquidity Facility (FLPP) program, which is intended for low-income communities.

Vitamin D-related genetic variants and prostate cancer risk in Black men.

The relationship between vitamin D and prostate cancer has primarily been characterized among White men. Black men, however, have higher prostate cancer incidence and mortality rates, chronically low circulating vitamin D levels, and ancestry-specific genetic variants in vitamin D-related genes. Here, we examine critical genes in the vitamin D pathway and prostate cancer risk in Black men. We assessed a total of 73 candidate variants in genes (namely GC, CYP27A1, CYP27B1, CYP24A1, VDR, and RXRA) including functional variants previously associated with prostate cancer and circulating 25(OHD) in White men. Associations with prostate cancer risk were examined using genome-wide association study data for approximately 10,000 prostate cancer cases and 10,000 controls among Black men and over 85,000 cases and 91,000 controls among White men for comparison. A statistical significance threshold of 0.000685 was used to account for the 73 variants tested. None of the variants examined were significantly associated with prostate cancer risk among Black men after multiple comparison adjustment. Suggestive associations (P < 0.05) for four variants were found in Black men, including two in RXRA (rs41400444 OR=1.09, 95 % CI: 1.01-1.17, P = 0.024 and rs10881574 OR = 0.93, 0.87-1.00, P = 0.046) and two in VDR (rs2853563 OR = 1.07, 1.01-1.13, P = 0.017 and rs1156882 OR = 1.06, 1.00-1.12, P = 0.045). Two variants in VDR were also positively associated with risk in White men (rs11568820 OR = 1.04, 1.02-1.06, P = 0.00024 and rs4516035 OR = 1.03, 1.01-1.04, P = 0.00055). We observed suggestive associations between genetic variants in RXRA and VDR and prostate cancer risk in Black men. Future research exploring the relationship of vitamin D with cancer risk in Black men will need larger sample sizes to identify ancestry-specific variants relevant to risk in this population.

Long-term exposure to ambient air pollution and epigenetic age acceleration in children.

Long-term exposure to ambient air pollution has been associated with epigenetic age acceleration (EAA) in adults, but its impact on children remains less understood. This study analyzed data from 457 children (mean age: 7.9 years) in the Project Viva cohort (2007-2010, eastern Massachusetts, USA). We calculated EAA from leukocytes: Horvath's Epigenetic Age Acceleration (HorvathEAA), Intrinsic Epigenetic Age Acceleration (IEAA), and Skin and Blood Epigenetic Age Acceleration (Skin&BloodEAA). We applied generalized additive models to evaluate associations of prior 365-day average and lifetime average exposure to PM2.5, NO2, and O3, and distance to major roadways with EAA. Results indicated that each interquartile range of prior 365-day average of PM2.5 corresponded with 0.26 years (95% CI: -0.49, -0.03) lower HorvathEAA, although it did not survive multiple testing adjustment. Similar patterns but with wider confidence intervals were observed for IEAA (-0.22, 95% CI: -0.44, 0.01) and Skin&BloodEAA (-0.04, 95% CI: -0.19, 0.11). No associations were observed of exposure to lifetime average PM2.5, prior-year or lifetime average NO2 or O3, or distance to major roadways with EAA. These findings suggest higher prior 365-day average PM2.5 exposure may relate to lower HorvathEAA in children.

To adjust, or not to adjust, for multiple comparisons.

Questions often arise concerning when, whether and how we should adjust our interpretation of the results from multiple hypothesis tests. Strong arguments have been put forward in the epidemiological literature against any correction or adjustment for multiplicity, but regulatory requirements (particularly for pharmaceutical trials) can sometimes trump other concerns. The formal basis for adjustment is often the control of error rates, and hence the problems of multiplicity may seem rooted in a purely frequentist paradigm, though this can be a restrictive viewpoint. Commentators may never wholly agree on any of these things. This article draws some of the key threads from the discussion, and suggests further reading.

The problem of multiple adjustments in the assessment of minimal clinically important differences.

Anthropometric, demographic, genetic, and clinical features may affect cognitive, behavioral, and functional decline, while clinical trials seldom consider minimal clinically important differences (MCIDs) in their analyses. MCIDs were reviewed taking into account features that may affect cognitive, behavioral, or functional decline in clinical trials of new disease-modifying therapies. The higher the number of comparisons of different confounders in statistical analyses, the lower P values will be significant. Proper selection of confounders is crucial to accurately assess MCIDs without compromising statistical significance. Statistical adjustment of the significance of MCIDs according to multiple comparisons is essential for the generalizability of research results. Wider inclusion of confounding variables in the statistics may help bring trial results closer to real-world conditions and improve the prediction of the efficacy of new disease-modifying therapies, though such factors must be carefully selected not to compromise the statistical significance of the analyses. Anthropometric, demographic, and clinical features may affect cognitive, behavioral, and functional decline.Clinical trials seldom take minimal clinically important differences (MCIDs) or their confounders into account.Generalizability of research results requires the assessment of multiple confounding factors.The higher the number of comparisons involved, the lower P values will be considered significant.Use of MCIDs adjusted for confounding factors should be implemented when outcomes are not susceptible to translation into absolute benefits.

Impact of intravascular ultrasound on limb events in endovascular therapy for patients with peripheral arterial disease: insights from the TOMA-CODE registry.

Intravascular ultrasound (IVUS) has become a standard procedure for performing coronary intervention, but its impact on peripheral endovascular therapy (EVT) remains unclear. To assess the usefulness of IVUS during EVT, this study analyzed over 2000 consecutive patients from the TOkyo-taMA peripheral vascular intervention research COmraDE (TOMA-CODE) registry with peripheral arterial disease (PAD) in Japan. The primary outcome was chronic limb events (a composite of clinically driven target lesion revascularization (cTLR) and major amputation) during a two-year follow-up period. The secondary outcomes included the procedural success rate, in-hospital major adverse limb events (MALE), and major cardiac and cerebrovascular events (MACCE). Patients with and without IVUS were compared using propensity score matching. Among the 2227 eligible cases enrolled, with a median follow-up period of 10.4months, there were no significant differences in limb events between IVUS (784 patients) and non-IVUS (1443 patients) groups during the follow-up period (15.4% vs. 14.4%, P = 0.53, unadjusted; 14.8% vs. 15.4%, P = 0.77, adjusted). In contrast, the IVUS group had higher procedural success rates (98.7% vs. 96.7%, P = 0.02) and lower in-hospital MALE (1.6% vs. 4.1%, P = 0.01), even after multiple adjustments. Additionally, there was no significant difference in the MACCE incidence (10.9% vs. 12.2%, P = 0.47) between the groups. This study demonstrated that IVUS usage did not reduce the occurrence of limb events among EVT patients in the chronic phase, but IVUS may improve in-hospital outcomes. Further research is necessary to verify these findings.

Mothers balancing work and family: the associations with emotional well-being, sleep–wake problems and the role of basic needs

BackgroundThe transition to motherhood involves significant changes, extending from pregnancy to the early years of a child's life. This period, characterized by multiple stressors and adjustments, can profoundly impact maternal well-being. For this reason, the aim of this study was to investigate the associations between work-family balance, need satisfaction, depression, anger, vitality and sleep–wake problems, using Self-determination Theory (SDT) as a theoretical framework.MethodsParticipated in this study 218 working mothers in Italy with children aged between 1 and 36 months. Using a correlational design, SEM with latent variables was used to test an integrative model.ResultsResults revealed significant positive associations between work-family balance and need satisfaction, and vitality, and negative direct associations of need satisfaction with sleep–wake problems, depression, and anger. Indirect associations were also visible between work-family balance and psychological outcomes through need satisfaction.Conclusions.Overall, findings underscore the importance of conditions that support the satisfaction autonomy, competence, and relatedness of working mothers during this critical life stage. These insights have implications for organizational policies and interventions aimed at supporting the mental health of working mothers.

Adaptive high flow oxygen therapy: New concept

Background High-flow oxygen therapy (HFOT) is increasingly utilized in clinical settings due to its potential to improve oxygenation, patient comfort and possibly outcomes in different respiratory failure states. The potential benefits of HFOT include matching the patients’ flow to reduce the work of breathing, creating airway pressure, humidification, and reducing dead space. However, it has some shortcomings including the difficulty of setting the flow to match patients’ efforts, the continuous flow does not represent normal physiologic spontaneous breathing, and the lack of traditional airway pressure monitoring. We are testing a new adaptive high-flow oxygen delivery technique “Auto Positive Airway Pressure” (Auto-PAP) where the flow delivered from the ventilator adapts to patients’ efforts taking into consideration the patients’ dead space Methods A bench study using ASL 5000 simulator, we created a single-compartment active model of a male with IBW 70 kg, with compliance of 40 ml/cmH20 and resistance of 10 cmH2o/L/s. The respiratory rate was set at 20 bpm, with inspiratory time of 1 second. Muscle pressure (Pmus) was gradually increased by increments of 5 cmH2O from 5 to 50. Adaptive high flow mode (Auto PAP) using a Bellavista 1000e ventilator (Zoll MA, USA) using a large bore nasal cannula to an adult-sized mannequin nose that was connected to the lung simulator. Pearson correlation coefficient was used in correlating the Pmus to the maximum, mean flow and pressure, and the simulator to the ventilator flow. Results There was significant strong correlation between the Pmus and the maximum flow R: 0.949, CI (0.794, 0.988) P &lt; 0.001, and mean flow R: 0.955, P &lt; 0.001, CI (0.816, 0.989). There was a significant strong correlation with Pmus and the maximum pressure R: 0.972, P &lt; 0.001, CI (0.883, 0.993) and mean pressure R: 0.942, P &lt; 0.001, CI (0.768, 0.986). There was significant strong correlation between the simulator and the ventilator flow R: 0.961, P &lt; 0.001. There was significant strong correlation between the simulator and the ventilator mean pressure R: 0.951, P &lt; 0.001, CI (0.799, 0.988). There was significant strong correlation between the mean flow from the ventilator to the mean airway pressure measured at the simulator R: 0.936, P &lt; 0.001 CI (0.747, 0.985). Conclusion Results suggest a significant correlation between the flow and pressure from adaptive HFOT and the patient muscle effort, indicating that the flow and pressure increase in response to the patients’ effort. This may reduce respiratory muscle workload compared to traditional high flow oxygen therapies and reduce the need for multiple manual adjustment of the flow. These findings underscore the potential of this technology to enhance respiratory support while minimizing patient effort. Further research is warranted to validate these findings in real patient cohorts in diverse clinical scenarios. Keywords: High flow oxygen therapy, mean flow, mean pressure

Efficacy and Safety of Sotatercept Across Ranges of Cardiac Index in Patients with Pulmonary Arterial Hypertension: A Pooled Analysis of PULSAR and STELLAR

BackgroundThis analysis compared effects of the activin signaling inhibitor, sotatercept, across pulmonary arterial hypertension (PAH) subgroups stratified by baseline cardiac index (CI). MethodsPooled data from PULSAR (N=106; NCT03496207) and STELLAR (N=323; NCT04576988) were analyzed using two different CI thresholds, < and ≥ 2.0 L/min/m2 or 2.5 L/min/m2. Median differences in change from baseline at week 24 were evaluated using Hodges-Lehmann (HL) estimator and mean differences by least squares (LS), with 95% confidence intervals and p-values; p=0.05 was significant. Categorial endpoints and time-to-clinical worsening were analyzed by Cochran-Mantel-Haenszel and Cox model (hazard ratio (HR), respectively, without multiplicity adjustment. ResultsOf 429 participants, 51 and 378 had CI <2.0 L/min/m2 and ≥ 2.0 L/min/m2, respectively, whereas 179 and 250 had CI <2.5 L/min/m2 and ≥ 2.5 L/min/m2, respectively. Across all CI subgroups, sotatercept vs placebo significantly improved median 6-minute walk distance (range: 33.9 to 63.7 m: p<0.001), pulmonary vascular resistance (range: -202.8 to -395.4 dyn•s•cm-5; p≤0.002), and N-terminal pro-B-type natriuretic peptide (range: -317.3 to -1041.2 pg/mL; p<0.001). LS means showed reductions in pulmonary and right atrial pressures, decreased right ventricular size and enhanced tricuspid annular plane systolic excursion/ systolic pulmonary artery pressure in all subgroups. Sotatercept significantly delayed time to first occurrence of death or a worsening event in the subset of participants with CI ≥2.5 (HR 0.12; p<0.001), ≥2.0 (HR 0.13; p<0.001), and <2.5 (HR 0.21; p<0.001) L/min/m2. Improvements in World Health Organization functional class (all p<0.050) and European Society of Cardiology/European Respiratory Society risk score (all p<0.001) were seen within each subgroup. ConclusionsEfficacy and safety were consistent across baseline CI subgroups, supporting use of sotatercept in PAH patients irrespective of baseline cardiac hemodynamics.

Association of 24-h movement behaviors during Covid-19 pandemic with spinal musculoskeletal disorders in undergraduate students: a cross-sectional study.

Musculoskeletal disorders (MSD) are an important health problem, and the Covid-19 pandemic affected several lifestyle and health aspects worldwide, including moderate-to-vigorous physical activity (MVPA), sedentary behavior (SB) and sleep time, which compose the 24-h movement guidelines (24-hMG). It is unclear whether meeting 24-hMG during pandemic have been associated with MSD in adult population and this study aimed to analyze the association of meeting 24-hMG with spinal MSD in undergraduate students during Covid-19 pandemic. A sample of 71 undergraduate students were assessed (24.0 ± 6.6 years, 52% of women). MVPA was assessed by accelerometer, while daily time of SB and sleep were assessed by questionnaires. Spinal MSD was assessed by the Nordic questionnaire. Logistic regression models analyzed the association of meeting 24-hMG (individually and combined) with MSD, independently of age, sex, and body mass index. Spinal MSD affected 78.9% of sample. Only 11.3% of sample fully met the 24-hMG. Participants who did not meet both MVPA and SB guidelines were more likely to have MSD in low back (OR:3.45, p = 0.049) and spine (OR:3.78, p = 0.048) even after multiple adjustment. Otherwise, not meeting SB guideline was inversely associated with upper back MSD (OR:0.22, p = 0.012). Meeting 24-hMG during Covid-19 pandemic were differently associated with spinal MSD, where combination of MVPA and SB shows to be protective against MSD in low back and in spine. However, the determinants of association between meeting SB guideline and higher upper back MSD still needs to be investigated.

Practical considerations of promising zone design for interim sample size Re-estimation: An application to GRAPHITE for graft vs host disease

BackgroundSample size calculation and power estimate are an integral part of clinical trials. With accelerated development to address the unmet medical needs, the fast-paced development may lead to uncertainties in initial planning and assumptions of clinical trials. Promising zone design presents sponsors an opportunity to re-estimate the sample size based on the interim data to mitigate risks, reduce uncertainties, and increase probability of trial success. MethodsThis paper aims to use the GRAPHITE trial (NCT03657160) as a real data application to showcase the practical considerations in implementation of promising zone design for interim sample size re-estimation (SSR), in light of sample size adaptation rules, maximum sample size allowed, multiplicity adjustment, and sponsor access to interim results. GRAPHITE is a phase 3 trial with vedolizumab for prophylaxis of acute graft vs host disease (aGvHD) after allogeneic hematopoietic stem cell transplant (allo-HSCT). The primary efficacy endpoint is lower intestinal aGVHD-free survival by Day +180 after allo-HSCT. A simulation study was conducted to demonstrate the evaluation of operating characteristics by various true underlying treatment effects at the design stage. ConclusionThe application of promising zone design for interim SSR is novel and has successfully helped the sponsor achieve the balance between minimizing the risks and maintaining scientific integrity. This work aims to highlight the necessity of empirical guidance to gain better insights for clinical researchers in practice and is expected to facilitate the understanding and implementation of promising zone design for interim SSR in phase 3 trials.

Evaluating multiplicity reporting in analgesic clinical trials: An analytical review.

Analgesia trials often demands multiple comparisons to assess various treatment arms, outcomes, or repeated assessments. These multiple comparisons risk inflating the false positive rate. Multiplicity correction in recent analgesic randomized controlled trials (RCTs) remains unclear despite statistical method advancements and regulatory guidelines. Our study aimed to identify reporting inadequacies in multiple analysis adjustments and explanations to understand these deficiencies. This review analysed RCTs from the European Journal of Pain, the Journal of Pain, and PAIN, published between January 2018 and December 2022. We included randomized, double-blind trials focusing on pain outcomes. Data extraction, managed by three researchers using predefined criteria, included trial characteristics, multiplicity presence, and correction methods. Descriptive statistical analyses included Fisher's exact, and Holm method for multiple comparisons. Out of 112 articles, 48 pre-specified a primary analysis plan. Multiple analyses were observed in 65 articles, with 60% adjusting for all comparisons, primarily using the Bonferroni method. Compared with previous studies, no significant changes in multiplicity correction practices were noted when stratified by trial type, size, and sponsor. The study reveals a persistent reliance on multiple comparisons in analgesic clinical trials without a corresponding increase in multiplicity corrections emphasizing a need for enhanced reporting and implementation of statistical adjustments. We acknowledge limitations in categorizing studies, the use of a surrogate for the trial stage, and sourcing data from journal webpages rather than a database. This study flags inadequate reporting on multiplicity correction in analgesic trials, stressing the risk of false positives and the urgent need for enhanced reporting to boost reproducibility.

Two-stage group ordinal consensus optimization ranking approach considering multiple optimal consistency adjustment solutions

In group decision making, decision makers can use pairwise comparisons to express their preferences. Reaching the consistency of decision makers and consensus of decision groups are two important processes for obtaining reliable decision-making results. Consistency and consensus optimization approach based on minimizing preference adjustment is one of the dominant approaches to obtaining ranking results by deriving priorities. In existing researches, maintaining consistency in preference adjustment during ordinal consensus optimization processes has been rarely noticed, and the choice of the consistency adjusted preferences from multiple optimal solutions has not been considered. To deal with these issues, this paper proposes a two-stage group ordinal consensus optimization ranking approach which considers multiple optimal consistency adjustment solutions to achieve individual preference consistency and group ordinal consensus. In the first stage, a minimum adjustment consistency optimization model is developed to obtain the minimum adjustment based on the concept of strong ordinal consistency. In the second stage, an ordinal consensus optimization ranking model is developed to obtain the optimal consistency and consensus adjustment solutions by minimizing the preference adjustments based on an improved consensus measure. Finally, a numerical example about lithium-ion battery recycling strategy selection is applied to illustrate the feasibility of the proposed approach. Moreover, the comparisons with other approaches are given to show the advantage and the sensitivity analysis is used to verify the effectiveness of the proposed approach.

Influence of Bone Conditions on the Accuracy of Implant Placement.

This study aimed to assess the influence of cortical bone thickness, bone density, and residual ridge morphology in the posterior mandibular area on the accuracy of implant placement using tooth-supported digital guides. The research included 75 implants from 55 patients. Each patient underwent a cone-beam computed tomography (CBCT) scan for image analysis. Simplant® Pro 17 software (SIMPLANT Pro 17.01) was utilized to measure cortical bone thickness, bone density, and residual ridge morphology at the implant sites. Subsequently, 3Shape Trios software (3Shape TRIOS Design Studio 1.7.19.0) was applied to delineate optimal implant positions and design tooth-supported surgical guides. After implant treatment, the linear and angular deviations from the planned placement were quantified. Multiple linear regression, Kruskal-Wallis test, Conover-Iman test, and Bonferroni adjustment were conducted to investigate the impact of bone characteristics on implant placement precision. The tooth-supported digital guides used in this study were sufficient to fulfill the precision criteria for implant treatment. Bone density was found to significantly influence the buccal-lingual angular deviation, mesio-distal linear deviation, and mesio-distal angular deviation (p < 0.05). Additionally, significant variances were noted in the coronal deviation, apical deviation and depth deviation in buccal-lingual orientation, coronal deviation, and apical deviation in mesio-distal orientation across various residual ridge morphologies (p < 0.05). Low bone density and S-shape morphology may affect the accuracy of implant placement using tooth-supported surgical guides.

LarvaeCountAI: a robust convolutional neural network-based tool for accurately counting the larvae of Culex annulirostris mosquitoes

Accurate counting of mosquito larval populations is essential for maintaining optimal conditions and population control within rearing facilities, assessing disease transmission risks, and implementing effective vector control measures. While existing methods for counting mosquito larvae have faced challenges such as the impact on larval mortality rate, multiple parameters adjustment and limitations in availability and affordability, recent advancements in artificial intelligence, particularly in AI-driven visual analysis, hold promise for addressing these issues. Here, we introduce LarvaeCountAI, an open-source convolutional neural network (CNN)-based tool designed to automatically count Culex annulirostris mosquito larvae from videos captured in laboratory environments. LarvaeCountAI does not require videos to be recorded using an advanced setup; it can count larvae with high accuracy from videos captured using a simple setup mainly consisting of a camera and commonly used plastic trays. Using the videos enables LarvaeCountAI to capitalise on the continuous movement of larvae, enhancing the likelihood of accurately counting a greater number of larvae. LarvaeCountAI adopts a non-invasive approach, where larvae are simply placed in trays and imaged, minimising any potential impact on larval mortality. This approach addresses the limitations associated with previous methods involving mechanical machines, which often increase the risk of larval mortality as larvae pass through multiple sections for counting purposes. The performance of LarvaeCountAI was tested using 10 video samples. Validation results demonstrated the excellent performance of LarvaeCountAI, with an accuracy ranging from 96.25 % to 99.13 % across 10 test videos and an average accuracy of 97.88 %. LarvaeCountAI represents a remarkable advancement in mosquito surveillance technology, offering a robust and efficient solution for monitoring larval populations. LarvaeCountAI can contribute to developing effective strategies for reducing disease transmission and safeguarding public health by providing timely and accurate data on mosquito larvae abundance.

Abstract 4138589: Prognostic implications of Biventricular systolic and diastolic strain in diabetes without coronary artery diseases.

Background: 2D-speckle-tracking echocardiography (2D-STE) has emerged as useful to assess subclinical myocardial dysfunction, however its utility in diabetes milletus (DM) has been limited to the evaluation of left ventricular (LV) longitudinal systolic function. Aim: To assess the differences and prognostic implications of left (LV) and right (RV)ventricular systolic and diastolic strain parameters in DM. Methods: Of the initial 1721 DM patients screened for this study only 513 consecutive patients with DM were eligible and retrospectively enrolled, and 2D-STE strain (longitudinal, circumferential and radial) parameters assessed on the 2D-TTE images. All patients were prospectively followed for development of new outcome/cardiac events which included hospitalization for acute HF, CVS-related death, heart transplantation, and also diabetic complications. The 2D-STE analysis was used to measure the peak LV (longitudinal, radial and circumferential) and RV (longitudinal and radial) strain parameters. The long-term outcomes were evaluated for all-cause CVS outcomes and recurrent hospitalization. Results: For the 513 eligible patients [mean age: 51±8; 62 % male sex], 263 reached the combined endpoint during a mean follow-up of 1.4±0.6years. Conventional TTE was performed in all subjects and reviewed. Both LV and RV strain parameters were significantly impaired compared to normal standard references (p&lt;.0001), where RV was more impaired than LV strain parameters. Th e best performance parameters predictive of CVS events were RV systolic and diastolic strain than global LV longitudinal systolic and diastolic strain. The strongest association between the degree of myocardial dysfunction and CVS risk was more evident for RV strain (free wall &gt; global strain) and lesser extend to LV strain. More myocardial strain impairments were demonstrated in those with higher left atrial volume index, impaired diastolic function, lower strain values ( LV, RV), and reduced tricuspid annular plane systolic excursion, p&lt;.001). RV strain and to a lesser extend LV strain impairment were independent predictors of combined outcomes after multiple adjustments using different models. Conclusion: Patients with Diabetes, RV and LV strain parameters are stronger (RV&gt;LV strain) predictors of outcome than other conventional parameters and should be included for regular clinical screening DM patients as these parameters provide a stronger prognostic stratification