Multiple Weight Research Articles

Comparative effectiveness ofbiological disease-modifying antirheumatic drugs and Janus kinase inhibitor monotherapy in rheumatoid arthritis.

The objective of this study was to examine the effectiveness and drug tolerability of biological DMARD (bDMARD) and Janus kinase inhibitor (JAKi) monotherapy in patients with RA in a multicentre cohort study. Patients with RA for whom bDMARD/JAKi monotherapy without conventional synthetic DMARDs has been initiated were included. Monotherapy regimens were categorized as IL-6 receptor inhibitors (IL-6Ris), cytotoxic T-lymphocyte-associated protein 4 immunoglobulin (CTLA4Ig), JAKis, or TNF inhibitors (TNFis). Multiple propensity score-based inverse probability weighting (IPW) was used to reduce selection bias. Linear mixed-effect models with IPW were used to examine changes in the DAS in 28 joints using ESR (DAS28)-ESR at 24 weeks, and drug retention was compared between monotherapy groups using IPW Cox proportional hazards models. A total of 849 treatment courses were included, involving 635 patients (IL-6Ris, 218; CTLA4Ig, 183; JAKis, 92; TNFis, 356). The change in DAS28-ESR at week 24 as the primary outcome was -0.93 (95% CI: -1.20 to -0.66) lower in the IL-6Ri group than in the TNFi group, while those of the CTLA4Ig and JAKi groups were similar to that of the TNFi group [-0.20 (-0.48 to 0.08), -0.25 (-0.67 to 0.16), respectively]. IL-6Ri use was associated with significantly lower overall drug discontinuation than that for TNFi use [hazard ratio = 0.55 (0.39-0.78), P = 0.001]. Similar retention rates were identified for the CTLA4Ig and JAKi groups to that of the TNFi group. In the analysis with IPW to reduce selection bias, IL-6Ri monotherapy was superior to TNFi monotherapy in terms of effectiveness and drug retention. No significant differences were identified between CTLA4Ig, JAKi and TNFi monotherapy.

Urban-rural differences in associations among perceived stress, resilience and self-care in Chinese older adults with multiple chronic conditions.

Social determinants of health (SDH) are mainly comprised of structural and intermediary domains. Emerging evidence suggests that the burden of multiple chronic conditions (MCCs) in older adults is exacerbated by structural determinants (e.g. low income and low education). However, less attention was paid to the intermediary determinants (i.e. material circumstances, psychosocial factors and behavioural factors) of MCCs. To investigate the associations among perceived stress, resilience and self-care in Chinese older adults with MCCs by comparing urban and rural groups. A convenience sample (125 and 115 participants from urban and rural settings, respectively) of Chinese older adults with MCCs was enrolled between January and April 2022. Hierarchical multiple regression analyses and propensity score weights were used to determine the associations among perceived stress, resilience and self-care. Hypothesis 1 regarding the negative associations between perceived stress and self-care was fully supported in the rural group. However, for the urban group, the negative association was only supported for the relationship between MCCs-related perceived stress and self-care maintenance. Hypothesis 2 was fully supported regarding the positive associations between resilience and the three components of self-care in both groups, although the relationship between resilience and self-care monitoring was marginally significant in the urban group. Hypothesis 3 regarding the moderating effect of resilience was only supported in the relationship between general perceived stress and self-care monitoring in the rural group. After adding the propensity score weights, the moderating effect was no longer statistically significant in the rural group. The urban-rural disparities in the Chinese context might largely be attributed to the complex interactions of the structural determinants and intermediary determinants. Findings can inform the development of culturally tailored interventions to promote self-care and reduce urban-rural disparities for Chinese older adults with MCCs. With the increasing number of older adults in China who are living with multiple chronic conditions and the call for effective interventions to improve their health outcomes, current findings can inform the development and implementation of nurse-led culturally tailored interventions to promote self-care and reduce urban-rural disparities for Chinese older adults with MCCs.

Causal association of physical activity with low back pain, intervertebral disc degeneration and sciatica: a two-sample mendelian randomization analysis study.

Objective: Previous studies are insufficient to confirm a causal association between physical activity (PA) and low back pain (LBP), intervertebral disc degeneration (IDD), and sciatica. The present study used a two-sample Mendelian randomization (MR) analysis method to demonstrate whether or not there was a causal connection. Methods: First, four PA phenotypes were selected [accelerometer-based PA (average acceleration), accelerometer-based PA (acceleration fraction >425mg), self-reported moderate-to-vigorous PA, and self-reported vigorous PA], setting thresholds for single nucleotide polymorphisms (SNPs) significantly concerned with PA p < 5 × 10-8, linkage disequilibrium (LD) r 2 < 0.01, genetic distance >5,000kb, and F-value >10. SNPs associated with the outcome and confounding factors were then excluded using the PhenoScanncer database. Finally, after coordinating the genetic instruments from genome-wide association studies (GWAS) effect alleles for exposure and outcomes, multiplicative random effects inverse variance weighting (IVW), MR-Egger, weighted median method (WMM), and weighted mode method were used to assess exposure-outcome causality and perform sensitivity analysis on the estimated results. Results: The current study's IVW findings revealed proof of a causal connection between PA and LBP. While there was a positive causal tie between accelerometer-based PA (acceleration fraction >425mg) and LBP [OR: 1.818, 95% CI:1.129-2.926, p = 0.012], there was a negative causal link between accelerometer-based PA (average acceleration) and LBP [OR: 0.945, 95% CI: 0.909-0.984, p = 0.005]. However causal relationship between PA and IDD or sciatica was not found. Conclusion: Increasing average PA but needing to avoid high-intensity PA may be an effective means of preventing low back pain. Although PA is not directly causally related to disc degeneration and sciatica, it can act through indirect pathways.

The association between thyroid and breast cancers: a bidirectional mendelian randomization study.

Thyroid and breast cancers are the two most frequent types of endocrine-related tumors among women worldwide, and their incidence is still on the rise. Observational studies have shown a relationship between thyroid and breast cancers. Nevertheless, many confounders predispose the results to interference. Accordingly, we performed a two-sample Mendelian randomization (MR) study to investigate the causal association between thyroid and breast cancers. We acquired breast cancer data from the UK Biobank (13,879 breast cancer cases and 198,523 controls) and the Breast Cancer Association Consortium (BCAC; 122,977 breast cancer cases and 105,974 controls), and thyroid cancer data from FinnGen Biobank (989 thyroid cancer and 217,803 controls). Then, the multiplicative random effects inverse variance weighting (IVW), weight median (WM), and MR Egger methods were executed for MR analysis. Overall, IVW showed a causal effect of breast cancer on thyroid cancer using the BCAC dataset (odds ratio [OR] = 1.17; 95% confidence interval [CI] = 1.036-1.322; P = 0.011), and this relationship was also supported by the UK Biobank dataset (OR = 23.899; 95% CI = 2.331-245.003; P = 0.007), which showed that breast cancer patients were more likely to be diagnosed with thyroid cancer. On the whole, the reverse MR analysis did not show a causal effect of breast cancer on thyroid cancer. However, IVW showed a causal effect of thyroid cancer on estrogen receptor -negative breast cancer using the BCAC dataset (OR = 1.019; 95% CI = 1.001-1.038; P = 0.043), which suggested that people with thyroid cancer were more likely to develop breast cancer. Breast cancer represents a possible risk factor for thyroid cancer and thyroid cancer also represents a possible risk factor for ER-negative breast cancer. Future studies using powerful genetic tools to determine the causal relationship between breast and thyroid cancers are required.

A weight Monte Carlo estimation of fluctuations in branching processes

Abstract It is well known that shortened modeling of particle trajectories with the use multiplicative statistical weights, as a rule, increases the efficiency of the program (in terms of accuracy/time ratio). This trick is often used in non-branching schemes simulating transfer processes without multiplication (for example, the transfer of X-ray radiation), in which it is sufficient to confine ourselves to studying only the average values of the field characteristics. With an increase in energy, however, multiplication processes begin to play a significant role (the production of electron-photon pairs by gamma quanta with energies above 1.022 MeV, etc.), when the resulting trajectory is not just a broken curve in the phase space, but a branched tree. This technique is also applicable to this process, but only if the study of statistical fluctuations and correlations is not the purpose of the calculation. The present review contains the basic concepts of the Monte Carlo method as applied to the theory of particle transport, demonstration of the weighting method in non-branching processes, and ends with a discussion of unbiased estimates of the second moment and covariance of additive functionals.

Parametric study of the effects of clump weights on the performance of a novel wind-wave hybrid system

This paper presents a novel catenary mooring system incorporating multiple clump weights (CWs) designed for a SPIC-Wavestar wind-wave energy hybrid system. To enhance the performance of the hybrid system, a parametric analysis was performed on mooring CWs. The motions of the SPIC platform, along with the power absorbed by the Wavestar wave energy converters (WECs), specifically in response to the operational regular wave, were simulated. The hydrodynamic analysis program AQWA was used for the analysis. The results indicated that the surge and pitch motions of the platform comprised low-frequency and wave-frequency components, whereas the heave motion only comprised a wave-frequency component. However, the low-frequency responses of the surge and pitch motions were substantially smaller than their wave-frequency counterparts. In addition, the properties of the CW exerted notable influence on both platform motion and the overall power absorption by the WEC array. The variation trends with respect to the CW weight, location, and number were complex. Overall, the results of this study provide valuable insights into the mooring design of ocean energy hybrid systems.

The effects of different endometrial preparation regimens on pregnancy outcomes in frozen-thawed embryo transfer cycles: a prospective randomized controlled study

Objective An increasing number of research have emerged to compare the pregnancy outcomes between the natural cycle and the hormone replacement therapy (HRT) cycle in preparing the endometrium for frozen-thawed embryo transfer (FET), but the results are controversial. This prospective randomized controlled study was hence designed to obtain more solid evidence. Materials and methods In this study, patients with regular menstrual cycle length (21–35 days) who underwent FET between January 2010 to December 2017 were recruited for this study. Upon further filtering with the selection criteria of patients being, a total of 405 patients were recruited and randomized. Finally, analysis was performed on 384 patients: 178 belonged to the natural cycle group whereas the remaining 206 were in the HRT group. The primary outcome was live birth rate, while the secondary outcomes were implantation rate, clinical pregnancy rate, early miscarriage rate, late miscarriage rate, multiple birth rate and low birth weight rate. Results The live birth rate (37.6% vs 30.1%, p = 0.119) of natural cycle group were higher than those of the hormone replacement therapy group, although the difference was not significant. The secondary outcomes were not found to differ significantly between the two groups. Nonetheless, the endometrium was found to be thicker in the natural cycle group (10.75 mm) than the HRT group (9.00 mm) (p < 0.001). Conclusion No significant differences were observed between the pregnancy outcomes of the natural cycle group and the HRT group which comprised of patients with regular menstrual cycle length.

A group consensus model with prospect theory under probabilistic linguistic term sets

The challenges encountered in the realm of multi-attribute group decision-making (MAGDM) involving probabilistic linguistic term sets (PLTSs) have garnered substantial attention. Within the PLTS context, this study introduces a consensus reaching process (CRP) that iteratively refines the weights assigned to decision-makers (DMs) by leveraging the principles of prospect theory (PT). The primary goal of this iterative weight adjustment process is to enhance the overall decision-making procedure when dealing with PLTSs. To circumvent any data loss during transformation and compute the prospect values of PLTSs directly, a novel transformation formula is developed. Acknowledging the distinct cognitive levels among different DMs, the integration of multiple weights into the consensus process is characterized by its dynamic and iterative nature. Concerning the measurement of consensus, this study employs a method based on the gap between prospect values, which enhances objectivity while overcoming the limitations associated with the distance formula of PLTSs. Furthermore, the feedback mechanism incorporated into the modification process incorporates dynamic adjustment parameters that are tailored to different evaluation values, thereby preventing excessive adjustments that are either too low or too high. By utilizing the newly proposed prospect value function, this research aggregates the group evaluation value and identifies the optimal alternative. In conclusion, this paper concludes with a comparative analysis involving various counterparts, shedding light on the feasibility and validity of the proposed model.

Association of per- and polyfluoroalkyl substance exposure with metabolic syndrome and its components in adults and adolescents

Per- and polyfluoroalkyl substances (PFAS) are widespread contaminants, but few studies have explored the relationship between PFAS and levels of metabolic syndrome (MetS) in the population. The available evidence of an association is also conflicting. We selected adults and adolescents with complete PFAS data from the National Health and Nutrition Examination Survey conducted between 2003 and 2018. We analyzed the association between PFAS and MetS using multivariate logistic regression models and evaluated potential nonlinear relationships with restricted cubic spline models. Additionally, we employed weighted quantile sum (WQS) regressions to uncover the multiple exposure effects and relative weights of each PFAS. Finally, we conducted a series of sensitivity analyses to test the robustness of our findings. In this population-based study, we analyzed data from a total of 4,973 adults, aged 20–85 years, and 1,381 adolescents, aged 12–19 years. Using fully adjusted multivariate logistic regression models, we found that serum levels of perfluorodecanoate (PFDA) [0.65 (0.50, 0.85)] and total PFAS [0.92 (0.85, 0.99)] were negatively associated with the prevalence of MetS in adults. Similarly, in adolescents, we observed negative correlations between the prevalence of MetS and levels of PFDA [0.55 (0.38, 0.80)], perfluorooctanoic acid (PFOA) [0.62 (0.39, 1.00)], perfluorooctane sulfonic acid (PFOS) [0.59 (0.36, 0.96)], and total PFAS [0.61 (0.37, 0.99)]. Additionally, our study identified statistically significant negative associations between serum levels of PFAS and certain components of MetS, primarily elevated fasting glucose and lower high-density lipoprotein cholesterol. Our study found that PFAS was associated with a lower prevalence of MetS in both adults and adolescents, offering new insights into the relationship between PFAS and metabolic health. Interestingly, however, we observed conflicting findings across the components of MetS. Specifically, we observed that PFAS had a negative correlation with some metrics and a positive correlation with others. These conflicting results point to a complex interplay between PFAS and various metrics of metabolic health.

Detection of Malignant Skin Lesions Based on Decision Fusion of Ensembles of Neural Networks.

Today, skin cancer, and especially melanoma, is an increasing and dangerous health disease. The high mortality rate of some types of skin cancers needs to be detected in the early stages and treated urgently. The use of neural network ensembles for the detection of objects of interest in images has gained more and more interest due to the increased performance of the results. In this sense, this paper proposes two ensembles of neural networks, based on the fusion of the decisions of the component neural networks for the detection of four skin lesions (basal cancer cell, melanoma, benign keratosis, and melanocytic nevi). The first system is based on separate learning of three neural networks (MobileNet V2, DenseNet 169, and EfficientNet B2), with multiple weights for the four classes of lesions and weighted overall prediction. The second system is made up of six binary models (one for each pair of classes) for each network; the fusion and prediction are conducted by weighted summation per class and per model. In total, 18 such binary models will be considered. The 91.04% global accuracy of this set of binary models is superior to the first system (89.62%). Separately, only for the binary classifications within the system was the individual accuracy better. The individual F1 score for each class and the global system varied from 81.36% to 94.17%. Finally, a critical comparison is made with similar works from the literature.

A Deep-Learning Phase Picker with Calibrated Bayesian-Derived Uncertainties for Earthquakes in the Yellowstone Volcanic Region

ABSTRACT Traditional seismic phase pickers perform poorly during periods of elevated seismicity due to inherent weakness when detecting overlapping earthquake waveforms. This weakness results in incomplete seismic catalogs, particularly deficient in earthquakes that are close in space and time. Supervised deep-learning (DL) pickers allow for improved detection performance and better handle the overlapping waveforms. Here, we present a DL phase-picking procedure specifically trained on Yellowstone seismicity and designed to fit within the University of Utah Seismograph Stations (UUSS) real-time system. We modify and combine existing DL models to label the seismic phases in continuous data and produce better phase arrival times. We use transfer learning to achieve consistency with UUSS analysts while maintaining robust models. To improve the performance during periods of enhanced seismicity, we develop a data augmentation strategy to synthesize waveforms with two nearly coincident P arrivals. We also incorporate a model uncertainty quantification method, Multiple Stochastic Weight Averaging-Gaussian (MultiSWAG), for arrival-time estimates and compare it to dropout—a more standard approach. We use an efficient, model-agnostic method of empirically calibrating the uncertainties to produce meaningful 90% credible intervals. The credible intervals are used downstream in association, location, and quality assessment. For an in-depth evaluation of our automated method, we apply it to continuous data recorded from 25 March to 3 April 2014, on 20 three-component stations and 14 vertical-component stations. This 10-day period contains an Mw 4.8 event, the largest earthquake in the Yellowstone region since 1980. A seismic analyst manually examined more than 1000 located events, including ∼855 previously unidentified, and concluded that only two were incorrect. Finally, we present an analyst-created, high-resolution arrival-time data set, including 651 new arrival times, for one hour of data from station WY.YNR for robust evaluation of missed detections before association. Our method identified 60% of the analyst P picks and 81% of the S picks.

N-Acetylcysteine Displaces Glutathionyl-Moieties from Hg2+ and MeHg+ to Form More Hydrophobic Complexes at Near-Physiological Conditions.

The anthropogenic release of Hg is associated with an increased human exposure risk. Since Hg2+ and MeHg+ have a high affinity for thiols, their interaction with L-glutathione (GSH) within mammalian cells is fundamentally involved in their toxicological chemistry and excretion. To gain insight into the interaction of these mercurials with multiple small molecular weight thiols, we have investigated their competitive interactions with GSH and N-acetylcysteine (NAC) at near-physiological conditions, using a liquid chromatographic approach. This approach involved the injection of each mercurial onto a reversed-phase (RP)-HPLC column (37 °C) using a PBS buffer mobile phase containing 5.0 mM GSH to simulate cytosolic conditions with Hg being detected in the column effluent by an inductively coupled plasma atomic emission spectrometer (ICP-AES). When the 5.0 mM GSH mobile phase was amended with up to 10 mM NAC, gradually increasing retention times of both mercurials were observed. To explain this behavior, the experiment with 5.0 mM NAC and 5.0 mM GSH was replicated using 50 mM Tris buffer (pH 7.4), and the Hg-containing fractions were analyzed by electrospray ionization mass spectrometry. The results revealed the presence of Hg(GS)(NAC) and Hg(NAC)2 for Hg2+ and MeHg(GS) and MeHg(NAC) for MeHg+, which suggests that the coordination/displacement of GS-moieties from each mercurial by the more hydrophobic NAC can explain their retention behavior. Since the biotransformations of both mercurials were observed at near-physiological conditions, they are of toxicological relevance as they provide a biomolecular explanation for some results that were obtained when animals were administered with each mercurial and NAC.

Asymptotic synchronization and topology identification of stochastic hybrid delayed coupled systems with multiple weights

This article discusses a class of stochastic hybrid delayed coupled systems with multiple weights (SHDCSMW). Both white noise and telegraph noise are included in the coupled systems. By employing Kirchhoff’s Matrix-Tree Theorem, a global Lyapunov function is rebuilt indirectly, which is closely related to Markovian switching. Moreover, based on Lyapunov stability theory and stochastic analysis, several sufficient conditions with respect to asymptotic synchronization and topology identification of SHDCSMW are derived. Finally, the validity of theoretical results is proved by numerical examples.

Psychosocial Stressors at Work and Coronary Heart Disease Risk in Men and Women: 18-Year Prospective Cohort Study of Combined Exposures.

Psychosocial stressors at work, like job strain and effort-reward imbalance (ERI), can increase coronary heart disease (CHD) risk. ERI indicates an imbalance between the effort and received rewards. Evidence about the adverse effect of combined exposure to these work stressors on CHD risk is scarce. This study examines the separate and combined effect of job strain and ERI exposure on CHD incidence in a prospective cohort of white-collar workers in Quebec, Canada. Six thousand four hundred sixty-five white-collar workers without cardiovascular disease (mean age, 45.3±6.7) were followed for 18 years (from 2000 to 2018). Job strain and ERI were measured with validated questionnaires. CHD events were retrieved from medico-administrative databases using validated algorithms. Marginal Cox models were used to calculate hazard ratios (HR) stratified by sex. Multiple imputation and inverse probability weights were applied to minimize potential threats to internal validity. Among 3118 men, 571 had a first CHD event. Exposure to either job strain or ERI was associated with an adjusted 49% CHD risk increase (HR, 1.49 [95% CI, 1.07-2.09]). Combined exposure to job strain and ERI was associated with an adjusted 103% CHD risk increase (HR, 2.03 [95% CI, 1.38-2.97]). Exclusion of early CHD cases and censoring at retirement did not alter these associations. Among 3347 women, 265 had a first CHD event. Findings were inconclusive (passive job HR, 1.24 [95% CI, 0.80-1.91]; active job HR, 1.16 [95% CI, 0.70-1.94]; job strain HR, 1.08 [95% CI, 0.66-1.77]; ERI HR, 1.02 [95% CI, 0.72-1.45]). In this prospective cohort study, men exposed to job strain or ERI, separately and in combination, were at increased risk of CHD. Early interventions on these psychosocial stressors at work in men may be effective prevention strategies to reduce CHD burden. Among women, further investigation is required.

Multi-Parameter Auto-Tuning Algorithm for Mass Spectrometer Based on Improved Particle Swarm Optimization.

Quadrupole mass spectrometers (QMS) are widely used for clinical diagnosis and chemical analysis. To obtain the best experimental results, mass spectrometers must be calibrated to an ideal setting before use. However, tuning the current QMS is challenging. Traditional tuning techniques possess low automation levels and rely primarily on skilled engineers. Therefore, in this study, we propose an innovative auto-tuning algorithm for QMS based on the improved particle swarm optimization (PSO) algorithm to automatically find the optimal solution of QMS parameters and make the QMS reach the optimal state. The improved PSO algorithm is combined with simulated annealing, multiple inertia weights, dynamic boundaries, and other methods to prevent the traditional PSO algorithm from the issue of a local optimal solution and premature convergence. According to the characteristics of the mass spectrum peaks, a termination function is proposed to simplify the termination conditions of the PSO algorithm and further improve the automation level of the mass spectrometer. The results of auto-calibration testing of resolution and mass axis show that both resolution and mass axis calibration could effectively meet the requirements of mass spectrometry experiments. By the experiment of auto-optimization testing of lens and ion source parameters, these parameters were all in the vicinity of the optimal solution, which achieved the expected performance. Through numerous experiments, the reproducibility of the algorithm was established as meeting the auto-tuning function of the QMS. The proposed method can automatically tune the mass spectrometer from its non-optimal condition to the optimal one, which can effectively reduce the tuning difficulty of QMS.

Fermatean Fuzzy Fairly Aggregation Operators with Multi-Criteria Decision-Making

A Fermatean fuzzy set (FRFS) is the extension of a fuzzy set, an intuitionistic fuzzy set, and a Pythagorean fuzzy set, and is used in different fields. Unlike other fuzzy structures, the sum of cubes of membership grades in FRFSs approximates a unit interval, increasing uncertainty. In this study, we intend to provide unique operational rules and aggregation operators (AOs) inside a Fermatean fuzzy environment. To develop a fair remedy for the membership degree and non-membership degree features of “Fermatean fuzzy numbers (FRFNs)”, our solution introduces new neutral or fair operating principles, which include the concept of proportional distribution. Based on the suggested operating principles, we provide the “Fermatean fuzzy fairly weighted average operator and the Fermatean fuzzy fairly ordered weighted averaging operator”. Our suggested AOs provide more generalized, reliable, and exact data than previous techniques. Combining the recommended AOs with multiple decision-makers and partial weight information under FRFSs, we also devised a technique for “multi-criteria decision-making”. To illustrate the application of our novel method, we provide an example of the algorithm’s effectiveness in addressing decision-making challenges.

Evaluating the necessity of post-processing techniques on d4PDF data for extreme climate assessment.

The occurrence and severity of extreme precipitation events have been increasing globally. Although numerous projections have been proposed and developed for evaluating the climate change impacts, most models suffer from significant bias error due to the coarse resolution of the climate datasets, which affects the accuracy of the climate change assessment. Therefore, in this study, post-processing techniques (interpolation and bias correction methods) were adopted on the database for Policy Decision Making for Future Climate Change (d4PDF) model for extreme climatic flood events simulation in the Chao Phraya River Basin, Thailand, under + 4-K future climate simulation. Due to the limited number of the rain gages, the gradient plus inverse distance squared interpolation method (combination of multiple linear regression and distance weighting methods) was applied in this study. In the bias correction methods, the additional setting of monthly and seasonal periods was adjusted. The proposed bias correction approach deployed gamma distribution combined with generalized Pareto distribution setting with the seasonal period for the rainy season datasets, whereas only the gamma setting was applied with the monthly period during the dry season. The outcomes revealed that the proposed method could react to extreme rainfall events, expand dry days during dry season, and intensify rainfall amount during rainy season. The post-processing d4PDF trends of six sea surface temperature (SST) patterns (consists of 90 ensemble members) of two periods (near future: 2051-2070 and far future: 2091-2110) recorded the highest and lowest amounts of annual rainfalls of 4,450 mm/year in mid-stream of Nan River and 710 mm/year in the lower CPRB, respectively. Notably, the significant variances noted in the rainfall patterns among ensembles, demanding further investigation in future climate change, impact studies. The findings of the study provided novel insights on the importance of proper post-processing techniques for improving the robustness of d4PDF in climate change impacts assessment.

Embracing the Pros and Cons of the New Weight Loss Medications (Semaglutide, Tirzepatide, Etc.).

The history of multiple weight loss medications has been a concerning paradox based on an increased cardiovascular risk despite significant reductions in adipose tissue and weight. A new class of weight loss medications could change this past narrative based on early preliminary results of cardiovascular risk (not events-still need to be determined) and weight reduction in non-diabetics that acutely competes with results achieved with bariatric surgery. The purpose of this review is to provide a comprehensive summaryof the advantages and disadvantages of these newer medications, and how they could impact urology. Weight loss of - 15 to - 20% compared to baseline has become plausible in the short-term and preliminary guidance to reduce acute and chronic adverse events are receiving attention. However, the cost, access, conflicts of interest, supply chain, life-long adherence issues, and the long-term diverse implications on mental and physical health when exposed to this class of medications (GLP-1 agonists) are unknown. The profound caloric reductions should also result in baseline or ongoing nutritional deficiency testing, and general and specific dietary recommendations, which could theoretically mimic some bariatric surgery pre- and post-surgical protocols but has yet to be studied. Regardless, the potential impact of these medicines within a variety of medical specialties needs clinical research. Current and future lifestyle interventions, dietary patterns, and medicines in the weight loss category need to be held to a paradigm whereby cardiovascular health should improve with significant weight loss without a negative impact on mental health. In urology, the ability to impact cancer risk, ED, FSD, incontinence, infertility, nephrolithiasis, and multiple other endpoints are plausible (based on bariatric surgery data) but need preliminary clinical research. Other medicines with a similar or even larger potential impact are in clinical trials, and thus, a concise overview for clinicians and researchers was needed for objective guidance. Currently, comprehensive lifestyle changes utilized with and without these medications continue to garner positive mental, physical, and legacy effects, which suggest that they are as necessary as ever in the treatment of the numerous conditions impacted by unhealthy weight gain.

Successive Lag Synchronization for Multilayer Complex Networks With Multiple Weights

Successive Lag Synchronization for Multilayer Complex Networks With Multiple Weights

Dissipativity and synchronization of fractional-order output-coupled neural networks with multiple adaptive coupling weights

Different from the majority of existing results that focus on the passivity analysis of nonlinear systems, this paper attempts to analyze the more general QSR-dissipativity of fractional-order neural networks that own output coupling and multiple coupled weights, where outer coupling weights can be adjusted online by developing an adaptation law. Using the linear matrix inequality technique, several sufficient criteria that not only guarantee the QSR-dissipativity of the network system but also achieve global synchronization even under zero input are established. Of particular significance is the proposal of a fractional Lyapunov-like lemma, which plays a crucial role in verifying the asymptotic stability of synchronization errors. Finally, a simulation example is presented to verify the plausibility of the theoretical results.