Critical Value Research Articles

Defining the optimal segmentation method for measuring somatostatin receptor expressing tumor volume on 68Ga-DOTATATE positron emission tomography/computed tomography to predict prognosis in patients with gastroenteropancreatic neuroendocrine tumors.

We aimed to compare different segmentation methods used to calculate prognostically valuable volumetric parameters, somatostatin receptor expressing tumor volume (SRETV), and total lesion somatostatin receptor expression (TLSRE), measured by 68Ga-DOTATATE PET/CT and to find the optimal segmentation method to predict prognosis. Images of 34 patients diagnosed with gastroenteropancreatic neuroendocrine tumor (GEPNET) who underwent 68Ga-DOTATATE PET/CT imaging were reanalyzed. Four different threshold-based methods (fixed relative threshold method, normal liver background threshold method, fixed absolute standardized uptake value (SUV) threshold method, and adaptive threshold method) were used to calculate SRETV and TLSRE values. SRETV of all lesions of a patient was summarized as whole body SRETV (WB-SRETV) and TLSRE of all lesions of a patient was computed as whole body TLSRE (WB-TLSRE). WB-SRETVs calculated with all segmentation methods were statistically significantly associated with progression-free survival except WB-SRETVat which was calculated using adaptive threshold method. The fixed relative threshold methods calculated by using 45% (WB-SRETV45%) and 60% (WB-SRETV60%) of the SUV value as threshold respectively, were found to have statistically significant highest prognostic value (C-index = 0.704, CI = 0.622-0.786, P = 0.007). Among WB-TLSRE parameters, WB-TLSRE35%, WB-TLSRE40%, and WB-TLSRE50% had the highest prognostic value (C-index = 0.689, CI = 0.604-0.774, P = 0.008). The fixed relative threshold method was found to be the most effective and easily applicable method to measure SRETV on pretreatment 68Ga-DOTATATE PET/CT to predict prognosis in GEPNET patients. WB-SRETV45% (cutoff value of 11.8 cm3) and WB-SRETV60% (cutoff value of 6.3 cm3) were found to be the strongest predictors of prognosis in GEPNET patients.

Retrospective analysis of thyroid incidentalomas detected by [68Ga]Ga-PSMA-11 PET/CT.

Prostate cancer patients, undergo imaging procedures, with [68Ga]Ga-PSMA-11 PET/CT (prostate-specific membrane antigen based positron emission tomography/computed tomography) utilized for primary and secondary staging. PSMA thyroid incidentalomas (PTI) are discovered in the thyroid gland while imaging prostate cancer patients with [68Ga]Ga-PSMA-11 PET/CT. The aim of the study was to determine the clinical significance of PTIs detected on [68Ga]Ga-PSMA-11 PET/CT. Another goal was to identify a possible threshold for the maximum standardized uptake value (SUVmax), above which a malignant growth could be suspected. A retrospective cross-sectional study. 769 patients with prostat cancer who underwent [68Ga]Ga-PSMA-11 PET/CT scans in the nuclear medicine department of a tertiary care hospital between January 2020 and December 2022 were retrospectively screened in this study. We analyzed 67 patients in whom PTI was detected. Patients who exceeded the inclusion criteria had their thyroid ultrasonography and ultrasonography -guided fine needle aspiration findings analyzed. PTI was discovered in 67 patients (8%). 42 patients who met the inclusion and exclusion criteria were included in the study. Of the 4 malignant patients (9.5%) in the study population, 2 were classified as TIRADS 3 and 2 were classified as TIRADS 4. The cut-off SUVmax value was found to be 5.6. With 100% sensitivity and 47.37% specificity, a cutoff SUVmax of 5.3 was determined through receiver-operator characteristic analysis in order to predict malignant cytology. PTI is a significant clinical finding; most of diffuse and focal uptakes are frequently related to benign diseases. Each center should establish its own a possible SUVmax cut-off over which a malignant lesion should be suspected.

Normative values of the nociceptive blink reflex habituation

Introduction: Habituation is a physiological phenomenon, characterized by response reduction to repeated stimulus presentation. In headache disorders, habituation studies have involved different paradigms with several stimulation parameters and sensory modalities, and consistently showed impaired habituation in primary headaches in the interictal phase. The nociceptive blink reflex (nBR) and its related R2 response, modulated by a polysynaptic network in the trigeminocervical complex, is one of the most studied in the field. The lack of nBR habituation normative data hampered the possibility to draw conclusions regarding the functional status of individual patients. The present study aims to define normative values for the nBR habituation process in healthy subjects without a personal diagnosis and family history of migraine, or other headache disorders.Methods: We enrolled 40 healthy subjects (24 females, 32.7±11.6 years) for nBR recording and nBR habituation assessment. To assess the habituation of nBR, 26 consecutive stimuli were administered at three different and randomized stimulus frequencies (0.2, 0.3, 0.5 Hz). After excluding the first response, the remaining 25 area under the curve (AUC) were divided in 5 blocks, and the average values of the AUC was calculated for each block. The percentage reduction in the AUC of the fifth block, compared to the first, represents the habituation index (HI) value. We considered a one-tailed 10th percentile threshold as the lower threshold of normative values for nBR HI.Results: The habituation phenomenon was confirmed for all study frequencies. The absolute AUC of the R2 component across the five blocks of stimulation was higher in female subjects when compared to male for 0.5 Hz (p=0.021) and 0.2 Hz (p=0.007). We found a frequency-dependent habituation pattern, being lower at the 0.2 Hz stimulation when compared to 0.5 Hz (p=0.001), and 0.3 Hz (p=0.008). The average HIs were 73.1±13.6 at 0.5 Hz, 69.2±15.0 at 0.3 Hz, and 61.1±21.4 at 0.2 Hz. HIs were comparable between male and female subjects, without correlations with age, intensity of stimulation, and latency of the R2 component. The 10th percentile of the HIs was 43.5% for 0.5 Hz, 55.8% for 0.3 Hz, and 28.6% for 0.2 Hz.Conclusions: We investigated the nBR habituation in a population of healthy subjects for normative data collection. We described a frequency- dependent degree of habituation, being more pronounced at higher frequencies of stimulation. Moreover, we described gender-related features of response behaviour, which is extremely important in the migraine field. Our study further characterized the physiological habituation phenomenon in healthy controls exposed to a nociceptive stimulation. The definition of a normative habituation value will open novel possibilities in the study of migraine, as well as other headache and pain disorders.

Comparative evaluation of postoperative outcomes and expenditure between robotic and conventional single-level lumbar fusion surgery: a comprehensive analysis of nationwide inpatient sample data.

In this study, we investigate the evolution of lumbar fusion surgery with robotic assistance, specifically focusing on the impact of robotic technology on pedicle screw placement and fixation. Utilizing data from the Nationwide Inpatient Sample (NIS) covering 2016 to 2019, we conduct a comprehensive analysis of postoperative outcomes and costs for single-level lumbar fusion surgery. Traditionally, freehand techniques for pedicle screw placement posed risks, leading to the development of robotic-assisted techniques with advantages such as reduced misplacement, increased precision, smaller incisions, and decreased surgeon fatigue. However, conflicting study results regarding the efficacy of robotic assistance in comparison to conventional techniques have prompted the need for a thorough evaluation. With a dataset of 461,965 patients, our aim is to provide insights into the impact of robotic assistance on patient care and healthcare resource utilization. Our primary goal is to contribute to the ongoing discourse on the efficacy of robotic technology in lumbar fusion procedures, offering meaningful insights for optimizing patient-centered care and healthcare resource allocation. This study employed data from the Nationwide Inpatient Sample (NIS) spanning the years 2016 to 2019 from USA, 461,965 patients underwent one-level lumbar fusion surgery, with 5770 of them having the surgery with the assistance of robotic technology. The study focused primarily on one-level lumbar fusion surgery and excluded non-elective cases and those with prior surgeries. The analysis encompassed the identification of comorbidities, surgical etiologies, and complications using specific ICD-10 codes. Throughout the study, a constant comparison was made between robotic and non-robotic lumbar fusion procedures. Various statistical methods were applied, with a p value threshold of < 0.05, to determine statistical significance. Robotic-assisted lumbar fusion surgeries demonstrated a significant increase from 2016 to 2019, comprising 1.25% of cases. Both groups exhibited similar patient demographics, with minor differences in payment methods, favoring Medicare in non-robotic surgery and more private payer usage in robotic surgery. A comparison of comorbid conditions revealed differences in the prevalence of hypertension, dyslipidemia, and sleep apnea diagnoses-In terms of hospitalization outcomes and costs, there was a slight shorter hospital stay of 3.06days, compared to 3.13days in non-robotic surgery, showcasing a statistically significant difference (p = 0.042). Robotic surgery has higher charges, with a mean charge of $154,673, whereas non-robotic surgery had a mean charge of $125,467 (p < 0.0001). Robotic surgery demonstrated lower rates of heart failure, acute coronary artery disease, pulmonary edema, venous thromboembolism, and traumatic spinal injury compared to non-robotic surgery, with statistically significant differences (p < 0.05). Conversely, robotic surgery demonstrated increased post-surgery anemia and blood transfusion requirements compared to non-robotic patients (p < 0.0001). Renal disease prevalence was similar before surgery, but acute kidney injury was slightly higher in the robotic group post-surgery (p = 0.038). This is the first big data study on this matter, our study showed that Robotic-assisted lumbar fusion surgery has fewer post-operative complications such as heart failure, acute coronary artery disease, pulmonary edema, venous thromboembolism, and traumatic spinal injury in comparison to conventional methods. Conversely, robotic surgery demonstrated increased post-surgery anemia, blood transfusion and acute kidney injury. Robotic surgery has higher charges compared to non-robotic surgery.

Efficacy of intraoperative visual evoked potential amplitude reduction in predicting visual outcome after extended endoscopic endonasal resection of craniopharyngiomas.

Postoperative visual outcome is a major concern of neurosurgeons for patients with craniopharyngiomas. The current study aimed to investigate the value of visual evoked potential (VEP) amplitude reduction (N75-P100 and P100-N145) for predicting postoperative visual dysfunction (POVD) and refining current warning criteria for VEP monitoring. Data from 96 patients who underwent the extended endoscopic endonasal approach for craniopharyngiomas between October 2020 and November 2021 were retrospectively reviewed. VEP amplitude reduction ratios were calculated and compared between patients with POVD and those without. Subsequently, the critical threshold values of VEP amplitude reduction ratios for predicting POVD were obtained through receiver operating characteristic curve analysis. Finally, multivariate binary logistic regression analysis was applied to evaluate the effect of potential factors on the probability of experiencing POVD. Both N75-P100 and P100-N145 amplitude reduction ratios were significantly higher in patients with POVD (p < 0.001 for both). The threshold value of the N75-P100 amplitude reduction ratio for predicting POVD was 51.76% with an area under the curve (AUC) of 0.816 (p < 0.001), while the threshold value of the P100-N145 amplitude reduction ratio was 38.80% with an AUC of 0.738 (p < 0.001). Both N75-P100 and P100-N145 amplitude reduction ratios were identified as independent predictors for POVD via multivariate analysis (p < 0.001 and p = 0.018, respectively). Both N75-P100 and P100-N145 amplitude reduction ratios showed great potential to be indicators for POVD in patients with craniopharyngiomas. Regarding warning criteria for VEP monitoring, the authors recommend that both N75-P100 and P100-N145 amplitude reduction should be considered, with early warning criteria of a 50% reduction for N75-P100 amplitude and/or a 40% reduction for P100-N145 amplitude.

One‐bit DOA estimation in non‐uniform noise with alternating minimization method

AbstractThis letter presents a method to optimize the estimation of direction of arrival (DOA) using the uniform linear array (ULA) with one‐bit signals in the presence of non‐uniform noise. With the Toeplitz properties and the rank characteristics of the signal subspace matrix formed by the ULA, the alternating minimization (AM) method is employed to optimize the estimation problem. To address this challenge further, we utilize the singular value thresholding (SVT) method and the approximate projection method. The angle deviations caused by non‐uniform noise can be effectively corrected and a significant improvement in the estimation performance can be achieved. The feasibility and effectiveness of the proposed method are demonstrated through simulation results.

Optimization of Cu2O Thickness to Enhance Photocatalytic Properties of Electrodeposited Cu2O/FTO Photoanode

Currently, n-type cuprous oxide (Cu2O) is a promising material as photocatalyst because of its energy gap of 2 eV that absorbs visible light up to a wavelength of 600 nm. As a photoelectrode, the thickness of Cu2O is crucial, where the improper thickness may worsen the photocatalytic properties. This work aimed to enhance the photocatalytic properties of Cu2O electrodeposited on fluorine-doped tin oxide (FTO), called Cu2O/FTO, by optimizing the Cu2O thickness. The thickness of Cu2O was controlled by adjusting the deposition time in the electrochemical deposition of Cu2O/FTO. By changing the deposition time from 5 to 45 min, the morphology of Cu2O changed from a leaf-like shape to an irregular facet shape with highly dense coverage, and the average thickness increased from 370 to 1100 nm. The increasing Cu2O thickness resulted in the increasing light absorption. The Cu2O/FTO demonstrated anodic photocurrent, which increased with the Cu2O thickness up to a threshold value of 1000 nm (35 min deposition time). At a thickness of 1000 nm, Cu2O/FTO achieved the highest photocurrent (150 and 58 µA under irradiation of 365 and 470 nm, respectively) due to the highly dense morphology and high absorption. In addition, with a thickness of 1000 nm, the charge diffusion was still good. Further, the increase of Cu2O film thickness higher than 1000 nm caused low photocatalytic properties even though the morphology was highly dense, and the absorption was the highest. This condition could be due to the relatively too-high resistance of Cu2O that caused poor charge diffusion. Copyright © 2024 by Authors, Published by BCREC Publishing Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

A research on an improved fuzzy approximate entropy algorithm for EMG-based shoulder and neck muscle fatigue detection

A robust muscle fatigue algorithm plays a pivotal role in depicting the degree of muscle fatigue in both time-series EMG signal graphs and spectral graphs, aligning with human perception. While the fuzzy approximate entropy (fApEn) algorithm has been enhanced from the foundation of approximate entropy (ApEn) through the incorporation of fuzzy affiliation, concerns persist regarding the threshold value and the algorithm’s application range. This study extracts EMG signals across varied time durations and head-down angles, employing enhanced signal preprocessing techniques and optimizing the fApEn algorithm. Furthermore, real-time fatigue perceptions of subjects were recorded using the rating of perceived exertion. Experimental outcomes reveal that the EMG signal, post-wavelet analysis preprocessing, demonstrates promising noise reduction capabilities. Notably, the fApEn algorithm exhibits considerable enhancements through the identification of an optimal threshold using the gradient descent algorithm and a machine learning strategy.

Deep multimodal spatio-temporal Harris Hawk Optimized Pose Recognition framework for self-learning fitness exercises

Human pose recognition from videotapes has become an emerging research topic for tracking human movements. The objective of this work is to develop a deep multimodal Spatio-Temporal Harris Hawk Optimized Pose Recognition (STHHO-PR) framework for self-learning fitness exercises. The presented STHHO-PR framework uses audio modality and visual modality to classify the different poses. In audio modality, the VGG-16 network paradigm is used to extract the audio traits for fitness pose recognition. In visual modality, Harris Hawks Optimization (HHO) along with the Minimum Cross Entropy (MCE) method is employed to find out the optimum threshold values for body parts segmentation. These segmented body parts highlight the human joint points that are connected through the skeletonization process to extract the skeletal information. The extracted spatio-temporal features from audio modality and visual modality are optimally fused and used in the classification process. Weighted Majority Voting Ensemble (WMVE) classifier is adopted to build the classification model. This work is experimented with yoga videos acquired from publicly available datasets. The results show that the presented STHHO-PR framework outperforms other state-of-art procedures in terms of prediction accuracy.

Comprehensive identification and risk assessment of regulated and emerging mycotoxins in infant foods and related raw materials and risk management advice: A case study of an infant food company in China

This study evaluated muti-mycotoxins in 199 samples including processed infant foods and raw materials collected randomly from an infant food company and assessed their role in dietary exposure in infants and young children via probabilistic risk assessment. Approximately 79.6 % (74/93) of the processed infant foods and 65.1 % (69/106) of the raw materials were contaminated by mycotoxins, with a mean occurrence level of 3.66–321.8 µg/kg. Deoxynivalenol (DON) and tenuazonic acid (TeA) were the more prevalent mycotoxins detected, based on their higher frequencies and levels across samples. Co-occurrence of more than two mycotoxins was detected in 61.3 % (57/93) of the processed infant foods and 53.8 % (57/106) of the raw materials. Wheat flour and derived products (e.g., infant noodles and infant biscuits) were contaminated with higher contamination levels and a greater variety of mycotoxins than other samples (e.g., infant cereal and rice grains). The estimated daily exposure to OTA, DON, ZEN, and TEN was lower than the corresponding reference health-based guidance values, indicating acceptable health risks. However, the estimated dietary exposure to alternariol monomethyl ether (AME), alternariol (AOH), and tenuazonic acid (TeA) exceeded the corresponding thresholds of toxicological concern values, indicating potential dietary intake risks. Among the various samples, cereals and cereal-based infant foods emerged as the primary contributors to mycotoxin exposure. Further research is advised to address the uncertainties surrounding the toxicity associated with emerging Alternaria mycotoxins and to conduct cumulative risk assessments concerning multiple mycotoxin exposure in infants and young children.

The Effect of Crystal Arthropathy on the Diagnostic Criteria of Native Septic Arthritis.

Distinguishing between septic arthritis and crystal arthropathy flares can be challenging. The purpose of this study was to determine how the presence of synovial crystals affects the diagnostic criteria of septic arthritis. A retrospective review identified patients undergoing joint aspirations to rule out native septic arthritis. Differences between septic arthritis presenting with and without synovial crystals were analyzed. A receiver-operating characteristic curve was plotted for laboratory markers to determine the area under the curve, or diagnostic accuracy, for septic arthritis and to evaluate thresholds that maximized sensitivity and specificity. There were 302 joint aspirations in 267 patients. Septic arthritis was diagnosed in 17.9% (54/302). Patients with synovial crystals were less likely to have septic arthritis (4.2% [5/119] vs. 26.8% [49/183], P < 0.0001). Septic arthritis in patients with no synovial crystals was associated with fever and a higher synovial white blood cell (WBC) count, synovial polymorphonuclear cell percentage (PMN%), serum WBC, and C-reactive protein (CRP) (P < 0.05). Septic arthritis in patients with synovial crystals was only associated with inability to bear weight and a higher synovial WBC and CRP (P < 0.05). Synovial PMN% was considered nondiagnostic of septic arthritis (area under the curve 0.56) in patients with crystals while synovial WBC and CRP had acceptable (0.76) and excellent (0.83) diagnostic utility, respectively. The WBC and CRP value thresholds that maximized sensitivity and specificity for septic arthritis were greater in patients with crystals (21,600 vs. 17,954 cells/μL and 125 vs. 69 mg/L, respectively). The presence of synovial crystals reduced the likelihood of septic arthritis and altered the laboratory diagnostic criteria. PMN% was nondiagnostic in the setting of synovial crystals.

Quantitative evaluation of meniscus injury using synthetic magnetic resonance imaging.

Magnetic resonance imaging (MRI) can diagnose meniscal lesions anatomically, while quantitative MRI can reflect the changes of meniscal histology and biochemical structure. Our study aims to explore the association between the measurement values obtained from synthetic magnetic resonance imaging (SyMRI) and Stoller grades. Additionally, we aim to assess the diagnostic accuracy of SyMRI in determining the extent of meniscus injury. This potential accuracy could contribute to minimizing unnecessary invasive examinations and providing guidance for clinical treatment. Total of 60 (n=60) patients requiring knee arthroscopic surgery and 20 (n=20) healthy subjects were collected from July 2022 to November 2022. All subjects underwent conventional MRI and SyMRI. Manual measurements of the T1, T2 and proton density (PD) values were conducted for both normal menisci and the most severely affected position of injured menisci. These measurements corresponded to the Stoller grade of meniscus injuries observed in the conventional MRI. All patients and healthy subjects were divided into normal group, degeneration group and torn group according to the Stoller grade on conventional MRI. One-way analysis of variance (ANOVA) was employed to compare the T1, T2 and PD values of the meniscus among 3 groups. The accuracy of SyMRI in diagnosing meniscus injury was assessed by comparing the findings with arthroscopic observations. The diagnostic efficiency of meniscus degeneration and tear between conventional MRI and SyMRI were analyzed using McNemar test. Furthermore, a receiver operating characteristic curve (ROC curve) was constructed and the area under the curve (AUC) was utilized for evaluation. According to the measurements of SyMRI, there was no statistical difference of T1 value or PD value measured by SyMRI among the normal group, degeneration group and torn group, while the difference of T2 value was statistically significant among 3 groups (P=0.001). The arthroscopic findings showed that 11 patients were meniscal degeneration and 49 patients were meniscal tears. The arthroscopic findings were used as the gold standard, and the difference of T1 and PD values among the 3 groups was not statistically significant, while the difference of T2 values (32.81±2.51 of normal group, 44.85±3.98 of degeneration group and 54.42±3.82 of torn group) was statistically significant (P=0.001). When the threshold of T2 value was 51.67 (ms), the maximum Yoden index was 0.787 and the AUC value was 0.934. The measurement values derived from SyMRI could reflect the Stoller grade, illustrating that SyMRI has good consistency with conventional MRI. Moreover, the notable consistency observed between SyMRI and arthroscopy suggests a potential role for SyMRI in guiding clinical diagnoses.

CovXtreme : MATLAB software for non-stationary penalised piecewise constant marginal and conditional extreme value models

The covXtreme software provides functionality for estimation of marginal and conditional extreme value models, non-stationary with respect to covariates, and environmental design contours. Generalised Pareto (GP) marginal models of peaks over threshold are estimated, using a piecewise-constant representation for the variation of GP threshold and scale parameters on the (potentially multidimensional) covariate domain of interest. The conditional variation of one or more associated variates, given a large value of a single conditioning variate, is described using the conditional extremes model of Heffernan and Tawn (2004), the slope term of which is also assumed to vary in a piecewise constant manner with covariates. Optimal smoothness of marginal and conditional extreme value model parameters with respect to covariates is estimated using cross-validated roughness-penalised maximum likelihood estimation. Uncertainties in model parameter estimates due to marginal and conditional extreme value threshold choice, and sample size, are quantified using a bootstrap resampling scheme. Estimates of environmental contours using various schemes, including the direct sampling approach of Huseby et al. 2013, are calculated by simulation or numerical integration under fitted models. The software was developed in MATLAB for metocean applications, but is applicable generally to multivariate samples of peaks over threshold data. The software and case study data can be downloaded from GitHub, with an accompanying user guide.

Singular value thresholding two-stage matrix completion for drug sensitivity discovery

Incomplete data presents significant challenges in drug sensitivity analysis, especially in critical areas like oncology, where precision is paramount. Our study introduces an innovative imputation method designed specifically for low-rank matrices, addressing the crucial challenge of data completion in anticancer drug sensitivity testing. Our method unfolds in two main stages: Initially, the singular value thresholding algorithm is employed for preliminary matrix completion, establishing a solid foundation for subsequent steps. Then, the matrix rows are segmented into distinct blocks based on hierarchical clustering of correlation coefficients, applying singular value thresholding to the largest block, which has been proved to possess the largest entropy. This is followed by a refined data restoration process, where the reconstructed largest block is integrated into the initial matrix completion to achieve the final matrix completion. Compared to other methods, our approach not only improves the accuracy of data restoration but also ensures the integrity and reliability of the imputed values, establishing it as a robust tool for future drug sensitivity analysis.

Three-dimensional copula framework for early warning of agricultural droughts using meteorological drought and vegetation health conditions

ABSTRACT This study develops an early warning system for crop yield (CY) failure based on meteorological drought and vegetation health conditions. The framework combines three drought indices – the Standardized Precipitation Evapotranspiration Index (SPEI), standardized Normalized Difference Vegetation Index (stdNDVI), and standardized CY (stdCY) values – using copulas. Datasets for five major wheat-producing cities in Turkey between 2000 and 2022 are used for analysis. Results indicate that the time periods used to calculate SPEI and NDVI are critical in determining agricultural drought and CY conditions. The critical threshold values for SPEI and NDVI, with a 10% probability of causing agricultural drought, are found to be ~0.28 and ~0.42, respectively. Using a three-dimensional copula model resulted in more precise CY simulations than a two-dimensional model. The validation efforts showed that all of the observed CYs fell within the simulated range, indicating the robustness of the methodology in capturing drought impacts on CY conditions.

Hierarchical Fuzzy MCDA Multi-Risk Model for Detecting Critical Urban Areas in Climate Scenarios

One of the issues of greatest interest in urban planning today concerns the evaluation of the most vulnerable urban areas in the presence of different types of climate hazards. In this research, a hierarchical fuzzy MCDA model is implemented on a GIS-based platform aimed at detecting the urban areas most at risk in the presence of heatwave and pluvial flooding scenarios. The proposed model aims to detect the urban areas most vulnerable to both the two climatic phenomena and the two types of hazards as independent events; it partitions the physical component of an urban settlement into two subsystems: buildings and open spaces, and it determines the criticality of a subzone of the urban area of study by evaluating the vulnerabilities of the two subsystems to the two phenomena. The use of a hierarchical fuzzy MCDA model facilitates the modeling of the two subsystems and the assessment of their vulnerability to the two phenomena, and it provides a computationally fast tool for detecting critical urban areas. The model was tested on a study area made up of the districts of the central-eastern area of the city of Naples (Italy); it was divided into subzones made up of individual census areas. The most critical areas are represented by the subzones with criticality values higher than a specific threshold.

Short-term data suggests cognitive benefits in the elderly with single-implant overdentures.

This study was an extension of a randomized crossover clinical trial approved by the institutional ethics committee (approval number: D2014-148) and adhered to the CONSORT guidelines. The original study juxtaposed patient contentment with single-implant overdentures (1-IODs) against conventional complete dentures (CCDs), with patient satisfaction being the primary focus. In this follow-up study, the cognitive function of edentulous patients receiving 1-IODs was assessed, specifically monitoring for the emergence of mild cognitive impairment (MCI) throughout a three-year period. Patient outcomes were systematically recorded at predetermined intervals: initially, two months post-1-IOD placement, after one year (with groups alternated between denture types at eight-month marks), then after two and three years. A prosthodontist with a decade of expertise performed all denture-related procedures. This follow-up emphasized the cognitive outcomes using the Montreal Cognitive Assessment (MoCA-J), considering it alongside previously documented results on masticatory function, bone resorption, survival rates, and patient-reported outcomes. Between 2015 and 2016, a follow-up study enrolled edentulous patients over 50 years of age who were proficient in Japanese, had sufficient mandibular bone for implants, and were free of systemic health issues and habits that could impact oral health. The participants were randomly divided into two groups after receiving a central mandibular implant. Group 1 initially used 1-IODs, and Group 2 used unloaded CCDs. After two months and subsequent periods, they swapped denture types. Eventually, all patients chose 1-IODs for continued use. Implant success was monitored over three years. The design featured block randomization and accounted for a sample size of 22, determined to be sufficient for evaluating the primary outcome of patient satisfaction. All patients underwent careful allocation and received customized dental interventions, with detailed radiographic planning and surgical precision guiding the implantation process. Multivariable linear mixed models were used to assess within-group changes in both overall and specific cognitive function scores across five timepoints. Age, assessment interval, and upper jaw denture status were incorporated as consistent variables, while individual participants were considered variable elements in the analysis. SPSS software version 22.0 was utilized to conduct the statistical tests, and a p value threshold of 0.05 was predetermined to establish statistical significance. Twenty-two patients with edentulous mandibles received 1-IODs. Memory and executive functions saw significant score increases at multiple timepoints over the three-year period, with statistical significance. Though one participant dropped out and another passed away, and two did not complete the 3-year follow-up, the remaining 18 participants provided comprehensive data. Age and type of maxillary denture were significant factors, influencing MoCA-J scores with older participants and those with fixed dentures showing lower scores in certain domains. Overall, the findings illustrated the positive correlation between 1-IODs and cognitive function in older adults. Older adults with no natural teeth left in their mandible showed improved cognitive function after one and three years of using 1-IODs, as reflected by their total and specific cognitive domain scores. The study suggests that such implant therapy may offer protective benefits against cognitive decline, demonstrating clinical relevance for patient care, regardless of the maxillary arch (antagonist) condition.

Analysis of Electroosmotically Modulated Peristaltic Transport of Third Grade Fluid in a Microtube Considering Slip-Dependent Zeta Potential

Abstract The present study investigates electro-osmotically modulated peristaltic transport of third-grade fluid through a microtube taking into consideration the intricate coupling of zeta potential and hydrodynamic slippage. The analytical results encompass the mathematical expressions for dimensionless electrical potential distribution as well as series solutions for stream function and axial pressure gradient up to first order utilizing the perturbation technique for small Deborah number coupled with the Cauchy product for infinite series. Critical values and ranges of wavelength have been obtained where the axial pressure gradient vanishes. Moreover, pivotal values and ranges of wavelength have also been noted for the invariance of pressure gradient with respect to Deborah number as well as Debye–Hückel parameter. Trapping phenomenon has also been investigated by contours of streamlines wherein the zones of recirculation or trapped boluses are formed predominantly near the microtube walls. Additionally, the relative enhancement in hydrodynamic slippage amplifies the trapped bolus size, whereas a diminishing behavior on bolus size is observed by the electro-osmotic parameter.

A Low-Speed Position Sensorless Scheme From Standstill for Low-Cost SRM Drives Based on Triple Current Slope Difference Threshold

In this paper, a triple current slope difference threshold based low-speed sensorless scheme for low-cost SRM drives is proposed. Firstly, slope based methods, including the current slope difference method, are proposed and the advantages in terms of anti-interference ability over traditional instantaneous value based methods have been clarified. Secondly, the traditional single/double threshold methods and corresponding outgoing/incoming phase injection types are introduced and comprehensively compared. The limitations of conventional methods while adopted in low-cost SRM drives are stated. Accordingly, to solve the problem that the current cannot be obtained during the demagnetization stage in the resistor-based current sampling scheme, the triple current slope difference threshold method is proposed, whose 3 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rd</sup> threshold indicates the zero-current position. Thirdly, a general threshold value determination method considering the three-phase unbalanced inductances is proposed, which only requires the unsaturated inductance vs. rotor position characteristics that is very easy to be obtained. The proposed method only needs to store six threshold values in the microprocessor and needs no complex calculations and additional hardware, which can be realized in low-cost drive systems. Finally, the experiments of both the steady-state and starting transient-state under over-load conditions are implemented to verify the feasibility and accuracy of the proposed method.

M3W: Multistep Three-Way Clustering.

Three-way clustering has been an active research topic in the field of cluster analysis in recent years. Some efforts are focused on the technique due to its feasibility and rationality. We observe, however, that the existing three-way clustering algorithms struggle to obtain more information and limit the fault tolerance excessively. Moreover, although the one-step three-way allocation based on a pair of fixed, global thresholds is the most straightforward way to generate the three-way cluster representations, the clusters derived from a pair of global thresholds cannot exactly reveal the inherent clustering structure of the dataset, and the threshold values are often difficult to determine beforehand. Inspired by sequential three-way decisions, we propose an algorithm, called multistep three-way clustering (M3W), to address these issues. Specifically, we first use a progressive erosion strategy to construct a multilevel structure of data, so that lower levels (or external layers) can gather more available information from higher levels (or internal layers). Then, we further propose a multistep three-way allocation strategy, which sufficiently considers the neighborhood information of every eroded instance. We use the allocation strategy in combination with the multilevel structure to ensure that more information is gradually obtained to increase the probability of being assigned correctly, capturing adaptively the inherent clustering structure of the dataset. The proposed algorithm is compared with eight competitors using 18 benchmark datasets. Experimental results show that M3W achieves superior performance, verifying its advantages and effectiveness.