Study adsorbents based on bent-Al13-CS-CTA and its application to the removal of CR from wastewater.

For rapid and efficient removal of Congo red (CR) from aqueous solutions, a composite of bent-Al13-CS-CTA was prepared from bentonite (bent), chitosan (CS), citric acid (CTA) and Al13 compounds. To comprehend the adsorption process, adsorption variables were changed, including initial pH of the solution, contact time, temperature, initial CR concentration, and adsorption dose. Bent intercalated with X-ray diffraction (XRD), specific surface area (BET), scanning electron microscopy (SEM) and Fourier transform infrared spectrophotometry (FTIR) were used to analyze the material. Physicochemical and structural analysis proven the incorporation of Al13, CS, and CTA into the bent matrix. The pseudo-second-order model aligns with the adsorption kinetics. The adsorption isotherm conformed to the Langmuir adsorption isotherm, with a maximum adsorption capacity of 476.8 mg g-1 at pH 9, a dosage of 2 g L-1, and a temperature of 25 °C. Upon examining the thermodynamic properties of ΔS, ΔH, and ΔG, it was found that the reaction is a spontaneous endothermic process that could potentially be utilized to eliminate CR.

Development of a convenient and effective hypertension risk prediction model and exploration of the relationship between Serum Ferritin and Hypertension Risk: a study based on NHANES 2017-March 2020.

Background: Hypertension is a major public health problem, and its resulting other cardiovascular diseases are the leading cause of death worldwide. In this study, we constructed a convenient and high-performance hypertension risk prediction model to assist in clinical diagnosis and explore other important influencing factors. Methods: We included 8,073 people from NHANES (2017-March 2020), using their 120 features to form the original dataset. After data pre-processing, we removed several redundant features through LASSO regression and correlation analysis. Thirteen commonly used machine learning methods were used to construct prediction models, and then, the methods with better performance were coupled with recursive feature elimination to determine the optimal feature subset. After data balancing through SMOTE, we integrated these better-performing learners to construct a fusion model based for predicting hypertension risk on stacking strategy. In addition, to explore the relationship between serum ferritin and the risk of hypertension, we performed a univariate analysis and divided it into four level groups (Q1 to Q4) by quartiles, with the lowest level group (Q1) as the reference, and performed multiple logistic regression analysis and trend analysis. Results: The optimal feature subsets were: age, BMI, waist, SBP, DBP, Cre, UACR, serum ferritin, HbA1C, and doctors recommend reducing salt intake. Compared to other machine learning models, the constructed fusion model showed better predictive performance with precision, accuracy, recall, F1 value and AUC of 0.871, 0.873, 0.871, 0.869 and 0.966, respectively. For the analysis of the relationship between serum ferritin and hypertension, after controlling for all co-variates, OR and 95% CI from Q2 to Q4, compared to Q1, were 1.396 (1.176-1.658), 1.499 (1.254-1.791), and 1.645 (1.360-1.989), respectively, with P < 0.01 and P for trend <0.001. Conclusion: The hypertension risk prediction model developed in this study is efficient in predicting hypertension with only 10 low-cost and easily accessible features, which is cost-effective in assisting clinical diagnosis. We also found a trend correlation between serum ferritin levels and the risk of hypertension.

Removal of Methylene Blue from Aqueous Solutions by Surface Modified Talc.

In this study, raw talc powder surface modification was conducted, and the powder was modified in two different methods using acid washing and ball milling. Modified talc was characterized by X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). In order to investigate the adsorption capacity of modified talc on dyes, adsorption experiments were carried out with methylene blue (MB) in aqueous solutions as the target contaminant. The findings of the characterization revealed that both modifications increased the adsorption capacity of talc, which was attributed to changes in specific surface area and active groups. The influence of process parameters such as contact time, pH, dye concentration, and adsorbent dosage on the adsorption performance was systematically investigated. Modified talc was able to adsorb MB rapidly, reaching equilibrium within 60 min. Additionally, the adsorption performance was improved as the pH of the dye solution increased. The isotherms for MB adsorption by modified talc fitted well with the Langmuir model. The pseudo-second-order model in the adsorption kinetic model properly described the adsorption behavior. The results show that the modified talc can be used as an inexpensive and abundant candidate material for the adsorption of dyes in industrial wastewater.

Frailty mediated the association between tooth loss and mortality in the oldest old individuals: a cohort study.

Introduction: Tooth loss is associated with increased mortality risk; however, the mechanism underlying this is still not clear. The objective of this study was to explore whether frailty mediates the association between tooth loss and mortality risk among the oldest old individuals. Methods: The participants were followed up from 1998 to 2018 in the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Frailty was constructed following a standard procedure. Mortality, frailty, and tooth loss were applied as the outcome, mediator, and independent variables, respectively. The Cox model was fitted, including possible confounders, for causal mediation analysis. A total effect (TE), an average causal mediation effect (ACME), an average direct effect (ADE), and a proportion mediated (PM) effect were calculated. Results: During the 129,936 person-years at risk, 31,899 individuals with a mean age of 91.79 years were included. The TE and ADE of severe tooth loss on mortality were 0.12 (95% CI: 0.08, 0.15) and 0.09 (95% CI: 0.05, 0.13); the ACME of frailty was 0.03 (95% CI: 0.02, 0.03) with 21.56% of the TE being mediated. Discussion: This study illustrated that tooth loss is associated with mortality, and frailty appeared to mediate the relationship. It is recommended that oral health indicators and frailty status be incorporated into routine geriatric assessments to promote optimal oral health and non-frailty status.

Personalized subcutaneous implantable cardioverter-defibrillator sensing vectors generated by mathematical rotation increase device eligibility whilst preserving device performance.

AIMS: Approximately 5.7% of potential subcutaneous implantable cardioverter-defibrillator (S-ICD) recipients are ineligible by virtue of their vector morphology, with higher rates of ineligibility observed in some at-risk groups. Mathematical vector rotation is a novel technique that can generate a personalized sensing vector, one with maximal R:T ratio, using electrocardiogram (ECG) signal recorded from the present S-ICD location. METHODS AND RESULTS: A cohort of S-ICD ineligible patients were identified through ECG screening of ICD patients with no ventricular pacing requirement and their personalized vectors were generated using ECG signal from a Holter monitor. Subcutaneous ICD eligibility in this cohort was then recalculated. In a separate cohort, episodes of arrhythmia were recorded in patients undergoing arrhythmia induction, and arrhythmia detection in standard S-ICD vectors was compared to rotated vectors using an S-ICD simulator. Ninety-two participants (mean age 64.9 ± 2.7 years) underwent screening and 5.4% were found to be S-ICD ineligible. Personalized vector generation increased the R:T ratio in these vectors from 2.21 to 7.21 (4.54-9.88, P < 0.001) increasing the cohort eligibility from 94.6% to 100%. Rotated S-ICD vectors also showed high ventricular fibrillation (VF) detection sensitivity (97.8%), low time to VF detection (6.1 s), and excellent tachycardia discrimination (sensitivity 96%, specificity 88%), with no significant differences between rotated and standard vectors. CONCLUSION: In S-ICD ineligible patients, mathematical vector rotation can generate a personalized vector that is associated with a significant increase in R:T ratio, resulting in universal device eligibility in our cohort. Ventricular fibrillation detection efficacy, time to VF detection, and tachycardia discrimination were not affected by vector rotation.

Prediction and classification of ventricular arrhythmia based on phase-space reconstruction and fuzzy c-means clustering.

BACKGROUND AND OBJECTIVE: Prediction and classification of Ventricular Arrhythmias (VA) may allow clinicians sufficient time to intervene for stopping its escalation to Sudden Cardiac Death (SCD). This paper proposes a novel method for predicting VA and classifying its type, in particular, the fatal VA even before the event occurs. METHODS: A statistical index J based on the combination of phase-space reconstruction (PSR) and box counting has been used to predict VA. The fuzzy c-means (FCM) clustering technique is applied for the classification of impending VA. RESULTS: 32 healthy and 32 arrhythmic subjects from two open databases - PTB Diagnostic database (PTBDB) and CU Ventricular Tachyarrhythmia (CUDB) database respectively; were used to validate our proposed method. Our method showed average prediction time of approximately 5 min (4.97 min) for impending VA in the tested dataset while classifying four types of VA (VA without ventricular premature beats (VPBs), ventricular fibrillation (VF), ventricular tachycardia (VT), and VT followed by VF) with an average 4 min (approximately) before the VA onset, i.e., after 1 min of the prediction time point with average accuracy of 98.4%, a sensitivity of 97.5% and specificity of 99.1%. CONCLUSIONS: The results obtained can be used in clinical practice after rigorous clinical trial to advance technologies such as implantable cardioverter defibrillator (ICD) that can help to preempt the occurrence of fatal ventricular arrhythmia - a main cause of SCD.

A new algorithm to reduce T-wave over-sensing based on phase space reconstruction in S-ICD system.

BACKGROUND AND OBJECTIVE: The subcutaneous implantable cardioverter defibrillator (S-ICD) reduces mortality in individuals at high risk of sudden arrhythmic death, by rapid defibrillation of life-threatening arrhythmia. Unfortunately, S-ICD recipients are also at risk of inappropriate shock therapies, which themselves are associated with increased rates of mortality and morbidity. The commonest cause of inappropriate shock therapies is T wave oversensing (TWOS), where T waves are incorrectly counted as R waves leading to an overestimation of heart rate. It is important to develop a method to reduce TWOS and improve the accuracy of R-peak detection in S-ICD system. METHODS: This paper introduces a novel algorithm to reduce TWOS based on phase space reconstruction (PSR); a common method used to analyse the chaotic characteristics of non-linear signals. RESULTS: The algorithm was evaluated against 34 records from University Hospital Southampton (UHS) and all 48 records from the MIT-BIH arrhythmia database. In the UHS analysis we demonstrated a sensitivity of 99.88%, a positive predictive value of 99.99% and an accuracy of 99.88% with reductions in TWOS episodes (from 166 to 0). Whilst in the MIT-BIH analysis we demonstrated a sensitivity of 99.87%, a positive predictive value of 99.99% and an accuracy of 99.91% for R wave detection. The average processing time for 1 min ECG signals from all records is 2.9 s. CONCLUSIONS: Our algorithm is sensitive for R-wave detection and can effectively reduce the TWOS with low computational complexity, and it would therefore have the potential to reduce inappropriate shock therapies in S-ICD recipients, which would significantly reduce shock related morbidity and mortality, and undoubtedly improving patient's quality of life.

Antimicrobial Stewardship Programs in Northwest China: A Cross-Sectional Survey of Perceptions, Involvement, and Perceived Barriers Among Hospital Pharmacists.

Background: Antimicrobial stewardship (AMS) is a key prevention strategy in addressing the global concern of increasing antimicrobial resistance (AMR). Pharmacists are one of the integral members of AMS hospital teams around the world. Toward reducing AMR, a major strategy in China is to improve the capacity and participation of pharmacists in the AMS framework. However, little is known about how hospital pharmacists perceive their position and participation in AMS work, and the barriers to this work in China, especially in the Northwest region. Methods: Region this work describes a cross-sectional, anonymous, online survey study. Hospital pharmacists from five provinces/autonomous regions in northwest China were invited to participate in June and July 2020. Participants completed the survey by using WeChat, a popular social application in China. We purposefully distributed the questionnaire link and QR code to hospital pharmacists through the hospital antimicrobial resistance surveillance network, hospital antimicrobial consumption surveillance network, provincial and city pharmaceutical associations, and hospital pharmacist WeChat groups. Results: Out of 1032 respondents, 93.1% believed that AMS programs promote the judicial prescribing of antimicrobials, 95.5% strongly agreed that AMS could reduce the widespread use of antimicrobials, and 92.3% believed that AMS could improve medical services. Pharmacists were most likely to be involved in AMS through reviewing prescriptions of antimicrobials, intervening in inappropriate prescriptions, and providing feedback on antimicrobial prescriptions and medical orders. Barriers to participating in AMS included workload (59.5% of respondents), ineffective communication between pharmacists and doctors (57.7%), and inadequate knowledge of AMS (47.0%). Differences in responses were found between the five surveyed provinces. A significant association was found between median involvement scores and gender, age, education, level of superiority, experience, and type of hospital (p < 0.05). Conclusion: Pharmacists perceived that AMS programs are important, but that their involvement in related activities is limited in all provinces. Further studies and strategies should consider how to overcome the identified barriers to optimize the participation of pharmacists in AMS programs.

An Automatic R and T Peak Detection Method Based on the Combination of Hierarchical Clustering and Discrete Wavelet Transform.

The detection and delineation of QRS-complexes and T-waves in Electrocardiogram (ECG) is an important task because these features are associated with the cardiac abnormalities including ventricular arrhythmias that may lead to sudden cardiac death. In this paper, we propose a novel method for the R-peak and the T-peak detection using hierarchical clustering and Discrete Wavelet Transform (DWT) from the ECG signal. In the first step, a template of the single ECG beat is identified. Secondly, all R-peaks are detected by using hierarchical clustering. Then, each corresponding T-wave boundary is delineated based on the template morphology. Finally, the determination of T wave peaks is achieved based on the Modulus-Maxima Analysis (MMA) of the DWT coefficients. We evaluated the algorithm by using all records from the MIT-BIH arrhythmia database and QT database. The R-peak detector achieved a sensitivity of 99.89%, a positive predictivity of 99.97% and 99.83% accuracy over the validation MIT-BIH database. In addition, it shows a sensitivity of 100%, a positive predictivity of 99.83% in manually annotated QT database. It also shows 99.92% sensitivity and 99.96% positive predictivity over the automatic annotated QT database. In terms of the T-peak detection, our algorithm is verified with 99.91% sensitivity and 99.38% positive predictivity in manually annotated QT database.

Evaluation of an urban traffic Noise-Exposed population based on points of interest and noise maps: The case of Guangzhou.

The primary objective of this study was to develop an evaluation method for assessing an urban traffic noise-exposed population and apply it in the main urban area of Guangzhou. The method based on points of interest (POIs) and noise map is realized in several steps. First, after regionalizing based on road networks and executing a cluster analysis for regions according to the properties of POIs, the environmental noise functional regions (NFRs) of the urban area are presented. Then, surrounding POIs are used to infer the type of buildings, and according to the attraction of different building types and the whole population of the region, the population distribution at the building level is calculated. Finally, with the help of a noise map, an evaluation method for assessing an urban traffic noise-exposed population is proposed. The method is applied in the main urban area of Guangzhou, and the results reveal the followings. 1) At daytime and nighttime, 23.63% and 30.53% of the population, respectively, experience noise levels that exceed the noise standards. The per capita noise exposure value at daytime and nighttime is 0.9 dB and 2.0 dB, respectively. 2) The percentages of the exposed population of Yuexiu District were 28.89% at daytime and 35.65% at nighttime, which are the largest, followed by the exposed population percentages of Liwan, Haizhu, and Tianhe Districts. 3) From the view of different classes of NFRs, the percentages of the exposed population of Class 1 and Class 4 are larger than the percentages of the exposed population from the other classes, especially at nighttime (48.24% of Class 1 and 40.79% of Class 4). 4) Although there are masses of people affected by traffic noise, a large percentage of them (85%) experience not more than 5 dB of traffic noise superscale.

[Spatial distribution pattern and time series dynamics of Panonychus ulmi Koch in an apple orchard of Liaoning Province, Northeast China].

Panonychus ulmi Koch is one of the important pest insects of apple production in China. To clarify the spatiotemporal dynamics of P. ulmi on the apple tree crowns in an apple orchard of Liaoning, Northeast China, an investigation with random sampling was conducted on the pest mite number at each direction and each layer of the crowns in the whole growth season from May to November 2007. The spatial distribution pattern and time series dynamics of P. ulmi were analyzed by calculating the indices of aggregation and using the parameters of Iwao model. In the early and mid growth periods of apple tree, P. ulmi within whole crown fitted negative binomial distribution, presented an aggregated pattern, and its fundamental component was the group composed of several individuals that attracted each other. The aggregation intensity showed a negative fluctuation with population density, namely, high population density but low patchiness density, and low population density but high patchiness density, and there existed definite differences at different crown directions and layers, i. e., the patchiness density was the highest in south direction and the lowest in west direction, and was higher in mid and lower layers than in upper layer, and in inner layer than in outer layer.