Age-specific rates of hospital transfers in long-stay nursing home residents.

INTRODUCTION: hospital transfers and admissions are critical events in the care of nursing home residents. We sought to determine hospital transfer rates at different ages. METHODS: a cohort of 1,187 long-stay nursing home residents who had participated in a Centers for Medicare and Medicaid demonstration project. We analysed the number of hospital transfers of the study participants recorded by the Minimum Data Set. Using a modern regression technique, we depicted the annual rate of hospital transfers as a smooth function of age. RESULTS: transfer rates declined with age in a nonlinear fashion. Rates were the highest among residents younger than 60 years of age (1.30-2.15 transfers per year), relatively stable between 60 and 80 (1.17-1.30 transfers per year) and lower in those older than 80 (0.77-1.17 transfers per year). Factors associated with increased risk of transfers included prior diagnoses of hip fracture (annual incidence rate ratio or IRR: 2.057, 95% confidence interval (CI): [1.240, 3.412]), dialysis (IRR: 1.717, 95% CI: [1.313, 2.246]), urinary tract infection (IRR: 1.755, 95% CI: [1.361, 2.264]), pneumonia (IRR: 1.501, 95% CI: [1.072, 2.104]), daily pain (IRR: 1.297, 95% CI: [1.055,1.594]), anaemia (IRR: 1.229, 95% CI [1.068, 1.414]) and chronic obstructive pulmonary disease (IRR: 1.168, 95% CI: [1.010,1.352]). Transfer rates were lower in residents who had orders reflecting preferences for comfort care (IRR: 0.79, 95% CI: [0.665, 0.936]). DISCUSSION: younger nursing home residents may require specialised interventions to reduce hospital transfers; declining transfer rates with the oldest age groups may reflect preferences for comfort-focused care.

A ß-NMR study of the depth, temperature, and molecular-weight dependence of secondary dynamics in polystyrene: Entropy-enthalpy compensation and dynamic gradients near the free surface.

We investigated the depth, temperature, and molecular-weight (MW) dependence of the γ-relaxation in polystyrene glasses using implanted 8Li+ and ß-detected nuclear magnetic resonance. Measurements were performed on thin films with MW ranging from 1.1 to 641 kg/mol. The temperature dependence of the average 8Li spin-lattice relaxation time (T1 avg) was measured near the free surface and in the bulk. Spin-lattice relaxation is caused by phenyl ring flips, which involve transitions between local minima over free-energy barriers with enthalpic and entropic contributions. We used transition state theory to model the temperature dependence of the γ-relaxation, and hence T1 avg. There is no clear correlation of the average entropy of activation (Δ‡S̄) and enthalpy of activation (Δ‡H̄) with MW, but there is a clear correlation between Δ‡S̄ and Δ‡H̄, i.e., entropy-enthalpy compensation. This results in the average Gibbs energy of activation, Δ‡G, being approximately independent of MW. Measurements of the temperature dependence of T1 avg as a function of depth below the free surface indicate the inherent entropic barrier, i.e., the entropy of activation corresponding to Δ‡H̄ = 0, has an exponential dependence on the distance from the free surface before reaching the bulk value. This results in Δ‡G near the free surface being lower than the bulk. Combining these observations results in a model where the average fluctuation rate of the γ-relaxation has a "double-exponential" depth dependence. This model can explain the depth dependence of 1/T1 avg in polystyrene films. The characteristic length of enhanced dynamics is ∼6 nm and approximately independent of MW near room temperature.

Magnesium(II)-ATP Complexes in 1-Ethyl-3-Methylimidazolium Acetate Solutions Characterized by 31 Mg ß-Radiation-Detected NMR Spectroscopy.

The complexation of MgII with adenosine 5'-triphosphate (ATP) is omnipresent in biochemical energy conversion, but is difficult to interrogate directly. Here we use the spin- 1/2 ß-emitter 31 Mg to study MgII -ATP complexation in 1-ethyl-3-methylimidazolium acetate (EMIM-Ac) solutions using ß-radiation-detected nuclear magnetic resonance (ß-NMR). We demonstrate that (nuclear) spin-polarized 31 Mg, following ion-implantation from an accelerator beamline into EMIM-Ac, binds to ATP within its radioactive lifetime before depolarizing. The evolution of the spectra with solute concentration indicates that the implanted 31 Mg initially bind to the solvent acetate anions, whereafter they undergo dynamic exchange and form either a mono- (31 Mg-ATP) or di-nuclear (31 MgMg-ATP) complex. The chemical shift of 31 Mg-ATP is observed up-field of 31 MgMg-ATP, in accord with quantum chemical calculations. These observations constitute a crucial advance towards using ß-NMR to probe chemistry and biochemistry in solution.

Robust estimation of heterogeneous treatment effects using electronic health record data.

Estimation of heterogeneous treatment effects is an essential component of precision medicine. Model and algorithm-based methods have been developed within the causal inference framework to achieve valid estimation and inference. Existing methods such as the A-learner, R-learner, modified covariates method (with and without efficiency augmentation), inverse propensity score weighting, and augmented inverse propensity score weighting have been proposed mostly under the square error loss function. The performance of these methods in the presence of data irregularity and high dimensionality, such as that encountered in electronic health record (EHR) data analysis, has been less studied. In this research, we describe a general formulation that unifies many of the existing learners through a common score function. The new formulation allows the incorporation of least absolute deviation (LAD) regression and dimension reduction techniques to counter the challenges in EHR data analysis. We show that under a set of mild regularity conditions, the resultant estimator has an asymptotic normal distribution. Within this framework, we proposed two specific estimators for EHR analysis based on weighted LAD with penalties for sparsity and smoothness simultaneously. Our simulation studies show that the proposed methods are more robust to outliers under various circumstances. We use these methods to assess the blood pressure-lowering effects of two commonly used antihypertensive therapies.

Transformation of Fe-P Complexes in Bioreactors and P Recovery from Sludge: Investigation by XANES Spectroscopy.

The transformation of Fe-P complexes in bioreactors can be important for phosphorus (P) recovery from sludge. In this research, X-ray absorption near-edge structure analysis was conducted to quantify the transformation of Fe and P species in the sludge of different aging periods and in the subsequent acidogenic cofermentation for P recovery. P was readily removed from wastewater by Fe-facilitated coprecipitation and adsorption and could be extracted and recovered from sludge via acidogenic cofermentation and microbial iron reduction with food waste. The fresh Fe-based sludge mainly contained fresh ferrihydrite and amorphous FePO4 with sufficient accessible surface area, which was favorable for Fe-P mobilization and dissolution via microbial reaction. Ferric iron dosed into wastewater underwent rapid hydrolysis, clustering, aggregation, and slow crystallization to form hydrous iron oxides (HFO) with various complicated structures. With the aging of sludge in bioreactors, the HFO densified into phases with much reduced surface area and reactivity (e.g., goethite), which greatly increased the difficulty of P release and recovery. Thus, aging of P-containing sludge should be minimized in wastewater treatment systems for the purpose of P recovery.

Phosphorus Removal and Recovery from Wastewater using Fe-Dosing Bioreactor and Cofermentation: Investigation by X-ray Absorption Near-Edge Structure Spectroscopy.

A new phosphorus (P) removal and recovery process that integrates an FeCl3-dosing, membrane bioreactor (MBR), and side-stream cofermentation was developed for wastewater treatment. The Fe and P species and their transformation mechanisms via aerobic and anaerobic conditions were investigated with X-ray absorption near edge structure (XANES) spectroscopy. In the new treatment system, 98.4% of the total P in domestic wastewater was removed and retained in activated sludge in the MBR. During the subsequent acidogenic cofermentation with food waste, P in the MBR sludge was released and eventually recovered as vivianite, achieving an overall P recovery efficiency of 61.9% from wastewater. The main pathways for P removal and recovery with iron dosing and acidogenic fermentation were determined by XANES analysis. The results showed that Fe-enhanced P removal with the MBR was mainly achieved by precipitation as ferric phosphate (24.2%) and adsorption onto hydrous iron oxides (60.3%). During anaerobic fermentation, transition from Fe(III)-P to Fe(II)-P complex occurred in the sludge, leading to Fe(II) dissolution and P release. The pH decrease and microbial Fe reduction were crucial conditions for effective P extraction from the MBR sludge. The efficiency of P recovery increased with an increase in the fermentation time and organic load and a decrease of pH in the solution.

Acceptance and commitment therapy for symptom interference in metastatic breast cancer patients: a pilot randomized trial.

PURPOSE: Breast cancer is the leading cause of cancer mortality in women worldwide. With medical advances, metastatic breast cancer (MBC) patients often live for years with many symptoms that interfere with activities. However, there is a paucity of efficacious interventions to address symptom-related suffering and functional interference. Thus, this study examined the feasibility and preliminary efficacy of telephone-based acceptance and commitment therapy (ACT) for symptom interference with functioning in MBC patients. METHODS: Symptomatic MBC patients (N = 47) were randomly assigned to six telephone sessions of ACT or six telephone sessions of education/support. Patients completed measures of symptom interference and measures assessing the severity of pain, fatigue, sleep disturbance, depressive symptoms, and anxiety. RESULTS: The eligibility screening rate (64%) and high retention (83% at 8 weeks post-baseline) demonstrated feasibility. When examining within-group change, ACT participants showed decreases in symptom interference (i.e., fatigue interference and sleep-related impairment; Cohen's d range = - 0.23 to - 0.31) at 8 and 12 weeks post-baseline, whereas education/support participants showed minimal change in these outcomes (d range = - 0.03 to 0.07). Additionally, at 12 weeks post-baseline, ACT participants showed moderate decreases in fatigue and sleep disturbance (both ds = - 0.43), whereas education/support participants showed small decreases in these outcomes (ds = - 0.24 and - 0.18 for fatigue and sleep disturbance, respectively). Both the ACT and education/support groups showed reductions in depressive symptoms (ds = - 0.27 and - 0.28) at 12 weeks post-baseline. Group differences in all outcomes were not statistically significant. CONCLUSIONS: ACT shows feasibility and promise in improving fatigue and sleep-related outcomes in MBC patients and warrants further investigation.

Continuously tunable pulsed Ti:Sa laser self-seeded by an extended grating cavity.

A continuously tunable titanium:sapphire (Ti:Sa) laser self-seeded by an extended grating cavity was demonstrated and characterized. By inserting a partially reflecting mirror inside the cavity of a classic single-cavity grating laser, two oscillators are created: a broadband power oscillator and a narrowband oscillator with a prism beam expander and a diffraction grating in Littrow configuration. By coupling the grating cavity oscillation into the power oscillator, a power-enhanced narrow-linewidth laser oscillation is achieved. Compared to the classic grating laser, this simple modification significantly increases the laser output power without considerably broadening the linewidth. With most of the oscillating laser power confined inside the broadband power cavity and lower power incident onto the grating, the new configuration also allows higher pump power, which is typically limited by the thermal deformation of the grating coating at high oscillation power.

Machine learning for municipal sludge recycling by thermochemical conversion towards sustainability.

The sustainable disposal of high-moisture municipal sludge (MS) has received increasing attention. Thermochemical conversion technologies can be used to recycle MS into liquid/gas bio-fuel and value-added solid products. In this review, we compared energy recovery potential of common thermochemical technologies (i.e., incineration, pyrolysis, hydrothermal conversion) for MS disposal via statistical methods, which indicated that hydrothermal conversion had a great potential in achieving energy recovery from MS. The application of machine learning (ML) in MS recycling was discussed to decipher complex relationships among MS components, process parameters and physicochemical reactions. Comprehensive ML models should be developed considering successive reaction processes of thermochemical conversion in future studies. Furthermore, challenges and prospects were proposed to improve effectiveness of ML for energizing thermochemical conversion of MS regarding data collection and preprocessing, model optimization and interpretability. This review sheds light on mechanism exploration of MS thermochemical recycling by ML, and provide practical guidance for MS recycling.

Robust Estimation of Heterogeneous Treatment Effects: An Algorithm-based Approach.

Heterogeneous treatment effect estimation is an essential element in the practice of tailoring treatment to suit the characteristics of individual patients. Most existing methods are not sufficiently robust against data irregularities. To enhance the robustness of the existing methods, we recently put forward a general estimating equation that unifies many existing learners. But the performance of model-based learners depends heavily on the correctness of the underlying treatment effect model. This paper addresses this vulnerability by converting the treatment effect estimation to a weighted supervised learning problem. We combine the general estimating equation with supervised learning algorithms, such as the gradient boosting machine, random forest, and artificial neural network, with appropriate modifications. This extension retains the estimators' robustness while enhancing their flexibility and scalability. Simulation shows that the algorithm-based estimation methods outperform their model-based counterparts in the presence of nonlinearity and non-additivity. We developed an R package, RCATE, for public access to the proposed methods. To illustrate the methods, we present a real data example to compare the blood pressure-lowering effects of two classes of antihypertensive agents.

Machine learning-assisted exploration for carbon neutrality potential of municipal sludge recycling via hydrothermal carbonization.

In the context of advocating carbon neutrality, there are new requirements for sustainable management of municipal sludge (MS). Hydrothermal carbonization (HTC) is a promising technology to deal with high-moisture MS considering its low energy consumption (without drying pretreatment) and value-added products (i.e., hydrochar). This study applied machine learning (ML) methods to conduct a holistic assessment with higher heating value (HHV) of hydrochar, carbon recovery (CR), and energy recovery (ER) as model targets, yielding accurate prediction models with R2 of 0.983, 0.844 and 0.858, respectively. Furthermore, MS properties showed positive (e.g., carbon content, HHV) and negative (e.g., ash content, O/C, and N/C) influences on the hydrochar HHV. By comparison, HTC parameters play a critical role for CR (51.7%) and ER (52.5%) prediction. The primary sludge was an optimal HTC feedstock while anaerobic digestion sludge had the lowest potential. This study provided a comprehensive reference for sustainable MS treatment and industrial application.

Phosphate interactions with iron-titanium oxide composites: Implications for phosphorus removal/recovery from wastewater.

Understanding the interactions between phosphate (P) and mineral adsorbents is critical for removing and recovering P from wastewater, especially in the presence of both cationic and organic components. To this end, we investigated the surface interactions of P with an iron-titanium coprecipitated oxide composite in the presence of Ca (0.5-3.0 mM) and acetate (1-5 mM), and quantified the molecular complexes and tested the possible removal and recovery of P from real wastewater. A quantitative analysis of P K-edge X-ray absorption near edge structure (XANES) confirmed the inner-sphere surface complexation of P with both Fe and Ti, whose contribution to P adsorption relies on their surface charge determined by pH conditions. The effects of Ca and acetate on P removal were highly pH-dependent. At pH 7, Ca (0.5-3.0 mM) in solution significantly increased P removal by 13-30% by precipitating the surface-adsorbed P, forming hydroxyapatite (14-26%). The presence of acetate had no obvious influence on P removal capacity and molecular mechanisms at pH 7. At pH 4, the removal amount of P was not obviously affected by the presence of Ca and acetate. However, acetate and high Ca concentration jointly facilitated the formation of amorphous FePO4 precipitate, complicating the interactions of P with Fe-Ti composite. In comparison with ferrihydrite, the Fe-Ti composite significantly decreased the formation of amorphous FePO4 probably by decreasing Fe dissolution due to the coprecipitated Ti component, facilitating further P recovery. An understanding of these microscopic mechanisms can lead to the successful use and simple regeneration of the adsorbent to recover P from real wastewater.

Deep learning-assisted automated sewage pipe defect detection for urban water environment management.

A healthy sewage pipe system plays a significant role in urban water management by collecting and transporting wastewater and stormwater, which can be assessed by hydraulic model. However, sewage pipe defects have been observed frequently in recent years during regular pipe maintenance according to the captured interior videos of underground pipes by closed-circuit television (CCTV) robots. In this case, hydraulic model constructed based on a healthy pipe would produce large deviations with that in real hydraulic performance and even be out of work, which can result in unanticipated damages such as blockage collapse or stormwater overflows. Quick defect evaluation and defect quantification are the precondition to achieve risk assessment and model calibration of urban water management, but currently pipe defects assessment still largely relies on technicians to check the CCTV videos/images. An automated sewage pipe defect detection system is necessary to timely determine pipe issues and then rehabilitate or renew sewage pipes, while the rapid development of deep learning especially in recent five years provides a fantastic opportunity to construct automated pipe defect detection system by image recognition. Given the initial success of deep learning application in CCTV interpretation, the review (i) integrated the methodological framework of automated sewage pipe defect detection, including data acquisition, image pre-processing, feature extraction, model construction and evaluation metrics, (ii) discussed the state-of-the-art performance of deep learning in pipe defects classification, location, and severity rating evaluation (e.g., up to ~96 % of accuracy and 140 FPS of processing speed), and (iii) proposed risk assessment and model calibration in urban water management by considering pipe defects. This review introduces a novel practical application-oriented methodology including defect data acquisition by CCTV, model construction by deep learning, and model application, provides references for further improving accuracy and generalization ability of urban water management models in practical application.

A new high parallel-field spectrometer at TRIUMF's ß-NMR facility.

A new high field spectrometer has been built to extend the capabilities of the ß-detected nuclear magnetic resonance (ß-NMR) facility at TRIUMF. This new beamline extension allows ß-NMR spectroscopy to be performed with fields up to 200 mT parallel to a sample's surface (perpendicular to the ion beam), allowing depth-resolved studies of local electromagnetic fields with spin polarized probes at a much higher applied magnetic field than previously available in this configuration. The primary motivation and application is to allow studies of superconducting radio frequency (SRF) materials close to the critical fields of Nb metal, which is extensively used to fabricate SRF cavities. The details of the design considerations and implementation of the ultra-high vacuum (UHV) system, ion optics, and beam diagnostics are presented here. Commissioning of the beamline and spectrometer with radioactive ions are also reported here. Future capabilities and applications in other areas are also described.

Genome-centric metagenomics provides new insights into metabolic pathways of polyhydroxyalkanoates biosynthesis and functional microorganisms subsisting on municipal organic wastes.

The microbial community of a sequencing batch reactor operated under feast and famine conditions for production of polyhydroxyalkanoates (PHAs) was characterized through high-throughput sequencing and metagenomic analysis. The fermented food waste and chemically-enhanced primary sludge was fed in this bioreactor. After acclimation, the PHA yield achieved as high as 0.60-0.69 g CODPHA/g CODS. The complete changes of microbial community structure were found during shifts of feedstock. A synthesis of SCL/MCL-PHAs pathway was established for PHA-producing bioreactor in this mixed-culture system. The structure-performance relationship of PHA-producing microbial community and feedstock composition was investigated. The results showed that microbial community tends to be decentralized and prefer team work for PHA synthesis to consume the multiple substrates and digest inevitable non-VFA contents in fermented liquor. This study also discovered unreported potential PHA producers (e.g., genera Tabrizicola, Nannocystis, Ga0077539, Ga0077559, JOSHI-001, SNC69-320 and UBA2334) subsisting on municipal organic wastes and expands the current knowledge about mixed-culture system that the PHA synthesis pathway is widely existed in activated sludge.

Environments and situations as correlates of eating and drinking among women living with obesity and urban poverty.

Objective: One path to improving weight management may be to lessen the self-control burden of physical activity and healthier food choices. Opportunities to lessen the self-control burden might be uncovered by assessing the spatiotemporal experiences of individuals in daily context. This report aims to describe the time, place, and social context of eating and drinking and 6-month weight change among 209 midlife women (n = 113 African-American) with obesity receiving safety-net primary care. Methods: Participants completed baseline and 6-month weight measures, observations and interviews regarding obesogenic cues in the home environment, and up to 12 ecological momentary assessments (EMA) per day for 30 days inquiring about location, social context, and eating and drinking. Results: Home was the most common location (62%) at times of EMA notifications. Participants reported "yes" to eating or drinking at the time of nearly one in three (31.1% ± 13.2%) EMA notifications. Regarding social situations, being alone was significantly associated with less frequent eating and drinking (OR = 0.75) unless at work in which case being alone was significantly associated with a greater frequency of eating or drinking (OR = 1.43). At work, eating was most common late at night, whereas at home eating was most frequent in the afternoon and evening hours. However, eating and drinking frequency was not associated with 6-month weight change. Conclusions: Home and work locations, time of day, and whether alone may be important dimensions to consider in the pursuit of more effective weight loss interventions. Opportunities to personalize weight management interventions, whether digital or human, and lessen in-the-moment self-control burden might lie in identifying times and locations most associated with caloric consumption.Clinical trial registration: NCT03083964 in clinicaltrials.gov.

Poverty, Comorbidity, and Ethnicity: COVID-19 Outcomes in a Safety Net Health System.

Objective: To determine if race-ethnicity is correlated with case-fatality rates among low-income patients hospitalized for COVID-19. Research Design: Observational cohort study using electronic health record data. Patients: All patients assessed for COVID-19 from March 2020 to January 2021 at one safety net health system. Measures: Patient demographic and clinical characteristics, and hospital care processes and outcomes. Results: Among 25,253 patients assessed for COVID-19, 6,357 (25.2%) were COVID-19 positive: 1,480 (23.3%) hospitalized; 334 (22.6%) required intensive care; and 106 (7.3%) died. More Hispanic patients tested positive (51.8%) than non-Hispanic Black (31.4%) and White patients (16.7%, P<.001]. Hospitalized Hispanic patients were younger, more often uninsured, and less likely to have comorbid conditions. Non-Hispanic Black patients had significantly more diabetes, hypertension, obesity, chronic kidney disease, and asthma (P<.05). Non-Hispanic White patients were older and had more cigarette smoking history, COPD, and cancer. Non-Hispanic White patients were more likely to receive intensive care (29.6% vs 21.1% vs 20.8%, P=.007) and more likely to die (12% vs 7.3% vs 3.5%, P<.001) compared with non-Hispanic Black and Hispanic patients, respectively. Length of stay was similar for all groups. In logistic regression models, Medicaid insurance status independently correlated with hospitalization (OR 3.67, P<.001) while only age (OR 1.076, P<.001) and cerebrovascular disease independently correlated with in-hospital mortality (OR 2.887, P=.002). Conclusions: Observed COVID-19 in-hospital mortality rate was lower than most published rates. Age, but not race-ethnicity, was independently correlated with in-hospital mortality. Safety net health systems are foundational in the care of vulnerable patients suffering from COVID-19, including patients from under-represented and low-income groups.

AMOTL2­knockdown promotes the proliferation, migration and invasion of glioma by regulating ß­catenin nuclear localization.

Glioblastoma multiforme (GBM) is the most prevalent type of malignant cancer in the adult central nervous system; however, its mechanism remains unclear. Angiomotin­like 2 (AMOTL2) is a member of the motin family of angiostatin­binding proteins. It has been reported as an oncogene in cervical and breast cancer, but its association with glioma remains unknown. The aim of the present study was to investigate AMOTL2­regulated processes in glioma cell lines using extensive in vitro assays and certain bioinformatics tools. These results revealed that AMOTL2 was downregulated in high­grade glioma cells and tissues, with patients with glioma exhibiting a high AMOTL2 expression having a higher survival rate. The results of the glioma cell phenotype experiment showed that AMOTL2 suppressed GBM proliferation, migration and invasion. In addition, immunoblotting, co­immunoprecipitation and immunofluorescence assays demonstrated that AMOTL2 could directly bind to ß­catenin protein, the key molecule of the Wnt signaling pathway, and regulate its downstream genes by regulating ß­catenin nuclear translocation. In conclusion, the present study demonstrated that AMOTL2 inhibited glioma proliferation, migration and invasion by regulating ß­catenin nuclear localization. Thus, AMOTL2 may serve as a therapeutic target to further improve the prognosis and prolong survival time of patients with glioma.

An efficacy comparison of hair removal utilizing a diode laser and an Nd:YAG laser system in Chinese women.

BACKGROUND: The 800 nm diode laser and the 1064 nm Nd:YAG laser have been used successfully for hair removal for many years. OBJECTIVE: To compare the efficacy of a diode laser with a Nd:YAG laser regarding axillary fossa hair removal in Chinese women. METHODS: Twenty-nine Chinese women underwent three treatment sessions at 4-week intervals with a diode laser (34-38 J/cm(2)) on one side and a Nd:YAG laser (34-40 J/cm(2)) on the other side. Assessments included the reduction of hair diameter following treatment, the regrowth rate in hair length, total hair reduction and the immediate pain associated with the treatments. RESULTS: At follow-up visit number 1 (4 weeks after the first session), the average reduction in hair diameter on the diode laser side and the Nd:YAG laser side was 2.44 µm and -0.6 µm, respectively. The regrowth rates of the hair were 61.93 µm/day and 59.84 µm/day, respectively, which were not statistically significant (p > 0.05). At follow-up visit number 1, hair reduction was 60.09% and 41.44%, respectively. At follow-up visit number 2 (4 weeks after the second session), hair reduction was noted to be 78.56% and 64.50%, respectively, which were both statistically significant (p < 0.05). Immediate pain scores at the first session were 6.97 and 6.17, respectively; at the second session were 5.48 and 6.69, respectively; and at the third session were 5.76 and 7.45, respectively; all statistically significant (p < 0.05). CONCLUSIONS: The diode laser showed more efficacy and was found to be more comfortable than the Nd:YAG laser for axillary fossa hair removal in Chinese women.

Characterization and mitigation of the fouling of flat-sheet ceramic membranes for direct filtration of the coagulated domestic wastewater.

Ceramic membranes allow a high filtration flux with a low fouling propensity. Direct filtration of municipal wastewater using flat-sheet ceramic membranes (FSCM) is an attractive and promising technology for wastewater treatment and resource recovery. Urgent need is to determine the fouling behavior of FSCM and its optimal cleaning strategy in direct filtration applications. This study was conducted on pre-coagulation of sewage with FeCl3 (20 mg Fe/L) or polyaluminum chloride (15 mg Al/L), followed by FSCM filtration at around 1.0 m/d (as high as 41.7 L/m2-h in flux). The results showed that the coagulation-FSCM filtration removed chemical oxygen demand and total phosphorus by up to 90.0% and 99.9%, respectively. The pollutants (organics and nutrients) in the sewage influent were concentrated into the sludge for potential resource recovery. Without pre-coagulation, foulants easily entered the membrane pores, causing rapid membrane fouling. Chemically enhanced coagulation greatly decreased the membrane fouling rate by aggregating various foulants into flocs. Fouled membranes were effectively renewed by physical means, such as water flushing and sonication, or a short period of chemical backwashing with NaOH, HCl or oxidizing agents. The study revealed the fouling mechanisms of FSCM in sewage filtration and developed effective cleaning strategies for its long-term operation.