Spent Yeast-Derived 3D Porous Carbon Skeleton as Low-Cost D-Mannitol Supporting Material for Medium Temperature Thermal Energy Storage.

Shape-stable phase change materials (ss-PCMs) are extensively applied in renewable energy storage. The core for realizing high latent heat and good thermal stability of ss-PCMs is the designation of suitable supporting skeletons that can effectively preserve the PCMs from leaking out. In this study, ss-PCMs impregnated by D-mannitol were prepared using a waste yeast-derived carbon (YC) as the support material. YC possesses a large surface area (669.90 m2/g), which can provide sufficient phase transition space and nucleation sites for D-mannitol. The results indicated that a reduced supercooling of 44.76 °C for YC/D-mannitol ss-PCMs can be realized. The ss-PCMs also exhibited good cycling stability, with latent heat loss rates of 4.00% and 2.15% after 200 thermal cycles. We further demonstrate that YC provides restricted space for mannitol to inhibit the supercooling mechanism. The YC/D-mannitol ss-PCMs exhibited great promise for solar heat storage and industrial waste heat recovery in the medium temperature domain.

The Assessment of Sleep Quality in Patients Following Valve Repair and Valve Replacement for Infective Endocarditis: A Retrospective Study at a Single Center.

BACKGROUND The aim of this study was to measure sleep quality among patients who underwent infective endocarditis (IE) surgery and identify the risk factors involved in sleep disorders. MATERIAL AND METHODS In this study, we used actigraphy, the Pittsburgh Sleep Quality Index (PSQI), and Epworth Sleep Scale (ESS) to determine the clinical characteristics of sleep disorders in 116 patients with IE who were in rehabilitation after surgery. RESULTS Our results showed that 46 (39.7%) patients had sleep efficiency over 85%, while 70 (60.3%) patients had sleep efficiency below 85%. The correlation analysis showed that sleep efficiency was related to the duration of the disease, with a longer duration leading to lower sleep efficiency (P=0.031). The sleep efficiency of patients with IE following surgery was also affected by alcohol consumption; however, surprisingly, patients with "heavy" alcohol consumption had higher sleep efficiency (P=0.030). We found a significant correlation between sleep efficiency and postoperative interleukin-6 (IL) levels, C-reactive protein (CRP) levels, and preoperative erythrocyte sedimentation rate (P<0.05). No significant correlation was found between brain natriuretic peptide levels and sleep efficiency, PSQI score, or ESS score. Postoperative hemoglobin (Hb) level was associated with sleep efficiency (R=0.194, P=0.036), but there was no statistically significant correlation between the PSQI and ESS scores. Postoperative alanine transaminase (ALT) showed a significant negative correlation with sleep efficiency (R=-0.27, P=0.003). CONCLUSIONS We found a high prevalence of sleep disorders in patients with IE along with an increase in inflammatory factors, including postoperative IL-6, CRP, ALT, and Hb levels.

ECG-based prediction algorithm for imminent malignant ventricular arrhythmias using decision tree.

Spontaneous prediction of malignant ventricular arrhythmia (MVA) is useful to avoid delay in rescue operations. Recently, researchers have developed several algorithms to predict MVA using various features derived from electrocardiogram (ECG). However, there are several unresolved issues regarding MVA prediction such as the effect of number of ECG features on a prediction remaining unclear, possibility that an alert for occurring MVA may arrive very late and uncertainty in the performance of the algorithm predicting MVA minutes before onset. To overcome the aforementioned problems, this research conducts an in-depth study on the number and types of ECG features that are implemented in a decision tree classifier. In addition, this research also investigates an algorithm's execution time before the occurrence of MVA to minimize delays in warnings for MVA. Lastly, this research aims to study both the sensitivity and specificity of an algorithm to reveal the performance of MVA prediction algorithms from time to time. To strengthen the results of analysis, several classifiers such as support vector machine and naive Bayes are also examined for the purpose of comparison study. There are three phases required to achieve the objectives. The first phase is literature review on existing relevant studies. The second phase deals with design and development of four modules for predicting MVA. Rigorous experiments are performed in the feature selection and classification modules. The results show that eight ECG features with decision tree classifier achieved good prediction performance in terms of execution time and sensitivity. In addition, the results show that the highest percentage for sensitivity and specificity is 95% and 90% respectively, in the fourth 5-minute interval (15.1 minutes-20 minutes) that preceded the onset of an arrhythmia event. Such results imply that the fourth 5-minute interval would be the best time to perform prediction.

Two-stage pervaporation process for effective in situ removal acetone-butanol-ethanol from fermentation broth.

Two-stage pervaporation for ABE recovery from fermentation broth was studied to reduce the energy cost. The permeate after the first stage in situ pervaporation system was further used as the feedstock in the second stage of pervaporation unit using the same PDMS/PVDF membrane. A total 782.5g/L of ABE (304.56g/L of acetone, 451.98g/L of butanol and 25.97g/L of ethanol) was achieved in the second stage permeate, while the overall acetone, butanol and ethanol separation factors were: 70.7-89.73, 70.48-84.74 and 9.05-13.58, respectively. Furthermore, the theoretical evaporation energy requirement for ABE separation in the consolidate fermentation, which containing two-stage pervaporation and the following distillation process, was estimated less than ∼13.2MJ/kg-butanol. The required evaporation energy was only 36.7% of the energy content of butanol. The novel two-stage pervaporation process was effective in increasing ABE production and reducing energy consumption of the solvents separation system.