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In this paper, a tree-like branching microchannel with bifurcating interconnections is designed for gas turbine blade cooling. A theoretical analysis, experimental study, and numerical simulation of the heat transfer and hydrodynamic characteristics of the tree-like branching microchannel is performed, and the influence of the total number of branching levels m on the anti-clogging performance is also studied. The results indicate that the total heat transfer ratio and pressure drop ratio are closely related to the structur ne parameters. The comprehensive thermal performance increase with an increase in the ratio of Lb/L0 and fractal dimension D. Nu/Nus, f/fs, and η are increased as m increases from 3 to 5. Furthermore, the tree-like microchannel network exhibits robustness for cooling gas turbine blades. A greater total number of branching levels and a higher Re number are advantageous for enhancing the anti-clogging performance of the tree-like branching microchannel.

The PANI/Mesoporous MnO2 composites were prepared through a simple one step method and we introduced the KI-H2SO4 solution as the electrolyte of PANI/MnO2 composites creatively. The characterization of structure, morphology, and composition are obtained by X-ray diffraction, Fourier transform infrared spectroscopy, thermal gravity analysis, Raman spectra, and scanning electron microscope. The electrochemical performances were investigated by constant-current charge–discharge, the voltammetry curve, and alternating current (AC) impedance technique. The specific capacitance of composites is 1405 F/g, which is almost 10 times larger than MnO2 (158 F/g). We also find that the iodide concentration is closely related to the specific capacitance. Therefore, we explored the specific capacitance at different iodide concentration (0.05, 0.1, 0.2, 0.5, and 1 M), the results indicated that the specific capacitance reached a maximum value (1580 F/g) at 0.5 mol/L. Additionally, the PANI/Mesoporous MnO2 composites not only exhibited a good ratio discharge property (857 F/g) at high current density, but also revealed an excellent cycling stability after 500 cycles, which retained 90% of the original specific capacitance.

Among patients who are discharged from the Emergency Department (ED), about 3% return within 30 days. Revisits can be related to the nature of the disease, medical errors, and/or inadequate diagnoses and treatment during their initial ED visit. Identification of high-risk patient population can help device new strategies for improved ED care with reduced ED utilization. A decision tree based model with discriminant Electronic Medical Record (EMR) features was developed and validated, estimating patient ED 30 day revisit risk. A retrospective cohort of 293,461 ED encounters from HealthInfoNet (HIN), Maine's Health Information Exchange (HIE), between January 1, 2012 and December 31, 2012, was assembled with the associated patients' demographic information and one-year clinical histories before the discharge date as the inputs. To validate, a prospective cohort of 193,886 encounters between January 1, 2013 and June 30, 2013 was constructed. The c-statistics for the retrospective and prospective predictions were 0.710 and 0.704 respectively. Clinical resource utilization, including ED use, was analyzed as a function of the ED risk score. Cluster analysis of high-risk patients identified discrete sub-populations with distinctive demographic, clinical and resource utilization patterns. Our ED 30-day revisit model was prospectively validated on the Maine State HIN secure statewide data system. Future integration of our ED predictive analytics into the ED care work flow may lead to increased opportunities for targeted care intervention to reduce ED resource burden and overall healthcare expense, and improve outcomes.

Identifying patients at risk of a 30-day readmission can help providers design interventions, and provide targeted care to improve clinical effectiveness. This study developed a risk model to predict a 30-day inpatient hospital readmission for patients in Maine, across all payers, all diseases and all demographic groups. Our objective was to develop a model to determine the risk for inpatient hospital readmission within 30 days post discharge. All patients within the Maine Health Information Exchange (HIE) system were included. The model was retrospectively developed on inpatient encounters between January 1, 2012 to December 31, 2012 from 24 randomly chosen hospitals, and then prospectively validated on inpatient encounters from January 1, 2013 to December 31, 2013 using all HIE patients. A risk assessment tool partitioned the entire HIE population into subgroups that corresponded to probability of hospital readmission as determined by a corresponding positive predictive value (PPV). An overall model c-statistic of 0.72 was achieved. The total 30-day readmission rates in low (score of 0-30), intermediate (score of 30-70) and high (score of 70-100) risk groupings were 8.67%, 24.10% and 74.10%, respectively. A time to event analysis revealed the higher risk groups readmitted to a hospital earlier than the lower risk groups. Six high-risk patient subgroup patterns were revealed through unsupervised clustering. Our model was successfully integrated into the statewide HIE to identify patient readmission risk upon admission and daily during hospitalization or for 30 days subsequently, providing daily risk score updates. The risk model was validated as an effective tool for predicting 30-day readmissions for patients across all payer, disease and demographic groups within the Maine HIE. Exposing the key clinical, demographic and utilization profiles driving each patient's risk of readmission score may be useful to providers in developing individualized post discharge care plans.

Necrotizing enterocolitis (NEC) is a major source of neonatal morbidity and mortality. Since there is no specific diagnostic test or risk of progression model available for NEC, the diagnosis and outcome prediction of NEC is made on clinical grounds. The objective in this study was to develop and validate new NEC scoring systems for automated staging and prognostic forecasting. A six-center consortium of university based pediatric teaching hospitals prospectively collected data on infants under suspicion of having NEC over a 7-year period. A database comprised of 520 infants was utilized to develop the NEC diagnostic and prognostic models by dividing the entire dataset into training and testing cohorts of demographically matched subjects. Developed on the training cohort and validated on the blind testing cohort, our multivariate analyses led to NEC scoring metrics integrating clinical data. Machine learning using clinical and laboratory results at the time of clinical presentation led to two nec models: (1) an automated diagnostic classification scheme; (2) a dynamic prognostic method for risk-stratifying patients into low, intermediate and high NEC scores to determine the risk for disease progression. We submit that dynamic risk stratification of infants with NEC will assist clinicians in determining the need for additional diagnostic testing and guide potential therapies in a dynamic manner. http://translationalmedicine.stanford.edu/cgi-bin/NEC/index.pl and smartphone application upon request.

Type 2 diabetes mellitus (T2DM), with increased risk of serious long-term complications, currently represents 8.3% of the adult population. We hypothesized that a critical transition state prior to the new onset T2DM can be revealed through the longitudinal electronic medical record (EMR) analysis. We applied the transition-based network entropy methodology which previously identified a dynamic driver network (DDN) underlying the critical T2DM transition at the tissue molecular biological level. To profile pre-disease phenotypical changes that indicated a critical transition state, a cohort of 7,334 patients was assembled from the Maine State Health Information Exchange (HIE). These patients all had their first confirmative diagnosis of T2DM between January 1, 2013 and June 30, 2013. The cohort's EMRs from the 24 months preceding their date of first T2DM diagnosis were extracted. Analysis of these patients' pre-disease clinical history identified a dynamic driver network (DDN) and an associated critical transition state six months prior to their first confirmative T2DM state. This 6-month window before the disease state provides an early warning of the impending T2DM, warranting an opportunity to apply proactive interventions to prevent or delay the new onset of T2DM.

In recent years, manganese dioxide has become a research hotspot as an electrode material because of its low price. However, it has also become an obstacle to industrialization due to its low ratio of capacitance and the low rate performance which is caused by the poor electrical conductivity. In this study, a KI solution with electrochemical activity was innovatively applied to the electrolyte, and we systematically investigated the rate performance of the mesoporous manganese dioxide and the composite electrode with silver nanowires in supercapacitors. The results showed that when mesoporous manganese dioxide and mesoporous manganese dioxide/silver nanowires composite were used as electrodes, the strength of the current was amplified five times (from 0.1 to 0.5 A/g), the remaining rates of specific capacitance were 95% (from 205.5 down to 197.1 F/g) and 92% (from 208.1 down to 191.7 F/g) in the KI electrolyte, and the rate performance was much higher than which in an Na2SO4 electrolyte with a remaining rate of 25% (from 200.3 down to 49.1 F/g) and 60% (from 187.2 down to 113.1 F/g). The morphology and detail structure were investigated by Scanning electron microscopy, X-ray diffraction, Fourier transform infrared spectrometry and Nitrogen adsorption-desorption isotherms. The electrochemical performance was assessed by cyclic voltammograms, galvanostatic charge/discharge and electrochemical impedance spectroscopy.

The attenuated Salmonella typhimurium χ4550 strain was used to harbour a reconstructed bicistronic DNA vaccine against porcine rotavirus, which carried the rotavirus nonstructural protein 4 (NSP4) and VP7 genes simultaneously. Using a balanced lethal system, the kanamycin resistance gene of expressing eukaryotic plasmids pVAX1 and pVAXD were replaced by the aspartate β-semialdehyde dehydrogenase (asd) gene. The NSP4 cleavage product (259–525) of rotavirus OSU strain and VP7 full-length genes were amplified by reverse transcription polymerase chain reaction and then inserted into the eukaryotic single-expression plasmid, pVAX1-asd, and the eukaryotic dual-expression plasmid, pVAXD-asd, respectively. The recombinant plasmids pVAX1-asd-NSP4, pVAX1-asd-VP7 and pVAXD-asd-NSP4-VP7 were transformed into the attenuated S. typhimurium χ4550 strain by electrotransformation. An indirect immunofluorescence assay of the expressed COS-7 cell suggested that the recombinant S. typhimurium χ4550 strain was constructed successfully. The recombinant S. typhimurium χ4550 strain was orally administered to BALB/c mice. The group immunised with dual- expression plasmids produced a significantly higher level of serum Immunoglobulin G (IgG) and intestinal Immunoglobulin A (IgA) than the group immunised with single-expression plasmids. These results indicated that eukaryotic bicistronic plasmid DNA vaccines could be successfully constructed to enhance humoural, mucosal and cellular immune response against rotavirus infection.

Mesoporous polyaniline-silica nanocomposites with a full interpenetrating structure for pseudocapacitors were synthesized via the vapor phase approach. The morphology and structure of the nanocomposites were deeply investigated by scanning electron microscopy, infrared spectroscopy, X-ray diffraction, thermal gravimetric analysis and nitrogen adsorption-desorption tests. The results present that the mesoporous nanocomposites possess a uniform particle morphology and full interpenetrating structure, leading to a continuous conductive polyaniline network with a large specific surface area. The electrochemical performances of the nanocomposites were tested in a mixed solution of sulfuric acid and potassium iodide. With the merits of a large specific surface area and suitable pore size distribution, the nanocomposite showed a large specific capacitance (1702.68 farad (F)/g) due to its higher utilization of the active material. This amazing value is almost three-times larger than that of bulk polyaniline when the same mass of active material was used.

Conventional ionic polymer–metal composite actuator had two major drawbacks: (i) complicated and time-consuming fabrication of noble metal electrode and (ii) degradation of electromechanical property in open air. In this study, we proposed a facile method to fabricate graphene oxide (GO)-based electromechanical actuators with surface-reduced graphene oxide (rGO) as its electrodes. Such GO actuators were fabricated by evaporating the aqueous dispersion of exfoliated GO nanosheets, followed with in situ reduction of the surface of the GO nanosheets by hydrogen iodide (HI). When subjected to a 3 V electrical field, the GO actuator performed electromechanical bending action with a tip displacement of 5 mm and exhibited a blocking force of 10 gf g⁻¹ for 10 s. In addition, the GO actuator showed an almost identical actuating behavior in cyclic measurements. The durable actuation could be attributed to both the unique lamellar structure of the GO film which blocked the diffusion of cationic clusters and the surface rGO electrodes which protected the interlamellar water from evaporation.