Biochemical changes in low-salt solid-state fermented soy sauce

Low-salt solid-state fermentation soy sauce was prepared with defatted soy bean and wheat bran. Biochemical changes during the aging of the soy sauce mash were investigated. Results showed that after a 15-day aging period, the contents of total nitrogen, formol titration nitrogen, free amino acids, reducing sugar, total sugar and the brown color were increased. However, pH was decreased during the fermentation period. Furthermore, contents of total free amino acids in low-salt solid-state fermentation soy sauce fluctuated during the fermentation period, and in most periods, it was increased. The analysis of free amino acid composition shows that the contents of glutamic acid, aspartic acid, alanine and leucine were higher than other amino acids. Therefore, it means that these amino acids may contribute to the taste and flavor of low-salt solid-state fermentation soy sauce. The biochemical changes characters were due to enzyme activities, solution balance and reaction balance, and biochemical changes contributed to the improvement of the flavor of low-salt solid-state fermented soy sauce. Analyzing the biochemical change in the fermented process of soy sauce is helpful in finding out the shortcoming of low-salt solid-state fermented soy sauce.Key words: Low-salt solid-state fermented soy sauce, biochemical changes, fermentation period, chemicalcomposition

A Study on Nonthermal Irreversible Electroporation of the Thyroid.

BackgroundNonthermal irreversible electroporation is a minimally invasive surgery technology that employs high and brief electric fields to ablate undesirable tissues. Nonthermal irreversible electroporation can ablate only cells while preserving intact functional properties of the extracellular structures. Therefore, nonthermal irreversible electroporation can be used to ablate tissues safely near large blood vessels, the esophagus, or nerves. This suggests that it could be used for thyroid ablation abutting the esophagus. This study examines the feasibility of using nonthermal irreversible electroporation for thyroid ablation.MethodsRats were used to evaluate the effects of nonthermal irreversible electroporation on the thyroid. The procedure entails the delivery of high electric field pulses (1-3 kV/cm, 100 microseconds) between 2 surface electrodes bracing the thyroid. The right lobe was treated with various nonthermal irreversible electroporation pulse sequences, and the left was the control. After 24 hours of the nonthermal irreversible electroporation treatment, the thyroid was examined with hemotoxylin and eosin histological analysis. Mathematical models of electric fields and the Joule heating-induced temperature raise in the thyroid were developed to examine the experimental results.ResultsTreatment with nonthermal irreversible electroporation leads to follicular cells damage, associated with cell swelling, inflammatory cell infiltration, and cell ablation. Nonthermal irreversible electroporation spares the trachea structure. Unusually high electric fields, for these types of tissue, 3000 V/cm, are needed for thyroid ablation. The mathematical model suggests that this may be related to the heterogeneous structure of the thyroid-induced distortion of local electric fields. Moreover, most of the tissue does not experience thermal damage inducing temperature elevation. However, the heterogeneous structure of the thyroid may cause local hot spots with the potential for local thermal damage.ConclusionNonthermal irreversible electroporation with 3000 V/cm can be used for thyroid ablation. Possible applications are treatment of hyperthyroidism and thyroid cancer. The highly heterogeneous structure of the thyroid distorts the electric fields and temperature distribution in the thyroid must be considered when designing treatment protocols for this tissue type

Self-assembly of 3D fennel-like Co3O4 with thirty-six surfaces for high performance supercapacitor

Three-dimensional (3D) fennel-like cobalt oxide (II,III) (Co3O4) particles with thirty-six surfaces on nickel foams were prepared via a simple hydrothermal synthesis method and its growth process was also researched. The crystalline structure and morphology were investigated by X-ray diffraction (XRD), scanning electron microscopy (SEM), and Raman spectroscopy. The Brunauer-Emmett Teller (BET) analysis revealed that 3D fennel-like Co3O4 particles have high specific surface area. Therefore, the special structure with thirty-six surfaces indicates the good electrochemical performance of the micron-nanometer material as electrode material for supercapacitors. The cyclic voltammetry (CV), galvanostatic charge-discharge, and electrochemical impedance spectroscopy (EIS) were conducted to evaluate the electrochemical performances. Compared with other morphological materials of the similar sizes, the Co3O4 particles on nickel foam exhibit a high specific capacitance of 384.375 F.g(-1) at the current density of 3A.g(-1) and excellent cycling stability of a capacitance retention of 96.54% after 1500 galvanostatic charge-discharge cycles in 6M potassium hydroxide (KOH) electrolyte

Dynamic Analysis and Control of the Clutch Filling Process in Clutch-to-Clutch Transmissions

Clutch fill control in clutch-to-clutch transmissions influences shift quality considerably. An oncoming clutch should be applied synchronously with the release of an offgoing clutch to shift gear smoothly; therefore, the gap between the piston and clutch plates should be eliminated when the torque capacity is near zero at the end of the clutch fill phase. Open-loop control is typically implemented for the clutch fill because of the cost of pressure sensor. Low control precision causes underfill or overfill to occur, deteriorating shift quality. In this paper, a mathematical model of an electrohydraulic clutch shift control system is presented. Special dynamic characteristic parameters for optimal clutch fill control are subsequently proposed. An automatic method for predicting initial fill control parameters is proposed to eliminate distinct discrepancies among transmissions caused by manufacturing or assembling errors. To prevent underfill and overfill, a fuzzy adaptive control method is proposed, in which clutch fill control parameters are adjusted self-adaptively and continually. Road vehicle test results proved that applying the fuzzy adaptive method ensures the consistency of shift quality even after the transmission’s status is changed

Deterministic-Statistical Approach for an Inverse Acoustic Source Problem using Multiple Frequency Limited Aperture Data

We propose a deterministic-statistical method for an inverse source problem using multiple frequency limited aperture far field data. The direct sampling method is used to obtain a disc such that it contains the compact support of the source. The Dirichlet eigenfunctions of the disc are used to expand the source function. Then the inverse problem is recast as a statistical inference problem for the expansion coefficients and the Bayesian inversion is employed to reconstruct the coefficients. The stability of the statistical inverse problem with respect to the measured data is justified in the sense of Hellinger distance. A preconditioned Crank-Nicolson (pCN) Metropolis-Hastings (MH) algorithm is implemented to explore the posterior density function of the unknowns. Numerical examples show that the proposed method is effective for both smooth and non-smooth sources given limited-aperture data

Adverse event detection by integrating twitter data and VAERS

Background: Vaccinehasbeenoneofthemostsuccessfulpublichealthinterventionstodate.However,vaccines are pharmaceutical products that carry risks so that many adverse events (AEs) are reported after receiving vaccines. Traditional adverse event reporting systems suffer from several crucial challenges including poor timeliness. This motivates increasing social media-based detection systems, which demonstrate successful capability to capture timely and prevalent disease information. Despite these advantages, social media-based AE detection suffers from serious challenges such as labor-intensive labeling and class imbalance of the training data. Results: Totacklebothchallengesfromtraditionalreportingsystemsandsocialmedia,weexploittheircomplementary strength and develop a combinatorial classification approach by integrating Twitter data and the Vaccine Adverse Event Reporting System (VAERS) information aiming to identify potential AEs after influenza vaccine. Specifically, we combine formal reports which have accurately predefined labels with social media data to reduce the cost of manual labeling; in order to combat the class imbalance problem, a max-rule based multi-instance learning method is proposed to bias positive users. Various experiments were conducted to validate our model compared with other baselines. We observed that (1) multi-instance learning methods outperformed baselines when only Twitter data were used; (2) formal reports helped improve the performance metrics of our multi-instance learning methods consistently while affecting the performance of other baselines negatively; (3) the effect of formal reports was more obvious when the training size was smaller. Case studies show that our model labeled users and tweets accurately. Conclusions: WehavedevelopedaframeworktodetectvaccineAEsbycombiningformalreportswithsocialmedia data. We demonstrate the power of formal reports on the performance improvement of AE detection when the amount of social media data was small. Various experiments and case studies show the effectiveness of our model