The Overshooting Hypothesis of Agricultural Prices: The Role of Asset Substitutability

By allowing for various degrees of asset substitutability between bonds and agricultural products, this paper reexamines the robustness of the overshooting hypothesis of agricultural product prices. It is found, in both a closed economy and an open economy, that the crucial factor determining whether agricultural prices overshoot or undershoot their long-run response following an expansion in the money stock depends upon the extent of asset substitutability between bonds and agricultural goods.asset substitutability, commodity prices, overshooting, Demand and Price Analysis,

Predicting effects of blood flow rate and size of vessels in a vasculature on hyperthermia treatments using computer simulation

<p>Abstract</p> <p>Background</p> <p>Pennes Bio Heat Transfer Equation (PBHTE) has been widely used to approximate the overall temperature distribution in tissue using a perfusion parameter term in the equation during hyperthermia treatment. In the similar modeling, effective thermal conductivity (K_eff) model uses thermal conductivity as a parameter to predict temperatures. However the equations do not describe the thermal contribution of blood vessels. A countercurrent vascular network model which represents a more fundamental approach to modeling temperatures in tissue than do the generally used approximate equations such as the Pennes BHTE or effective thermal conductivity equations was presented in 1996. This type of model is capable of calculating the blood temperature in vessels and describing a vasculature in the tissue regions.</p> <p>Methods</p> <p>In this paper, a countercurrent blood vessel network (CBVN) model for calculating tissue temperatures has been developed for studying hyperthermia cancer treatment. We use a systematic approach to reveal the impact of a vasculature of blood vessels against a single vessel which most studies have presented. A vasculature illustrates branching vessels at the periphery of the tumor volume. The general trends present in this vascular model are similar to those shown for physiological systems in Green and Whitmore. The 3-D temperature distributions are obtained by solving the conduction equation in the tissue and the convective energy equation with specified Nusselt number in the vessels.</p> <p>Results</p> <p>This paper investigates effects of size of blood vessels in the CBVN model on total absorbed power in the treated region and blood flow rates (or perfusion rate) in the CBVN on temperature distributions during hyperthermia cancer treatment. Also, the same optimized power distribution during hyperthermia treatment is used to illustrate the differences between PBHTE and CBVN models. K_eff(effective thermal conductivity model) delivers the same difference as compared to the CBVN model. The optimization used here is adjusting power based on the local temperature in the treated region in an attempt to reach the ideal therapeutic temperature of 43°C. The scheme can be used (or adapted) in a non-invasive power supply application such as high-intensity focused ultrasound (HIFU). Results show that, for low perfusion rates in CBVN model vessels, impacts on tissue temperature becomes insignificant. Uniform temperature in the treated region is obtained.</p> <p>Conclusion</p> <p>Therefore, any method that could decrease or prevent blood flow rates into the tumorous region is recommended as a pre-process to hyperthermia cancer treatment. Second, the size of vessels in vasculatures does not significantly affect on total power consumption during hyperthermia therapy when the total blood flow rate is constant. It is about 0.8% decreasing in total optimized absorbed power in the heated region as γ (the ratio of diameters of successive vessel generations) increases from 0.6 to 0.7, or from 0.7 to 0.8, or from 0.8 to 0.9. Last, in hyperthermia treatments, when the heated region consists of thermally significant vessels, much of absorbed power is required to heat the region and (provided that finer spatial power deposition exists) to heat vessels which could lead to higher blood temperatures than tissue temperatures when modeled them using PBHTE.</p

Ixora parviflora Protects against UVB-Induced Photoaging by Inhibiting the Expression of MMPs, MAP Kinases, and COX-2 and by Promoting Type I Procollagen Synthesis

Ixora parviflora with high polyphenol content exhibited antioxidant activity and reducing UVB-induced intracellular reactive oxygen species production. In this study, results of the photoaging screening experiments revealed that IPE at 1000 μg/mL reduced the activity of bacterial collagenase by 92.7 ± 4.2% and reduced the activity of elastase by 32.6 ± 1.4%. Therefore, we investigated the mechanisms by which IPE exerts its anti-photoaging activity. IPE at 1 μg/mL led to an increase in type I procollagen expression and increased total collagen synthesis in fibroblasts at 5 μg/mL. We found that IPE inhibited MMP-1, MMP-3, and MMP-9 expression at doses of 1, 5, and 10 μg/mL, respectively, in fibroblasts exposed to UV irradiation (40 mJ/cm2). Gelatin zymography assay showed that IPE at 50 μg/mL inhibited MMP-9 secretion/activity in cultured fibroblasts after UVB exposure. In addition, IPE inhibited the phosphorylation of p38, ERK, and JNK induced by UVB. Furthermore, IPE inhibited the UVB-induced expression of Smad7. In addition, IPE at 1 μg/mL inhibited NO production and COX-2 expression in UV-exposed fibroblasts. These findings show that IPE exhibits anti-inflammatory and anti-photoaging activities, indicating that IPE could be a potential anti-aging agent

Effects of job rotation and role stress among nurses on job satisfaction and organizational commitment

<p>Abstract</p> <p>Background</p> <p>The motivation for this study was to investigate how role stress among nurses could affect their job satisfaction and organizational commitment, and whether the job rotation system might encourage nurses to understand, relate to and share the vision of the organization, consequently increasing their job satisfaction and stimulating them to willingly remain in their jobs and commit themselves to the organization. Despite the fact that there have been plenty of studies on job satisfaction, none was specifically addressed to integrate the relational model of job rotation, role stress, job satisfaction, and organizational commitment among nurses.</p> <p>Methods</p> <p>With top managerial hospital administration's consent, questionnaires were only distributed to those nurses who had had job rotation experience. 650 copies of the questionnaire in two large and influential hospitals in southern Taiwan were distributed, among which 532 valid copies were retrieved with a response rate of 81.8%. Finally, the SPSS 11.0 and LISREL 8.54 (Linear Structural Relationship Model) statistical software packages were used for data analysis and processing.</p> <p>Results</p> <p>According to the nurses' views, the findings are as follows: (1) job rotation among nurses could have an effect on their job satisfaction; (2) job rotation could have an effect on organizational commitment; (3) job satisfaction could have a positive effect on organizational commitment; (4) role stress among nurses could have a negative effect on their job satisfaction; and (5) role stress could have a negative effect on their organizational commitment.</p> <p>Conclusion</p> <p>As a practical and excellent strategy for manpower utilization, a hospital could promote the benefits of job rotation to both individuals and the hospital while implementing job rotation periodically and fairly. And when a medical organization attempts to enhance nurses' commitment to the organization, the findings suggest that reduction of role ambiguity in role stress has the best effect on enhancing nurses' organizational commitment. The ultimate goal is to increase nurses' job satisfaction and encourage them to stay in their career. This would avoid the vicious circle of high turnover, which is wasteful of the organization's valuable human resources.</p

Learning to predict expression efficacy of vectors in recombinant protein production

<p>Abstract</p> <p>Background</p> <p>Recombinant protein production is a useful biotechnology to produce a large quantity of highly soluble proteins. Currently, the most widely used production system is to fuse a target protein into different vectors in <it>Escherichia coli </it>(<it>E. coli</it>). However, the production efficacy of different vectors varies for different target proteins. Trial-and-error is still the common practice to find out the efficacy of a vector for a given target protein. Previous studies are limited in that they assumed that proteins would be over-expressed and focused only on the solubility of expressed proteins. In fact, many pairings of vectors and proteins result in no expression.</p> <p>Results</p> <p>In this study, we applied machine learning to train prediction models to predict whether a pairing of vector-protein will express or not express in <it>E. coli</it>. For expressed cases, the models further predict whether the expressed proteins would be soluble. We collected a set of real cases from the clients of our recombinant protein production core facility, where six different vectors were designed and studied. This set of cases is used in both training and evaluation of our models. We evaluate three different models based on the support vector machines (SVM) and their ensembles. Unlike many previous works, these models consider the sequence of the target protein as well as the sequence of the whole fusion vector as the features. We show that a model that classifies a case into one of the three classes (no expression, inclusion body and soluble) outperforms a model that considers the nested structure of the three classes, while a model that can take advantage of the hierarchical structure of the three classes performs slight worse but comparably to the best model. Meanwhile, compared to previous works, we show that the prediction accuracy of our best method still performs the best. Lastly, we briefly present two methods to use the trained model in the design of the recombinant protein production systems to improve the chance of high soluble protein production.</p> <p>Conclusion</p> <p>In this paper, we show that a machine learning approach to the prediction of the efficacy of a vector for a target protein in a recombinant protein production system is promising and may compliment traditional knowledge-driven study of the efficacy. We will release our program to share with other labs in the public domain when this paper is published.</p

Impact of body-mass factors on setup displacement in patients with head and neck cancer treated with radiotherapy using daily on-line image guidance

BACKGROUND: To determine the impact of body-mass factors (BMF) before radiotherapy and changes during radiotherapy on the magnitude of setup displacement in patients with head and neck cancer (HNC). METHODS: The clinical data of 30 patients with HNC was analyzed using the alignment data from daily on-line on-board imaging from image-guided radiotherapy. BMFs included body weight, body height, and the circumference and bilateral thickness of the neck. Changes in the BMFs during treatment were retrieved from cone beam computed tomography at the 10th and 20th fractions. Setup errors for each patient were assessed by systematic error (SE) and random error (RE) through the superior-inferior (SI), anterior-posterior (AP), and medial-lateral (ML) directions, and couch rotation (CR). Using the median values of the BMFs as a cutoff, the impact of the factors on the magnitude of displacement was assessed by the Mann–Whitney U test. RESULTS: A higher body weight before radiotherapy correlated with a greater AP-SE (p = 0.045), SI-RE (p = 0.023), and CR-SE (p = 0.033). A longer body height was associated with a greater SI-RE (p = 0.002). A performance status score of 1 or 2 was related to a greater AP-SE (p = 0.043), AP-RE (p = 0.015), and SI-RE (p = 0.043). Among the ratios of the BMFs during radiotherapy, the values at the level of mastoid tip at the 20(th) fraction were associated with greater setup errors. CONCLUSIONS: To reduce setup errors in patients with HNC receiving RT, the use of on-line image-guided radiotherapy is recommended for patients with a large body weight or height, and a performance status score of 1–2. In addition, adaptive planning should be considered for those who have a large reduction ratio in the circumference (<1) and thickness (<0.94) over the level of the mastoid tip during the 20(th) fraction of treatment

High-quality single InGaAs/GaAs quantum dot growth on a CMOS-compatible silicon substrate for quantum photonic applications

We present the direct heteroepitaxial growth of high-quality InGaAs quantum dots on silicon, enabling scalable, cost-effective quantum photonics devices compatible with CMOS technology. GaAs heterostructures are grown on silicon via a GaP buffer and defect-reducing layers. These epitaxial quantum dots exhibit optical properties akin to those on traditional GaAs substrates, promising vast potential for the heteroepitaxy approach. They demonstrate strong multi-photon suppression with $g^{(2)}(\tau)=(3.7\pm 0.2) \times 10^{-2}$ and high photon indistinguishability $V=(66\pm 19)$% under non-resonance excitation. We achieve up to ($18\pm 1$)% photon extraction efficiency with a backside distributed Bragg mirror, marking a crucial step toward silicon-based quantum nanophotonics