AN INJECTION OF BASE MONEY AT ZERO INTEREST RATES: EMPIRICAL EVIDENCE FROM THE JAPANESE EXPERIENCE 2001-2006

Many macroeconomists and policymakers have debated the effectiveness of the quantitative monetary-easing policy (QMEP) that was introduced in Japan in 2001. This paper measures the effect of the QMEP on aggregate output and prices, and examines its transmission mechanism, based on the vector autoregressive (VAR) methodology. To ascertain the transmission mechanism, we include several financial market variables in the VAR system. The results show that the QMEP increased aggregate output through the stock price channel. This evidence suggests that further injection of base money is effective even when short-term nominal interest rates are at zero.Quantitative easing; Money injection; Portfolio rebalancing; Stock price channel; Vector autoregression

General Architecture for Hardware Implementation of Genetic Algorithm

FCCM 2006 : 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines , Apr 24-26, 2006 , Napa, CA, USAIn this paper, the authors propose a technique to flexibly implement genetic algorithms (GAs) for various problems on FPGAs. For the purpose, the authors propose a common architecture for GA. The proposed architecture allows designers to easily implement a GA as a hardware circuit consisting of parallel pipelines which execute GA operations. The proposed architecture is scalable to increase the number of parallel pipelines. The architecture is applicable to various problems and allows designers to estimate the size of resulting circuits. The authors give a model for predicting the size of resulting circuits from given parameters. Based on the proposed method, the authors have implemented a tool to facilitate GA circuit design and development. Through experiments using knapsack problem and traveling salesman problem (TSP), the authors show that the FPGA circuits synthesized based on the proposed method run much faster and consume much lower power than software implementation on a PC and the model can predict the size of the resulting circuit accurately enough

A Hardware Implementation Method of Multi-Objective Genetic Algorithms

CEC2006 : IEEE International Conference on Evolutionary Computation , Jul 16-21, 2006 , Vancouver, BC, CanadaMulti-objective genetic algorithms (MOGAs) are approximation techniques to solve multi-objective optimization problems. Since MOGAs search a wide variety of pareto optimal solutions at the same time, MOGAs require large computation power. In order to solve practical sizes of the multi objective optimization problems, it is desirable to design and develop a hardware implementation method for MOGAs with high search efficiency and calculation speed. In this paper, we propose a new method to easily implement MOGAs as high performance hardware circuits. In the proposed method, we adopt simple Minimal Generation Gap (MGG) model as the generation model, because it is easy to be pipelined. In order to preserve diversity of individuals, we need a special selection mechanism such as the niching method which takes large computation time to repeatedly compare superiority among all individuals in the population. In the proposed method, we developed a new selection mechanism which greatly reduces the number of comparisons among individuals, keeping diversity of individuals. Our method also includes a parallel execution architecture based on Island GA which is scalable to the number of concurrent pipelines and effective to keep diversity of individuals. We applied our method to multi-objective Knapsack Problem. As a result, we confirmed that our method has higher search efficiency than existing method

Flexible implementation of genetic algorithms on FPGAs

FPGA '06 : ACM/SIGDA 14th international symposium on Field programmable gate arrays , Feb 22-24, 2006 , Monterey, CA, USAGenetic algorithms (GAs) are useful since they can find near optimal solutions for combinatorial optimization problems quickly. Although there are many mobile/home applications of GAs such as navigation systems, QoS routing and video encoding systems, it was difficult to apply GAs to those applications due to low computational power of mobile/home appliances. In this paper, we propose a technique to flexibly implement genetic algorithms for various problems on FPGAs. For the purpose, we propose a basic architecture which consists of several modules for GA operations to compose a GA pipeline, and a parallel architecture consisting of multiple concurrent pipelines. The proposed architectures are simple enough to be implemented on FPGAs, applicable to various problems, and easy to estimate the size of the resulting circuit. We also propose a model for predicting the size of resulting circuit from given parameters consisting of the problem size, the number of concurrent pipelines and the number of candidate solutions for GA. Based on the proposed method, we have implemented a tool to facilitate GA circuit design and development. This tool allows designers to find appropriate parameter values so that the resulting circuit can be accommodated in the target FPGA device, and to automatically obtain RTL VHDL description. Through experiments using Knapsack Problem and TSP, we show that the FPGA circuits synthesized based on the proposed method run much faster and consume much lower power than software implementation on a PC and that our model can predict the size of the resulting circuit accurately enough

Response Rate Is Associated with Prolonged Survival in Patients with Advanced Non-small Cell Lung Cancer Treated with Gefitinib or Erlotinib

Introduction:Gaining a higher response rate (RR) has usually been determined as a primary end point in phase II trials evaluating the efficacy of new molecular targeted drugs. However, a relationship between clinical response and survival benefit has not been well studied in the patients treated with molecular targeted agents.Methods:Prospective trials of epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) monotherapy in non-small cell lung cancer were extracted from MEDLINE, EMBASE, and the annual meetings in 2007 of the American Society of Clinical Oncology, European Cancer Conference, and World Conference on Lung Cancer.Correlation between clinical response and survival was examined using linear regression analysis. We also tried to compare the significance of RR as surrogate markers for survival with that of disease control rate (DCR) by calculating the area under their receiver operating characteristic (ROC) curves.Results:We identified 24 phase II trials and 4 phase III trials with a total of 6171 patients and 30 treatment arms, including 22 arms for the gefitinib group and 8 arms for the erlotinib group. Both RR and DCR strongly correlated with median survival time (MST; p < 0.0001 and p = 0.003, respectively). In an ROC analysis, the area under the ROC curve predicting MST prolongation by RR was 0.918, which was higher than the area under the ROC curve by DCR.Conclusions:We found a significant relationship between RR and MST in clinical trials with EGFR-TKIs. RR could be an independent surrogate marker for MST in the current response criteria in the clinical trials of EGFR-TKIs

Pilot study of the optimal protocol of low dose step‐up follicle stimulating hormone therapy for infertile women

Purpose: To evaluate the optimized protocol of low dose follicle‐stimulating hormone (FSH) therapy that has a starting dose of 50 IU/62.5 IU with a small increment dose (12.5 IU) for women with World Health Organization (WHO) II ovulatory disorder and unexplained infertility. Methods: Anovulatory women with WHO group II ovulatory disorder (ovulation induction [OI] patients, n = 29), and with an unexplained infertility (ovarian stimulation [OS] patients, n = 21) were enrolled. The protocol of low dose step‐up FSH therapy was optimized for the starting dose as 50 IU (body mass index [BMI] < 20 group) and 62.5 IU (BMI ≥ 20 group) with the increment dose of 12.5 IU. Study outcomes were ovulation, monofollicular development and other variables. Results: In the OIpatients, the ovulation rate was 100% (BMI < 20 group) and 90.9% (BMI ≥ 20 group). Monofollicular development was 80.0% (BMI < 20) and 77.3% (BMI ≥ 20). The pregnancy rate was 60% (3/5 BMI < 20) and 18.2% (4/22 BMI ≥ 20). There was no multiple pregnancy. In the OSpatients, the ovulation rate was 100%. Monofollicular development was 85.7% (BMI < 20) and 76.6% (BMI ≥ 20). No pregnancy was achieved in the OSpatients. Conclusion: Optimized protocol of low dose FSH therapy setting a starting dose 50 IU/62.5 IU by BMI with an increment dose of 12.5 IU was safe and highly effective in WHO group II anovulatory patients. However, this protocol seemed uneffective for patients with unexplained infertility

Tuning of Sry expression by H3K9 methylation and demethylation

Histone H3 lysine 9 (H3K9) methylation is a hallmark of heterochromatin. H3K9 demethylation is crucial in mouse sex determination; The H3K9 demethylase Jmjd1a deficiency leads to increased H3K9 methylation at the Sry locus in embryonic gonads, thereby compromising Sry expression and causing male-to-female sex reversal. We hypothesized that the H3K9 methylation level at the Sry locus is finely tuned by the balance in activities between the H3K9 demethylase Jmjd1a and an unidentified H3K9 methyltransferase to ensure correct Sry expression. Here we identified the GLP/G9a H3K9 methyltransferase complex as the enzyme catalyzing H3K9 methylation at the Sry locus. Based on this finding, we tried to rescue the sex-reversal phenotype of Jmjd1a-deficient mice by modulating GLP/G9a complex activity. A heterozygous GLP mutation rescued the sex-reversal phenotype of Jmjd1a-deficient mice by restoring Sry expression. The administration of a chemical inhibitor of GLP/G9a enzyme into Jmjd1a-deficient embryos also successfully rescued sex reversal. Our study not only reveals the molecular mechanism underlying the tuning of Sry expression but also provides proof on the principle of therapeutic strategies based on the pharmacological modulation of epigenetic balance