HOUSEHOLD SIZE AND COMPOSITION IMPACTS ON MEAT DEMAND IN MEXICO: A CENSORED DEMAND SYSTEM APPROACH

The proposed paper adopts the censored demand system approach of Lee and Pitt (1986) to examine the structure of Mexican food demand. This approach uses the concept of virtual prices to explain specific purchase patterns. The contribution of our selected paper is the incorporation of the endogenous equivalence scale function proposed by Phlipps (1998) within this censored system. The contribution of this analysis is not only in terms of the use of an endogenous scaling function within a censored demand system, but we also will be use simulated maximum likelihood techniques which allows for the specification and estimation of significantly larger sized demand systems without the imposition of restrictive distributional assumptions on the equation error terms. We use a Gibbs sampling techniques to evaluate higher order truncated distributions required to implement the Lee and Pitt (1986) model specification.Demand and Price Analysis,

Dependence of quantum-Hall conductance on the edge-state equilibration position in a bipolar graphene sheet

By using four-terminal configurations, we investigated the dependence of longitudinal and diagonal resistances of a graphene p-n interface on the quantum-Hall edge-state equilibration position. The resistance of a p-n device in our four-terminal scheme is asymmetric with respect to the zero point where the filling factor ($\nu$) of the entire graphene vanishes. This resistance asymmetry is caused by the chiral-direction-dependent change of the equilibration position and leads to a deeper insight into the equilibration process of the quantum-Hall edge states in a bipolar graphene system.Comment: 5 pages, 4 figures, will be published in PR

Data augmentation and semi-supervised learning for deep neural networks-based text classifier

User feedback is essential for understanding user needs. In this paper, we use free-text obtained from a survey on sleep-related issues to build a deep neural networks-based text classifier. However, to train the deep neural networks model, a lot of labelled data is needed. To reduce manual data labelling, we propose a method which is a combination of data augmentation and pseudo-labelling: data augmentation is applied to labelled data to increase the size of the initial train set and then the trained model is used to annotate unlabelled data with pseudo-labels. The result shows that the model with the data augmentation achieves macro-averaged f1 score of 65.2% while using 4,300 training data, whereas the model without data augmentation achieves macro-averaged f1 score of 68.2% with around 14,000 training data. Furthermore, with the combination of pseudo-labelling, the model achieves macro-averaged f1 score of 62.7% with only using 1,400 training data with labels. In other words, with the proposed method we can reduce the amount of labelled data for training while achieving relatively good performance

A Comment on the Implementation of the Ziggurat Method

We show that the short period of the uniform random number generator in the published implementation of Marsaglia and Tsang's Ziggurat method for generating random deviates can lead to poor distributions. Changing the uniform random number generator used in its implementation fixes this issue.

A deep-learning approach for reservoir evaluation for shale gas wells with complex fracture networks

The complex fracture networks in shale gas reservoirs bring greater challenges and uncertainties to the modeling in reservoir evaluation. As the  emerging potential technology, deep learning can be usefully applied to many aspects of reservoir evaluation. To further conduct the reservoir evaluation in rate transient analysis, this work proposes a data-driven proxy model for accurately evaluating the horizontal wells with complex fracture networks in shales. The production time, variable bottom hole pressure, and the fracture networks properties are used as input variables, while the output variable refers to the production for the forecast time period. The data from boundary element method is used to generate the proxy model for the learning process. The method of shuffled cross-validation is used to increase the model’s accuracy and generalizability. The proxy model is coupled with recently developed deep learning methods such as attention mechanism, skip connection, and cross-validation to address the time series analysis problem for multivariate operating and physical parameters. Results demonstrate that the attention mechanism is robust. The operating parameters analysis shows that the attention mechanism has the ability to analyze variable pressure drop/flowrate data. Sensitivity analysis also indicates that the model takes into account the geometric characteristics of fracture network. The model reliability is proved by a case study from Marcellus shale. The computation time of the trained attention mechanism model is approximately 0.3 s, which equates to 3.8% of the physical model’s running time.Cited as: Chu, H., Dong, P., Lee, W. J. A deep-learning approach for reservoir evaluation for shale gas wells with complex fracture networks. Advances in Geo-Energy Research, 2023, 7(1): 49-65. https://doi.org/10.46690/ager.2023.01.0

A GATEWAY™ Destination Vector For High-Throughput Construction of Neurospora crassa histidine-3 Gene Replacement Plasmids

We report the construction of a Destination Vector, called pJHAM007, for the targeted integration of DNA sequences at the histidine-3 (his-3) locus of Neurospora crassa. pJHAM007 has all the necessary features required to perform a simple, rapid and efficient GATEWAY™ recombinational cloning with an Entry Clone to yield a his-3-gene replacement Destination Vector

Inhibition of REV-ERBs stimulates microglial amyloid-beta clearance and reduces amyloid plaque deposition in the 5XFAD mouse model of Alzheimer\u27s disease

A promising new therapeutic target for the treatment of Alzheimer\u27s disease (AD) is the circadian system. Although patients with AD are known to have abnormal circadian rhythms and suffer sleep disturbances, the role of the molecular clock in regulating amyloid-beta (Aβ) pathology is still poorly understood. Here, we explored how the circadian repressors REV-ERBα and β affected Aβ clearance in mouse microglia. We discovered that, at Circadian time 4 (CT4), microglia expressed higher levels of the master clock protein BMAL1 and more rapidly phagocytosed fibrillary A

The effect of high-speed power training on physical frailty in older adults: Effect of a visual-guided exercise program in South Korean rural areas

Objective. Exercise has been shown to be an effective intervention; the difficulty still lies in providing exercise programs to the older adults in rural areas. Therefore, this study aimed to examine the effects of a 12-week exercise program provided with visual guidelines (prerecorded video) on frailty among older adults in rural areas. Methods. Fifty participants (71.7 ± 4.9 years) from 5 different rural areas were recruited and divided into two groups: the exercise group (EX, n = 24 (male: 8, female: 18)) and the control group (CON, n = 26 (male: 7, female: 17)). With the commencement of the exercise intervention, a prerecorded high-speed power training program for frail older adults was distributed to the EX group. A new prerecorded exercise program was delivered to the EX group every 4 weeks. Frailty status was diagnosed with Fried’s criteria before and after the intervention. Muscle strength was measured in the upper and lower limb strength (hand-grip strength and leg extension and flexion), and physical function was measured using a short physical performance battery and gait speed. Fasting blood was collected before and after the intervention and analyzed for blood lipid profile. Results. After 12 weeks of the intervention period, a significant difference in frailty status () and score () favoring the EX group was observed. Physical functions (gait speed () and time for sit to stand ()) were significantly improved in the EX group with a significant increase in knee extensor strength (). A significant difference in serum high-density lipoprotein levels favoring the EX group () was also observed. Conclusions. This study confirmed the positive effect of a visual-guided exercise program on older adults’ residents in rural areas and provided alternative methods to effectively provide exercise program for the older adults with limited resources