Technical Change, Factor Bias and Input Adjustments: Panel Data Evidence from Irrigated Rice Production in Southern Palawan, Philippines

Approximately 90 percent of the world's production and consumption of rice occurs in Asia, and regional demand is projected to increase by 70 percent over the next 30 years. Meeting this demand requires an expansion of the total area under irrigation in the coming decades. In this article, the authors observe the factors of labor, fertilizer and pesticides in relation to a profit-maximizing combination of inputs for rice production, the reaction of these factors to technological improvements such as irrigation and machinery, and their implications on the environment, particularly upland forest resources.irrigation, irrigated rice production, upland forest resources, Palawan, Philippines

Technical Change, Factor Bias and Input Adjustments: Panel Data Evidence from Irrigated Rice Production in Southern Palawan, Philippines

Approximately 90 percent of the world's production and consumption of rice occurs in Asia, and regional demand is projected to increase by 70 percent over the next 30 years. Meeting this demand requires an expansion of the total area under irrigation in the coming decades. In this article, the authors observe the factors of labor, fertilizer and pesticides in relation to a profit-maximizing combination of inputs for rice production, the reaction of these factors to technological improvements such as irrigation and machinery, and their implications on the environment, particularly upland forest resources.irrigation, irrigated rice production, upland forest resources, Palawan, Philippines

Linking Economic Policy and Environmental Outcomes at a Watershed Scale

Do the most promising policies to promote sustainable upland farming originate at the local or national level? Will coordination of local and national efforts produce better outcomes? This paper uses an optimization-simulation model of the Manupali watershed in the Philippines to investigate these issues. It compares the economic and environmental effects of four sets of stylized policy changes: (1) local policies that restrict some forms of land use; (2) local attempts to subsidize environment-friendly technologies; (3) a crop-specific tax levied on vegetable production; and (4) a hybrid approach that seeks to coordinate local technology initiatives with a broader-based national pricing policy.watershed, soil conservation, economy-environment linkage, upland farming

Keyframe-based monocular SLAM: design, survey, and future directions

Extensive research in the field of monocular SLAM for the past fifteen years has yielded workable systems that found their way into various applications in robotics and augmented reality. Although filter-based monocular SLAM systems were common at some time, the more efficient keyframe-based solutions are becoming the de facto methodology for building a monocular SLAM system. The objective of this paper is threefold: first, the paper serves as a guideline for people seeking to design their own monocular SLAM according to specific environmental constraints. Second, it presents a survey that covers the various keyframe-based monocular SLAM systems in the literature, detailing the components of their implementation, and critically assessing the specific strategies made in each proposed solution. Third, the paper provides insight into the direction of future research in this field, to address the major limitations still facing monocular SLAM; namely, in the issues of illumination changes, initialization, highly dynamic motion, poorly textured scenes, repetitive textures, map maintenance, and failure recovery

Why Can’t Neural Networks Forecast Pandemics Better

Why can’t neural networks (NN) forecast better? In the major super-forecasting competitions, NN have typically under-performed when compared to traditional statistical methods. When they have performed well, the underlying methods have been ensembles of NN and statistical methods. Forecasting stock markets, medical, infrastructure dynamics, social activity or pandemics each have their own challenges. In this study, we evaluate the strengths of a collection of methods for forecasting pandemics such as Covid-19 using NN, statistical methods as well as parameterized mechanistic models. Forecasts of epidemics can inform public health response and decision making, so accurate forecasting is crucial for general public notification, timing and spatial targeting of intervention. We show that NN typically under-perform in forecasting Covid-19 active cases which can be attributed to the lack of training data which is common for forecasts. Our test data consists of the top ten countries for active Covid-19 cases early in the pandemic and is represented as a Time Series (TS). We found that Statistical methods outperform NN for most cases. Albeit, NN are still good pattern finders and we suggest that there are perhaps more productive ways other than purely data driven models of using NN to help produce better forecasts

Farmer’s Preference and Effect of Feeding Selected Local Forages with Concentrate on the Dry Matter Intake and Weight Gain Performance of Bonga Sheep under Alarigeta Farmer’s Management

A study was conducted at Alarigeta kebele which is located in southwestern Ethiopia of Kaffa Zone, Adiyo woreda. In an effort to address feed problem, this study was carried out  with the objective of identifying farmers preference of local forages for sheep and evaluating the effect of feeding selected local forages on the dry matter intake and weight gain performance of Bonga sheep reared under farmers management. Group discussion was conducted to listing and ranking of the preferred plant species was done through a questionnaire that was administered through a reconnaissance survey. Thirty intact male yearling sheep were divided in to six groups of five sheep based on their initial body weight in randomized complete block design (RCBD). Treatments were consist of six different local forages selected by farmers in study area; T1 (Convolvulus kilimandschari Engl.), T2 (Commelina benghalensis L.), T3 (Basella alba L.), T4 (Brugmansia suaveolens Bercht.),T5(Bothriocline schimperi Olivo) and T6(Triumfetta tomentosa Boj.). A daily dry matter intake of T3 (4301 g/day) and T (4400 g/day) are significantly higher (P<0.05) than other groups. The greatest body weight of sheep was recorded in T3(9.6 kg) and T4 (9.4kg) as compared to other treatment groups (P<0.05). Keywords: Bonga sheep, Dry matter intake, local forage Convolvulus kilimandschari Engl, Commelina benghalensis L, Basella alba L, Brugmansia suaveolens Bercht, Bothriocline schimperi Olivo, Triumfetta tomentosa Bo