Years Of Input Research Articles

Airfield pavement performance prediction using Clustered Markov Chain Models

This study pairs unsupervised learning methods of clustering and classification with discrete-time Markov Chain models for airport pavement performance prediction, with the goal of allowing the clustering algorithm to take the place of typical pre-analysis grouping of pavement sections. The influences of cluster method, number of clusters, input years, interval time span, and training data on prediction results are analysed. Results indicate that clustering using the deterioration profiles of Pavement Condition Index (PCI) before applying the Markov Chain is sufficient to reduce the error by half in predicted pavement conditions for most cases. The initial pavement degradation is a reliable source for clustering and future condition prediction using the appropriately matched Markov Chain. This approach minimises the data required to predict pavement condition and proves the early deterioration rate of a pavement section can be used to predict its overall lifespan.

Neglecting the care of people with schizophrenia: here we go again.

Specialist early intervention teams consider clinician-patient engagement and continuity of care to be a driving philosophy behind the treatment they provide to people who have developed schizophrenia or a related psychotic illness. In almost all countries where this service model has been implemented there is a dearth of available data about what is happening to patients following time-limited treatment. Information on discharge pathways in England indicates that some early intervention specialists are discharging most of their patients from all psychiatric services after only 2 or 3 years of input. Some ex-patients will be living in a state of torment and neglect due to an untreated psychosis. In the UK, general practitioners should refuse to accept these discharge pathways for patients with insight-impairing mental illnesses.

Upgrading the genome of an elite japonica rice variety Kongyu 131 for lodging resistance improvement.

Developing a new rice variety requires tremendous efforts and years of input. To improve the defect traits of the excellent varieties becomes more cost and time efficient than breeding a completely new variety. Kongyu 131 is a high-performing japonica variety with early maturity, high yield, wide adaptability and cold resistance, but the poor-lodging resistance hinders the industrial production of Kongyu 131 in the Northeastern China. In this study, we attempted to improve the lodging resistance of Kongyu 131 from perspectives of both gene and trait. On the one hand, by QTL analysis and fine mapping we discovered the candidate gene loci. The following CRISPR/Cas9 and transgenic complementation study confirmed that Sd1 dominated the lodging resistance and favourable allele was mined for precise introduction and improvement. On the other hand, the Sd1 allelic variant was identified in Kongyu 131 by sequence alignment, then introduced another excellent allelic variation by backcrossing. Then, the two new resulting Kongyu 131 went through the field evaluation under different environments, planting densities and nitrogen fertilizer conditions. The results showed that the plant height of upgraded Kongyu 131 was 17%-26% lower than Kongyu 131 without penalty in yield. This study demonstrated a precise and targeted way to update the rice genome and upgrade the elite rice varieties by improving only a few gene defects from the perspective of breeding.

The role of input in native Spanish Late learners’ production and perception of English phonetic segments

Abstract This study evaluated the effect of input variation on the production and perception of English phonetic segments by native Spanish adults who had immigrated to the United States after the age of 16 years. The native Spanish (NS) participants were assigned to three groups of 20 each according to years of English input (years of U.S. residence multiplied by percent English use outside the home). Experiment 1 assessed the perceived relation between English and Spanish vowels. It yielded similar results for the NS groups designated “Low input” (M = 0.2 years of input), “Mid” (M = 1.2 years) and “High” (M = 3.0 years). Experiments 2–4 examined English vowel discrimination, vowel production and consonant discrimination. Apart from a modest improvement in vowel discrimination, these experiments showed little improvement as years of English input increased. One possible explanation for the essentially null finding of this study is that input matters little or not at all when an L2 is learned naturalistically following the closure of a critical period. Another possibility is that adequate native speaker input is crucial for L2 speech learning but the input differences evaluated here were insufficient to yield measurable improvements in performance. We conclude the article by illustrating a new technique that might be used to choose between these competing explanations.

The Second Green Revolution Will Bring Agri-Tech Breakthroughs to Growers

The Second Green Revolution Will Bring Agri-Tech Breakthroughs to Growers

Are matching funds for smallholder irrigation money well spent?

Groundwater irrigation can dramatically affect agricultural production and productivity. Despite its potential as an agricultural development tool, little credible evidence exists for the impacts of groundwater development on smallholder agriculture. We add to the evidence on the benefits of irrigation investments for small producers by evaluating the Rural Business Development (RBD) program of the Millennium Challenge Corporation in Nicaragua for small plantain producers. The RBD program offered matching funds covering up to 30% of the cost of two years of inputs, extension services, and diesel-powered micro-sprinkler irrigation for individual farms. In order to estimate the average impact of the RBD program on its beneficiaries, we combine model selection via the LASSO with doubly robust treatment effect estimation as applied to two years of panel data for 146 producers. We find that the program had substantial impacts on plantain revenue and production, while achieving nearly complete irrigation coverage of plantain land among beneficiaries. We find no discernible impact on household expenditure.

Combination of terrestrial reference frames based on space geodetic techniques in SHAO: methodology and main issues

Based on years of input from the four geodetic techniques (SLR, GPS, VLBI and DORIS), the strategies of the combination were studied in SHAO to generate a new global terrestrial reference frame as the material realization of the ITRS defined in IERS Conventions. The main input includes the time series of weekly solutions (or fortnightly for SLR 1983–1993) of observational data for satellite techniques and session-wise normal equations for VLBI. The set of estimated unknowns includes 3-dimensional Cartesian coordinates at the reference epoch 2005.0 of the stations distributed globally and their rates as well as the time series of consistent Earth Orientation Parameters (EOPs) at the same epochs as the input. Besides the final solution, namely SOL-2, generated by using all the inputs before 2015.0 obtained from short-term observation processing, another reference solution, namely SOL-1, was also computed by using the input before 2009.0 based on the same combination of procedures for the purpose of comparison with ITRF2008 and DTRF2008 and for evaluating the effect of the latest six more years of data on the combined results. The estimated accuracy of the x-component and y-component of the SOL-1 TRF-origin was better than 0.1 mm at epoch 2005.0 and better than 0.3 mm yr−1 in time evolution, either compared with ITRF2008 or DTRF2008. However, the z-component of the translation parameters from SOL-1 to ITRF2008 and DTRF2008 were 3.4 mm and −1.0 mm, respectively. It seems that the z-component of the SOL-1 TRF-origin was much closer to the one in DTRF2008 than the one in ITRF2008. The translation parameters from SOL-2 to ITRF2014 were 2.2, −1.8 and 0.9 mm in the x-, y- and z-components respectively with rates smaller than 0.4 mm yr−1. Similarly, the scale factor transformed from SOL-1 to DTRF2008 was much smaller than that to ITRF2008. The scale parameter from SOL-2 to ITRF2014 was −0.31 ppb with a rate lower than 0.01 ppb yr−1. The external precision (WRMS) compared with IERS EOP 08 C04 of the combined EOP series was smaller than 0.06 mas for the polar motions, smaller than 0.01 ms for the UT1-UTC and smaller than 0.02 ms for the LODs. The precision of the EOPs in SOL-2 was slightly higher than that of SOL-1.

Input and Age-Dependent Variation in Second Language Learning: A Connectionist Account.

Language learning requires linguistic input, but several studies have found that knowledge of second language (L2) rules does not seem to improve with more language exposure (e.g., Johnson & Newport, 1989). One reason for this is that previous studies did not factor out variation due to the different rules tested. To examine this issue, we reanalyzed grammaticality judgment scores in Flege, Yeni‐Komshian, and Liu's (1999) study of L2 learners using rule‐related predictors and found that, in addition to the overall drop in performance due to a sensitive period, L2 knowledge increased with years of input. Knowledge of different grammar rules was negatively associated with input frequency of those rules. To better understand these effects, we modeled the results using a connectionist model that was trained using Korean as a first language (L1) and then English as an L2. To explain the sensitive period in L2 learning, the model's learning rate was reduced in an age‐related manner. By assigning different learning rates for syntax and lexical learning, we were able to model the difference between early and late L2 learners in input sensitivity. The model's learning mechanism allowed transfer between the L1 and L2, and this helped to explain the differences between different rules in the grammaticality judgment task. This work demonstrates that an L1 model of learning and processing can be adapted to provide an explicit account of how the input and the sensitive period interact in L2 learning.

A general weighted least squares approach for the projection of input–output tables

ABSTRACTIn the context of input–output analysis, it is often necessary to update a matrix for a date when only the sum of its columns and rows are known. This projection problem is quite similar to temporal disaggregation. I borrow from this literature a class of solutions for which the exact result can be implemented without iteration. These solutions minimize the adjustment made to the out-of-date matrix and as such can be said optimal according to a chosen criteria. The framework I expose is flexible enough to encompass many of the existing methods and develop new ones. I propose one of such methods to project a matrix between two given benchmarks. I exemplify the technique on 35 years of input–output tables for France and show in particular that the issue of negative cells can be avoided.

Forecasting with CAPM

Capital asset pricing model is a popular formula using to calculate asset prices. This research looks at the sample forecasting of three CAPM constant beta model from 2005 to 2014. This research is going to look at the capabilities of CAPM by using the past varying. Five US sectors, five ASEAN countries and South Africa, for 11 portfolios will also be included in this research. Also the portfolios are also used testing amount of input years that will reduce the mispricing in both developed and developing markets.

Long-term doubling of litter inputs accelerates soil organic matter degradation and reduces soil carbon stocks

Soil organic matter (SOM) constitutes more than two-thirds of terrestrial carbon stocks yet there are many uncertainties about the fate of soil carbon reserves with global environmental change. Moisture, altered nutrient cycles, species shifts, growing season length or rising temperatures may alter forest primary productivity and the proportions of above and belowground biomass entering soil. We investigated SOM composition using molecular-level techniques after 20 years of detrital input and removal treatment (DIRT) at the Harvard Forest. SOM biomarkers (solvent extraction, base hydrolysis and cupric(II) oxide oxidation) and nuclear magnetic resonance (NMR) spectroscopy were used to quantify changes in SOM composition and microbial activity and community composition was assessed using phospholipid fatty acid (PLFA) analysis. Doubling aboveground litter inputs decreased soil carbon content, increased the degradation of labile SOM and enhanced the sequestration of aliphatic compounds in soil. The exclusion of belowground inputs resulted in a decrease in root-derived components and enhanced the degradation of stable SOM components such as leaf-derived aliphatic structures (cutin). The DIRT manipulations resulted in soil microbial community shifts that were attributed to the accelerated processing of specific SOM components. These results collectively reveal that a detailed molecular-level characterization of SOM can provide information on SOM compositional changes and transformations after 20 years of input manipulation in a temperate forest.

Investigation of the accuracy of historical irradiance products and interannual variability of solar irradiance using Met Office ground data

Met Office station data from 1980 to 2012 has been used to characterise the interannual variability of incident solar irradiance across the UK. The same data are used to evaluate four popular historical irradiance products to determine which are most suitable for use by the UK PV industry for site selection and system design. The study confirmed previous findings that interannual variability is typically 3–6% and weighted average probability of a particular percentage deviation from the mean at an average site in the UK was calculated. This weighted average showed that fewer than 2% of site-years could be expected to fall below 90% of the long-term site mean. The historical irradiance products were compared against Met Office station data from the input years of each product. This investigation has found that all products perform well. No products have a strong spatial trend. Meteonorm 7 is most conservative (MBE = −2.5%), CMSAF is most optimistic (MBE = +3.4%) and an average of all four products performs better than any one individual product (MBE = 0.3%).

Numerical modelling of floating debris in the world’s oceans

A global ocean circulation model is coupled to a Lagrangian particle tracking model to simulate 30years of input, transport and accumulation of floating debris in the world ocean. Using both terrestrial and maritime inputs, the modelling results clearly show the formation of five accumulation zones in the subtropical latitudes of the major ocean basins. The relative size and concentration of each clearly illustrate the dominance of the accumulation zones in the northern hemisphere, while smaller seas surrounded by densely populated areas are also shown to have a high concentration of floating debris. We also determine the relative contribution of different source regions to the total amount of material in a particular accumulation zone. This study provides a framework for describing the transport, distribution and accumulation of floating marine debris and can be continuously updated and adapted to assess scenarios reflecting changes in the production and disposal of plastic worldwide.

Perspectives on the eutrophication of the Yahara lakes

Eutrophication of the four Yahara lakes—Mendota, Monona, Waubesa, and Kegonsa—near Madison, Wisconsin, has been dramatic since the mid-1800s. For Lake Mendota, the erosion of sediments from higher water levels established by the damming of the lake's outlet, plus the agricultural expansion of its watershed, resulted in blue-green algal growths. These impacts, however, were dwarfed by water quality problems stemming from Madison's wastewater inputs that directly entered Lake Monona from the late 1800s through 1936, and then Lake Waubesa until 1958. Blue-green algal blooms were so bad in the lower Yahara lakes that the Madison Public Health Department conducted major copper sulfate treatments during 1925–1954. During the wastewater input years, inorganic nitrogen (N) and especially dissolved reactive phosphorus (DRP) concentrations in the surface waters were very high (particularly in Waubesa and Kegonsa), indicating neither nutrient was limiting algal growth. No P legacy from the wastewater inputs was found in Waubesa and Kegonsa's sediments; minimal P-binding potential due to low iron (Fe) availability is the hypothesized reason. Mendota's algal blooms were not a problem until the mid-1940s when wastewater inputs from upstream communities increased as well as the agricultural use of N and P fertilizers. This increase in eutrophication symptoms coincided with an increase in indices of DRP and inorganic N concentrations in the lake. After wastewater diversion in 1971, blue-green algal blooms persisted in Lake Mendota, and the onus of the problem shifted to agricultural and urban nonpoint source pollution. While much progress has been made in recent years to control these pollution sources to Mendota, manure runoff during late winter continues as a management problem. As evidence, P loadings during January to March constituted 48% of total loadings measured for 1990–2006 in the Yahara River subwatershed. Much of this runoff P was dissolved and not associated with high sediment loads, whereas during other months, more of the runoff P was bound to sediments that could settle out in lower stream reaches prior to entering the lake. However, low P-binding potential of recently deposited sediments in Mendota along with signs of water quality improvements following periods of drought indicate the lake could respond rapidly to nutrient input reductions. Finally, DRP and inorganic N concentrations since 1980 have indicated that algal growth in the Yahara lakes during July–August may have been limited by not only P, but N (especially in the lower Yahara lakes). Aggressive programs to reduce inputs from both nutrients will be important to prevent scum-forming blue-green algal blooms and filamentous algal growths that could become problematic once zebra mussels become established in the Yahara lakes.

Dr. William R. Maples and the Role of the Consultants at the U.S. Army Central Identification Laboratory, Hawaii

Abstract This paper discusses the history and role of the consultants at the U.S. Army Central Identification Laboratory. Hawaii (CILHI) and the many contributions made by Dr. William R. Maples as a CILHI consultant. For over eleven years Dr. Maples was a prominent and integral force at the CILHI. His involvement with the CILHI as a senior forensic anthropologist began in 1985. In 1986 Dr. Maples signed a contract with the U.S. Army to conduct on-going reviews of the CILHI. He was one of the original consultants and maintained this responsibility until his death. For a significant portion of his professional career Dr. Maples was dedicated to first improving and then maintaining the scientific integrity of the CILHI. The uncompromising ethical and scientific standards by which the Central Identification Laboratory operates today is a direct reflection of the years of input by Dr. William R. Maples.