Use of DNA-based genetic markers in plant breeding

Genetic markers have been used since the beginnings of plant breeding, but the concept of linkage and recently the availability of molecular markers have offered new and powerful tools that can help to perform the traditional tasks of selection or that can change the traditional breeding process. Markers can either be used in a descriptive manner to identify varieties, to study the ‘micro-evolution’ of composite crosses or variety mixtures or to analyse the breeding progress retrospectively in order to learn from the past. The operative use of markers in plant breeding is connected to the selection of parental lines and progeny lines. The possible implementation of these processes stretches from the introgression of specific chromosome fragments to ‘marker-based idiotype breeding’

Proceedings of the COST SUSVAR/ECO-PB Workshop on organic plant breeding strategies and the use of molecular markers

In many countries,national projects are in progress to investigate the sustainable low-input approach.In the present COST network,these projects are coordinated by means of exchange of materials,establishing common methods for assessment and statistical analyses and by combining national experimental results.The common framework is cereal production in low-input sustainable systems with emphasis on crop diversity.The network is organised into six Working Groups,five focusing on specific research areas and one focusing on the practical application of the research results for variety testing:1)plant genetics and plant breeding,2)biostatistics,3)plant nutrition and soil microbiology,4)weed biology and plant competition,5)plant pathology and plant disease resistance biology and 6)variety testing and certification.It is essential that scientists from many disciplines work together to investigate the complex interactions between the crop and its environment,in order to be able to exploit the natural regulatory mechanisms of different agricultural systems for stabilising and increasing yield and quality.The results of this cooperation will contribute to commercial plant breeding as well as official variety testing,when participants from these areas disperse the knowledge achieved through the EU COST Action

China's GDP in U.S. dollars based on purchasing power parity

China's gross domestic product per capita was only US$300 to$370 in 1980-91 in an estimate based on the World Bank Atlas approach used in the World Development Report. These estimates fail to capture the fact that in the 10 years since embarking on a program of economic reform aimed at rapid economic development, China has been one of the fastest growing economies in the world. Knowing what its true standard of living and productive potential is important not only for measuring the size of China's economy but for assessing its growth performance. The authors provide a detailed comparison of the GDP of China and the United States using the purchasing power parity approach formulated by the U.N. International Comparison Program (ICP), with 1986 as a base. Using this approach, which establishes a conversion factor based on prices for comparable items rather than on exchange rates, they find that: 1) China's per capita GDP in 1986 international dollars in between $770 and$1,044, depending on assumptions made about comparison-resistant service sectors and quality adjustments made in a number of selected ones in calculating purchasing power parities; and 2) China's per capita GDP in 1991 international dollars is between $1,227 and$1,663, allowing for the impact of inflation in the United States on the purchasing power parity and growth rates in China computed from national currency GDP data in constant prices.Environmental Economics&Policies,Economic Theory&Research,Payment Systems&Infrastructure,Public Health Promotion,Health Economics&Finance,Economic Theory&Research,Environmental Economics&Policies,Health Economics&Finance,Access to Markets,Markets and Market Access

Operations Research in the High Tech Military Environment: A Survey

The use of operations research as a technology to solve many of the problems of government and industry has become a major field of study within the very short span of the last fifty years. In the paper entitled, Operations Research in the High Tech Military Environment: A Survey, the reader is provided with a better understanding of the tenets of operations research through an examination of a representative sample of the latest operations research applications developed for the high tech environment. Initially, this involves providing the reader with some fundamental insights into what operations research is, what its practitioners do, and how the state-of-the-art has evolved to its present form. It then involves providing a brief description of what is meant by the term, high tech military environment. A survey, which constitutes the bulk of the material presented, focuses on how various operations research methodologies are being used within that environment. The paper concludes with a discussion of the possible directions operations research will take in the future, based on the present state-of-the-art

Machine learning computational tools to assist the performance of systematic reviews : A mapping review

Within evidence-based practice (EBP), systematic reviews (SR) are considered the highest level of evidence in that they summarize the best available research and describe the progress in a determined field. Due its methodology, SR require significant time and resources to be performed; they also require repetitive steps that may introduce biases and human errors. Machine learning (ML) algorithms therefore present a promising alternative and a potential game changer to speed up and automate the SR process. This review aims to map the current availability of computational tools that use ML techniques to assist in the performance of SR, and to support authors in the selection of the right software for the performance of evidence synthesis. The mapping review was based on comprehensive searches in electronic databases and software repositories to obtain relevant literature and records, followed by screening for eligibility based on titles, abstracts, and full text by two reviewers. The data extraction consisted of listing and extracting the name and basic characteristics of the included tools, for example a tool's applicability to the various SR stages, pricing options, open-source availability, and type of software. These tools were classified and graphically represented to facilitate the description of our findings. A total of 9653 studies and 585 records were obtained from the structured searches performed on selected bibliometric databases and software repositories respectively. After screening, a total of 119 descriptions from publications and records allowed us to identify 63 tools that assist the SR process using ML techniques. This review provides a high-quality map of currently available ML software to assist the performance of SR. ML algorithms are arguably one of the best techniques at present for the automation of SR. The most promising tools were easily accessible and included a high number of user-friendly features permitting the automation of SR and other kinds of evidence synthesis reviews. The online version contains supplementary material available at 10.1186/s12874-022-01805-4

Declines in student achievement in science-- implications for public education

During the 1960s and 1970s, major innovative science curricula were introduced into public schools in the United States, and federal funds were used to improve the quality of science teachers. Nevertheless, student achievement in science has generally declined since 1963. This research focused on changes in four of the key variables related to science achievement--teachers, students, curricula, and school goals. The research examined (a) meta-analyses of the effectiveness of the innovative science curricula on student achievement, (b) research on changes in teacher and student characteristics during the last 30 years, (c) educational literature on changes in the goals of public education during this same period, and (d) changes in student achievement. The results of this research suggest that the recent declines in science achievement are related to changes in student motivation, school goals, and school autonomy. The data indicate that contrary to the claims of some recent education commission reports, teachers and curricula have improved steadily over the last three decades. The conclusions developed from this research suggest that a number of the current educational reforms such as teacher competency testing, merit pay, curricular reform, student competency testing, and year-round schools should have little positive effect on student achievement. The research also suggests that parental involvement in education could have a negative influence on science achievement. The findings do suggest that schools of choice, corporate educational partnerships, and teacher empowerment could significantly improve student science achievement

Characterization of Infants' General Movements Using a Commercial RGB-Depth Sensor and a Deep Neural Network Tracking Processing Tool: An Exploratory Study

Cerebral palsy, the most common childhood neuromotor disorder, is often diagnosed through visual assessment of general movements (GM) in infancy. This skill requires extensive training and is thus difficult to implement on a large scale. Automated analysis of GM performed using low-cost instrumentation in the home may be used to estimate quantitative metrics predictive of movement disorders. This study explored if infants' GM may be successfully evaluated in a familiar environment by processing the 3D trajectories of points of interest (PoI) obtained from recordings of a single commercial RGB-D sensor. The RGB videos were processed using an open-source markerless motion tracking method which allowed the estimation of the 2D trajectories of the selected PoI and a purposely developed method which allowed the reconstruction of their 3D trajectories making use of the data recorded with the depth sensor. Eight infants' GM were recorded in the home at 3, 4, and 5 months of age. Eight GM metrics proposed in the literature in addition to a novel metric were estimated from the PoI trajectories at each timepoint. A pediatric neurologist and physiatrist provided an overall clinical evaluation from infants' video. Subsequently, a comparison between metrics and clinical evaluation was performed. The results demonstrated that GM metrics may be meaningfully estimated and potentially used for early identification of movement disorders